Optimizing beta-lactam antibiotic dosing in critically ill patients:
Prolonged infusion versus intermittent bolus administration
Mohd Hafiz Abdul Aziz
BPharm (Hons), MClinPharm
A thesis submitted for the degree of Doctor of Philosophy at
The University of Queensland in 2015
School of Medicine
i
Abstract
Severe sepsis is a major burden in the intensive care unit (ICU) with persistently high mortality
rates. Optimization of antibiotic dosing has been suggested as an intervention to improve clinical
outcomes for critically ill patients with severe sepsis. However, current antibiotic dosing guidelines
may not be appropriate for these patients, as they rarely consider the altered physiology and illness
severity associated with this population. Optimizing antibiotic dosing using pharmacokinetic (PK)
and pharmacodynamic (PD) principles can address these critical illness-related changes and
promote therapeutic success. Due to their wide spectrum of antibiotic activity and excellent safety
profile, beta-lactam antibiotics are commonly used for severe infections in the ICU. Two alternative
dosing approaches to traditional intermittent bolus (IB) dosing, namely continuous infusion (CI)
and extended infusion (EI), have been suggested to maximize the therapeutic potential of these
antibiotics in critically ill patients. Collectively, the two dosing approaches can also be referred as
prolonged infusion (PI).
This Thesis aims to better characterize the pharmacokinetics/pharmacodynamics (PK/PD) of beta-
lactam antibiotics to determine whether there is any therapeutic advantage associated with PI dosing
(CI and/or EI) as compared to IB dosing.
This Thesis comprises of eight chapters. Chapter 1 is an introductory chapter which provides an
overview of the published literature on the area of research. The discussion in Chapter 1 presents a
theoretical framework behind the Thesis objectives. Chapter 1 concludes with the specific aims of
this Thesis.
Chapter 2 reports the findings of a prospective PK study which aimed to describe the population PK
of doripenem in critically ill patients with sepsis and perform dosing simulations to develop
clinically relevant dosing guidelines for these patients. Twelve critically ill participants receiving
500 mg of doripenem 8-hourly as a 1-hr infusion were enrolled. The volume of distribution (Vd)
and clearance (CL) of doripenem in this patient cohort were substantially different than those
usually described in non-critically patients. As current dosing guidelines were mostly derived from
the non-critically ill, findings from this study suggest that the licensed “one-dose-fits-all” dosing for
doripenem is unlikely to achieve optimal exposures in critically ill patients. Empirical use of PI
dosing should be considered to account for PK and illness severity differences, particularly when
less-susceptible pathogens are involved.
ii
Chapter 3 incorporates a published systematic review which compares the PK/PD data and clinical
outcomes between CI and IB dosing to describe any potential merits supporting either of the two
dosing approaches for critically ill patients. The findings suggest that beta-lactam CI may not be
advantageous for all critically ill patients and may be beneficial in patients with severe infections.
Chapter 4 describes the findings of a post hoc analysis on the Defining Antibiotic Levels in
Intensive care unit patients (DALI) study, which recruited critically ill patients from 68 ICUs across
10 countries. The analysis aimed to compare the PK/PD target attainment and clinical outcomes
between PI (CI and EI) and IB dosing of meropenem and piperacillin/tazobactam in 182 critically
ill patients. In this analysis, PI dosing significantly increased the target attainment for most PK/PD
end-points. Data from this chapter also suggest that the critically ill patients who are most likely to
benefit from altered dosing strategies are those with severe pneumonia and not receiving renal
replacement therapy (RRT).
Chapter 5 is a published review article which scrutinizes the methodology of clinical studies
comparing CI versus IB dosing of beta-lactam antibiotics. Several issues and problems in the
interpretation of results obtained from these studies are discussed. This finally led to a proposal of
how a methodologically robust study should be performed to test the clinical outcome differences of
CI versus IB dosing of beta-lactam antibiotics in critically ill patients.
Chapter 6 reports the findings of the Beta-Lactam In Severe Sepsis (BLISS) study, which was a
two-centre, randomized controlled trial of CI versus IB dosing of beta-lactam antibiotics, enrolling
140 critically ill participants with severe sepsis who were not on RRT. This study aimed to
determine if CI is associated with better clinical outcomes and PK/PD target attainment in critically
ill patients, as opposed to IB dosing. In this study, CI of beta-lactam antibiotics demonstrated higher
clinical cure rates and better PK/PD target attainment than IB dosing. The findings suggest that
beta-lactam CI may be most beneficial for critically ill patients with severe infections, who are
infected with less-susceptible microorganisms.
Chapter 7 incorporates a published review article which systematically analyses the relevance of
PK/PD characteristics of antibiotics and their potential roles in maximizing patient outcomes and
preventing the emergence of antibiotic resistance. Based on the collated data, dosing approaches
which are likely to reduce the risk of antibiotic resistance in the ICU were also proposed.
iii
Chapter 8 will be the final chapter in this Thesis and summarizes the clinical findings of all the
work and highlight potential areas of future research.
iv
Declaration by author
This thesis is composed of my original work, and contains no material previously published or
written by another person except where due reference has been made in the text. I have clearly
stated the contribution by others to jointly-authored works that I have included in my thesis.
I have clearly stated the contribution of others to my thesis as a whole, including statistical
assistance, survey design, data analysis, significant technical procedures, professional editorial
advice, and any other original research work used or reported in my thesis. The content of my thesis
is the result of work I have carried out since the commencement of my research higher degree
candidature and does not include a substantial part of work that has been submitted to qualify for
the award of any other degree or diploma in any university or other tertiary institution. I have
clearly stated which parts of my thesis, if any, have been submitted to qualify for another award.
I acknowledge that an electronic copy of my thesis must be lodged with the University Library and,
subject to the policy and procedures of The University of Queensland, the thesis be made available
for research and study in accordance with the Copyright Act 1968 unless a period of embargo has
been approved by the Dean of the Graduate School.
I acknowledge that copyright of all material contained in my thesis resides with the copyright
holder(s) of that material. Where appropriate I have obtained copyright permission from the
copyright holder to reproduce material in this thesis.
v
Publications during candidature
Published manuscript
Mohd Hafiz AA, Staatz CE, Kirkpatrick CM, Lipman J, Roberts JA. Continuous infusion vs. bolus
dosing: implications for beta-lactam antibiotics. Minerva Anestesiologica 2012; 78(1): 94-104.
Abdul-Aziz MH, Dulhunty JM, Bellomo R, Lipman J, Roberts JA. Continuous beta-lactam
infusion in critically ill patients: the clinical evidence. Annals of Intensive Care 2012; 2(1): 37.
Jamal JA, Abdul-Aziz MH, Lipman J, Roberts JA. Defining antibiotic dosing in lung infections.
Clinical Pulmonary Medicine 2013; 20(3): 121-128.
Roberts JA, Abdul-Aziz MH, Lipman J, Mouton JW, Vinks AA, Felton TW, Hope WW, Farkas A,
Neely MN, Schentag JJ, Drusano G, Frey OR, Theuretzbacher U, Kuti JL. Individualised antibiotic
dosing for patients who are critically ill: challenges and potential solutions. Lancet Infectious
Diseases 2014; 14(6): 498-509.
Abdul-Aziz MH, McDonald C, McWhinney B, Ungerer JP, Lipman J, Roberts JA. Low
flucloxacillin concentrations in a patient with central nervous system infection: the need for plasma
and cerebrospinal fluid drug monitoring in the ICU. Annals of Pharmacotherapy 2014; 48(10):
1380-1384.
Abdul-Aziz MH, Lipman J, Mouton JW, Hope WW, Roberts JA. Applying
pharmacokinetic/pharmacodynamic principles in critically ill patients: optimizing efficacy and
reducing resistance development. Seminars in Respiratory and Critical Care Medicine 2015; 36(1):
136-153.
Abdul-Aziz MH, Abd Rahman AN, Mat-Nor MB, Sulaiman H, Wallis SC, Lipman J, Roberts JA,
Staatz CE. Population pharmacokinetics of doripenem in critically ill patients with sepsis in a
Malaysian intensive care unit. Antimicrobial Agents and Chemotherapy 2015; 60(1): 206-214.
Abdul-Aziz MH, Lipman J, Akova M, Bassetti M, De Waele JJ, Dimopoulos G, Dulhunty J,
Kaukonen KM, Koulenti D, Martin C, Montravers P, Rello J, Rhodes A, Starr T, Wallis SC,
Roberts JA, DALI Study Authors. Is prolonged infusion of piperacillin/tazobactam and meropenem
vi
in critically ill patients associated with improved pharmacokinetic/pharmacodynamic and patient
outcomes? An observation from the Defining Antibiotic Levels in Intensive care unit patients
(DALI) cohort. Journal of Antimicrobial Chemotherapy 2016; 71(1): 196-207.
Alobaid AS, Brinkman A, Frey OR, Roehr AC, Luque S, Grau S, Wong G, Abdul-Aziz MH,
Roberts MS, Lipman J, Roberts JA. What is the effect of obesity on piperacillin and meropenem
trough concentrations in critically ill patients? Journal of Antimicrobial Chemotherapy 2016; 71(3):
696-702.
Abdul-Aziz MH, Helmi S, Mat-Nor MB, Rai V, Wong KK, Hasan MS, Abd Rahman AN, Jamal
JA, Wallis SC, Lipman J, Staatz CE, Roberts JA. BLISS: Beta-Lactam Infusion in Severe Sepsis: a
prospective, two-centre, open-labelled, randomized controlled trial of continuous versus intermittent
beta-lactam infusion in critically ill patients with severe sepsis. Intensive Care Medicine 2016.
Roberts JA, Abdul-Aziz MH, Davis JS, Dulhunty JM, Cotta MO, Myburgh J, Bellomo R, Lipman
J. Continuous versus intermittent beta-lactam infusion in severe sepsis: a meta-analysis of
individual patient data from randomized trials. Am J Respir Crit Care Med 2016.
Conference abstracts
Oral presentation at international conference
Abdul-Aziz MH, Sulaiman H, Mat-Nor MB, Rai V, Wong KK, Hasan MS, Wallis SC, Lipman J,
Staatz CE, Roberts JA. The BLISS Study: Beta-Lactam Infusion in Severe Sepsis: Randomized
controlled trial of continuous versus intermittent beta-lactam infusion in critically ill patients with
severe sepsis in a Malaysian ICU setting. 55th Interscience Conference on Antimicrobial Agents and
Chemotherapy (ICAAC), San Diego, USA, 17-21st September 2015.
Poster presentations
Abdul-Aziz MH, Roberts JA, Akova, Bassetti M, De Waele JJ, Dimopoulos G, Kaukonen KM,
Koulenti D, Martin C, Montravers P, Rello J, Rhodes A, Starr T, Wallis SC, Lipman J. DALI:
Defining Antibiotic Levels in Intensive care unit patients: prolonged infusion of beta-lactam
antibiotics in critically ill patients. 53rd Interscience Conference on Antimicrobial Agents and
Chemotherapy (ICAAC), Denver, USA, 10-13th September 2013.
vii
Abdul-Aziz MH, Udy AA, Wallis SC, Roberts MS, Lipman J, Roberts JA. Plasma and
subcutaneous tissue pharmacokinetics of piperacillin in a large cohort of critically ill patients with
sepsis. 24th European Congress of Clinical Microbiology and Infectious Diseases (ECCMID),
Barcelona, Spain, 10-13th May 2014.
viii
Publications included in this thesis
Abdul-Aziz MH, Abd Rahman AN, Mat-Nor MB, Sulaiman H, Wallis SC, Lipman J, Roberts JA,
Staatz CE. Population pharmacokinetics of doripenem in critically ill patients with sepsis in a
Malaysian intensive care unit. Antimicrobial Agents and Chemotherapy 2015; 60(1): 206-214 –
incorporated as Chapter 2.
Contributor Statement of contribution
Mohd Hafiz Abdul-Aziz (Candidate) Conception and design of the study (60%)
Literature review (70%)
Data collection (70%)
Bioanalysis (30%)
Pharmacokinetic/pharmacodynamic analysis (50%)
Preparation of the manuscript (100%)
Azrin N. Abd Rahman Data collection (10%)
Pharmacokinetic/pharmacodynamic analysis (30%)
Critical review of the manuscript (10%)
Mohd-Basri Mat-Nor Data collection (20%)
Critical review of the manuscript (10%)
Helmi Sulaiman Critical review of the manuscript (10%)
Steven C. Wallis Bioanalysis (70%)
Critical review of the manuscript (10%)
Jeffrey Lipman Critical review of the manuscript (10%)
Jason A. Roberts Conception and design of the study (20%)
Literature review (20%)
Pharmacokinetic/pharmacodynamic analysis (10%)
Critical review of the manuscript (20%)
Christine E. Staatz Conception and design of the study (20%)
Literature review (10%)
Pharmacokinetic/pharmacodynamic analysis (10%)
Critical review of the manuscript (30%)
ix
Mohd Hafiz AA, Staatz CE, Kirkpatrick CM, Lipman J, Roberts JA. Continuous infusion vs. bolus
dosing: implications for beta-lactam antibiotics. Minerva Anestesiologica 2012; 78(1): 94-104 –
incorporated as Chapter 3.
Contributor Statement of contribution
Mohd Hafiz Abdul-Aziz (Candidate) Conception and design of the manuscript (30%)
Literature review (80%)
Preparation of the manuscript (100%)
Christine E. Staatz Critical review of the manuscript (40%)
Carl M. J. Kirkpatrick Critical review of the manuscript (10%)
Jeffrey Lipman Conception and design of the manuscript (20%)
Critical review of the manuscript (10%)
Jason A. Roberts Conception and design of the manuscript (50%)
Literature review (20%)
Critical review of the manuscript (40%)
Abdul-Aziz MH, Lipman J, Akova M, Bassetti M, De Waele JJ, Dimopoulos G, Dulhunty J,
Kaukonen KM, Koulenti D, Martin C, Montravers P, Rello J, Rhodes A, Starr T, Wallis SC,
Roberts JA, DALI Study Authors. Is prolonged infusion of piperacillin/tazobactam and meropenem
in critically ill patients associated with improved pharmacokinetic/pharmacodynamic and patient
outcomes? An observation from the Defining Antibiotic Levels in Intensive care unit patients
(DALI) cohort. Journal of Antimicrobial Chemotherapy 2016; 71(1): 196-207 – incorporated as
Chapter 4.
Contributor Statement of contribution
Mohd Hafiz Abdul-Aziz (Candidate) Literature review (50%)
Bioanalysis (20%)
Data analysis (70%)
Preparation of the manuscript (100%)
Jeffrey Lipman Conception and design of the study (50%)
Critical review (5%)
Murat Akova Data collection (5%)
Critical review (5%)
x
Matteo Bassetti Data collection (5%)
Critical review (5%)
Jan J. De Waele Literature review (10%)
Data collection (5%)
Critical review (5%)
George Dimopoulos Data collection (5%)
Critical review (5%)
Joel Dulhunty Data analysis (15%)
Critical review (5%)
Kirsi M. Kaukonen Data collection (5%)
Critical review (5%)
Despoina Koulenti Data collection (5%)
Critical review (5%)
Claude Martin Data collection (5%)
Critical review (5%)
Philippe Montravers Data collection (5%)
Critical review (5%)
Jordi Rello Literature review (10%)
Data collection (5%)
Critical review (5%)
Andrew Rhodes Data collection (5%)
Critical review (5%)
Therese Starr Data collection (50%)
Critical review (5%)
Steven C. Wallis Bioanalysis (80%)
Critical review (5%)
Jason A. Roberts Conception and design of the study (50%)
Literature review (30%)
Data analysis (15%)
Critical review (30%)
xi
Abdul-Aziz MH, Dulhunty JM, Bellomo R, Lipman J, Roberts JA. Continuous beta-lactam
infusion in critically ill patients: the clinical evidence. Annals of Intensive Care 2012; 2(1): 37 –
incorporated as Chapter 5.
Contributor Statement of contribution
Mohd Hafiz Abdul-Aziz (Candidate) Conception and design of the manuscript (30%)
Literature review (90%)
Preparation of the manuscript (100%)
Joel M. Dulhunty Critical review of the manuscript (20%)
Rinaldo Bellomo Conception and design of the manuscript (20%)
Critical review of the manuscript (30%)
Jeffrey Lipman Conception and design of the manuscript (10%)
Critical review of the manuscript (10%)
Jason A. Roberts Conception and design of the manuscript (40%)
Literature review (20%)
Critical review of the manuscript (40%)
Abdul-Aziz MH, Helmi S, Mat-Nor MB, Rai V, Wong KK, Hasan MS, Abd Rahman AN, Jamal
JA, Wallis SC, Lipman J, Staatz CE, Roberts JA. BLISS: Beta-Lactam Infusion in Severe Sepsis: a
prospective, two-centre, open-labelled, randomized controlled trial of continuous versus intermittent
beta-lactam infusion in critically ill patients with severe sepsis. Intensive Care Medicine 2016 –
incorporated as Chapter 6.
Contributor Statement of contribution
Mohd Hafiz Abdul-Aziz (Candidate) Conception and design of the study (50%)
Literature review (80%)
Data collection (30%)
Bioanalysis (30%)
Data analysis (70%)
Preparation of the manuscript (100%)
Helmi Sulaiman Conception and design of the study (10%)
Data collection (30%)
Critical review (5%)
xii
Mohd-Basri Mat-Nor Conception and design of the study (10%)
Critical review (5%)
Vineya Rai Data collection (10%)
Critical review (5%)
Kang K. Wong Data collection (10%)
Critical review (5%)
Mohd S. Hasan Data collection (10%)
Critical review (5%)
Azrin N. Abd Rahman Data collection (10%)
Critical review (5%)
Janattul-Ain Jamal Bioanalysis (10%)
Critical review (5%)
Steven C. Wallis Bioanalysis (60%)
Critical review (5%)
Jeffrey Lipman Data analysis (10%)
Critical review (10%)
Christine E. Staatz Critical review (20%)
Jason A. Roberts Conception and design of the study (30%)
Literature review (20%)
Data analysis (20%)
Critical review (30%)
Abdul-Aziz MH, Lipman J, Mouton JW, Hope WW, Roberts JA. Applying
pharmacokinetic/pharmacodynamic principles in critically ill patients: optimizing efficacy and
reducing resistance development. Seminars in Respiratory and Critical Care Medicine 2015; 36(1):
136-153 – incorporated as Chapter 7.
Contributor Statement of contribution
Mohd Hafiz Abdul-Aziz (Candidate) Conception and design of the manuscript (10%)
Literature review (60%)
Preparation of the manuscript (100%)
Jeffrey Lipman Conception and design of the manuscript (30%)
Critical review of the manuscript (15%)
xiii
Johan W. Mouton Conception and design of the manuscript (30%)
Literature review (10%)
Critical review of the manuscript (30%)
William W. Hope Literature review (10%)
Critical review of the manuscript (15%)
Jason A. Roberts Conception and design of the manuscript (30%)
Literature review (20%)
Critical review of the manuscript (40%)
xiv
Contributions by others to the thesis
The contributions of others to study conception, data collection, sample processing and bioanalysis,
data analysis, drafting and critical review of the manuscripts arising from this Thesis are detailed in
each chapter. Additional contributions of others are described in the acknowledgement section of
each chapter of the Thesis.
Statement of parts of the thesis submitted to qualify for the award of another
degree
None
xv
Acknowledgements
I would like to acknowledge the scholarship provided by the Ministry of Education, Malaysia as
well as the research funds granted by the International Islamic University of Malaysia, all of which
has allowed me to perform and complete the planned projects.
The work presented in this Thesis has stemmed from significant contributions of time and effort
from a number of individuals. First and foremost, I am hugely indebted and would like to pay
homage to my principal advisor, Prof. Jason Roberts. This work would not have been possible
without your guidance and continual support. Having read a lot of your previous works, I never
thought that one day I would be meeting you, let alone being accepted as one of your students.
Thank you for your “leap of faith” on me and I hope you have not regretted that decision.
Throughout this challenging journey, you have been my teacher, my guide, my consultant, my
advisor, my problem solver and most importantly, my mentor. If I can be half as good as you are
now, I will consider myself blessed!
I would also like to express my deepest appreciation to my co-advisors, Dr. Christine Staatz and
Prof. Jeffrey Lipman, for their indispensable words of encouragement and unwavering support
offered to me throughout this journey. I am extremely indebted for the amount of time they set aside
for my studies, particularly for reading my manuscripts! I have learnt a lot from these two
individuals on hard work and it has been such a great honour to have been working with them.
I would like to thank everyone at the Burns, Trauma and Critical Care Research Centre (BTCCRC)
for having me and making this journey a smooth and a memorable one. Special thanks go to Dr.
Steven Wallis and Suzanne Parker-Scott. Had I known them earlier, I would most likely choose to
be a chemist rather than a pharmacist! My thanks are also reserved for Jenny Ordonez and Yamarly
Guerra, for without their help, I would have not completed the bioanalysis of all samples within the
stipulated time.
To my beautiful wife, Nurul Azrin Abd Rahman, thank you for joining me in this highly-emotional
roller coaster ride. You remained by my side through thick and thin, through all of its ups and
downs, as we made our way through the ebbs and flows of this emotional journey. Your tolerance
towards my “behaviours” and “carelessness” throughout these years is a testament of your
unflinching support and devotion. You’re the most intelligent and analytical person I have ever
known bar none, and with you by my side it feels that I can do anything.
xvi
To my dearest Mom, Norhaini Osman, this Thesis is dedicated for you. You’re the reason why I’m
here today and thank you for giving me all the things that I ever wanted in this life. You have
always stood by me like a firm rock, a pillar in my time of need and everything I have achieved in
this life, I absolutely owe them to you.
xvii
Keywords
Beta-lactam antibiotics, cefepime, continuous infusion, critically ill, doripenem, intermittent bolus,
meropenem, pharmacokinetics, pharmacodynamics, piperacillin/tazobactam.
Australian and New Zealand Standard Research Classifications (ANZSRC)
ANZSRC code: 11502, Clinical Pharmacology and Therapeutics, 50%
ANZSRC code: 110309, Infectious Disease, 25%
ANZSRC code: 110310, Intensive Care, 25%
Fields of Research (FoR) Classification
FoR code: 1103, Clinical Sciences, 80%
FoR code: 1115, Pharmacology and Pharmaceutical Sciences, 20%
xviii
Table of contents
Abstract ................................................................................................................................................ i
Declaration by author ....................................................................................................................... iv
Publications during candidature ...................................................................................................... v
Publications included in this thesis ................................................................................................ viii
Contributions by others to the thesis............................................................................................. xiv
Statement of parts of the thesis submitted to qualify for the award of another degree ........... xiv
Acknowledgements........................................................................................................................... xv
Keywords ........................................................................................................................................ xvii
Australian and New Zealand Standard Research Classifications (ANZSRC) ......................... xvii
Fields of Research (FoR) Classification ....................................................................................... xvii
Table of contents ........................................................................................................................... xviii
List of Tables ................................................................................................................................. xxvi
List of Figures ................................................................................................................................ xxix
Abbreviations ............................................................................................................................... xxxii
Chapter 1: Introduction and literature overview ......................................................................... 1
1.1 Introduction ........................................................................................................................... 1
1.2 Applied clinical pharmacology of antibiotics ....................................................................... 1
1.2.1 Pharmacokinetic considerations ................................................................................. 1
1.2.2 Pharmacodynamic considerations .............................................................................. 2
1.2.3 Bacterial kill characteristics of different antibiotics .................................................... 2
1.3 Sepsis ..................................................................................................................................... 3
1.4 Pathophysiological changes in critically ill patients with sepsis that can affect drug
pharmacokinetics .............................................................................................................................. 4
1.4.1 Changes of volume of distribution ............................................................................. 5
1.4.1.1 Tissue perfusion and target site distribution of antibiotics......................................... 6
1.4.1.2 Protein binding and hypoalbuminaemia ..................................................................... 6
1.4.2 Changes in drug clearance.......................................................................................... 7
1.4.2.1 Increase in cardiac output and augmented renal clearance ........................................ 7
1.4.2.2 End-organ dysfunction ............................................................................................... 7
1.4.2.3 Extra-corporeal circuits .............................................................................................. 8
1.4.3 Beta-lactam antibiotics and their pharmacokinetic and pharmacodynamic properties . 8
xix
1.4.4 Pharmacokinetic and pharmacodynamic considerations for critically ill patients with
sepsis……………………………………………………………………………………………………10
1.4.5 Continuous beta-lactam infusion .............................................................................. 12
1.4.5.1 In vitro models simulating human pharmacokinetics ............................................... 12
1.4.5.2 In vivo animal studies ............................................................................................... 12
1.4.5.3 Clinical outcomes ..................................................................................................... 13
1.4.6 Extended beta-lactam infusion ................................................................................. 22
1.4.6.1 Doripenem ................................................................................................................ 23
1.4.7 Summary ................................................................................................................. 25
Aims ................................................................................................................................................... 26
Chapter 2: Population pharmacokinetics of doripenem in critically ill patients with sepsis.. 27
2.1 Synopsis............................................................................................................................... 27
2.2 Manuscript entitled “Population pharmacokinetics of doripenem in critically ill patients
with sepsis in a Malaysian intensive care unit” .............................................................................. 28
2.2.1 Abstract ................................................................................................................... 30
2.2.2 Introduction ............................................................................................................. 31
2.2.3 Materials and methods ............................................................................................. 32
2.2.3.1 Setting ....................................................................................................................... 32
2.2.3.2 Study population....................................................................................................... 32
2.2.3.3 Doripenem administration and ancillary treatments ................................................ 32
2.2.3.4 Study protocol .......................................................................................................... 33
2.2.3.5 Doripenem assay ...................................................................................................... 33
2.2.3.6 Population pharmacokinetic analysis ....................................................................... 34
2.2.3.6.1 Software .............................................................................................................. 34
2.2.3.6.2 Structural and stochastic model development .................................................... 34
2.2.3.6.3 Covariate screening and model development ..................................................... 34
2.2.3.6.4 Model evaluation and prediction ........................................................................ 35
2.2.3.6.5 Dosing simulations ............................................................................................. 35
2.2.4 Results ..................................................................................................................... 36
xx
2.2.4.1 Demographic and clinical data ................................................................................. 36
2.2.4.2 Pharmacokinetic model-building ............................................................................. 36
2.2.4.3 Dosing simulations ................................................................................................... 40
2.2.5 Discussion ............................................................................................................... 41
2.2.6 Conclusions ............................................................................................................. 44
2.2.7 Acknowledgments ................................................................................................... 45
2.3 Conclusion ........................................................................................................................... 46
Chapter 3: Continuous beta-lactam infusion in critically ill patients: a structured review of
published literatures ........................................................................................................................ 47
3.1 Synopsis............................................................................................................................... 47
3.2 Manuscript entitled “Continuous infusion vs. bolus dosing: implications for beta-lactam
antibiotics”...................................................................................................................................... 48
3.2.1 Abstract ................................................................................................................... 50
3.2.2 Introduction ............................................................................................................. 51
3.2.3 The Pharmacodynamics of Beta-lactams .................................................................. 52
3.2.4 Comparative Studies between Intermittent and Continuous Administration .............. 52
3.2.4.1 Plasma Pharmacokinetics ......................................................................................... 52
3.2.4.1.1 Critically ill ......................................................................................................... 56
3.2.4.1.2 Peri-operative non-infected patients ................................................................... 56
3.2.4.1.3 Cystic fibrosis ..................................................................................................... 56
3.2.4.1.4 Cancer patients .................................................................................................... 57
3.2.4.1.5 Paediatric population .......................................................................................... 57
3.2.4.2 Tissue pharmacokinetics .......................................................................................... 58
3.2.4.3 Clinical outcomes ..................................................................................................... 59
3.2.4.3.1 Mortality ............................................................................................................. 60
3.2.4.3.2 Clinical cure ........................................................................................................ 60
3.2.4.3.3 Severity of Illness ............................................................................................... 62
3.2.4.3.4 Fever resolution/white blood cell normalization ................................................ 62
3.2.4.3.5 Mechanical ventilation ........................................................................................ 62
3.2.4.3.6 Length of ICU/hospital stay ................................................................................ 62
xxi
3.2.4.3.7 Adverse events .................................................................................................... 63
3.2.4.4 Other considerations ................................................................................................. 63
3.2.4.4.1 Stability Issues .................................................................................................... 63
3.2.5 Conclusions ............................................................................................................. 67
3.3 Conclusion ........................................................................................................................... 68
Chapter 4: Prolonged beta-lactam infusion in critically ill patients: a post hoc analysis on a
large dataset of critically ill patients .............................................................................................. 69
4.1 Synopsis............................................................................................................................... 69
4.2 Manuscript entitled “Is prolonged infusion of piperacillin/tazobactam and meropenem in
critically ill patients associated with improved pharmacokinetic/pharmacodynamic and patient
outcomes? An observation from the Defining Antibiotic Levels in Intensive care unit patients
(DALI) cohort” ............................................................................................................................... 70
4.2.1 Abstract ................................................................................................................... 73
4.2.1.1 Objectives ................................................................................................................. 73
4.2.1.2 Methods .................................................................................................................... 73
4.2.1.3 Results ...................................................................................................................... 73
4.2.1.4 Conclusions .............................................................................................................. 73
4.2.2 Introduction ............................................................................................................. 74
4.2.3 Materials and methods ............................................................................................. 75
4.2.3.1 Study design ............................................................................................................. 75
4.2.3.2 Sample integrity and bioanalysis .............................................................................. 75
4.2.3.3 Pharmacokinetic/pharmacodynamic and clinical outcome measures ...................... 75
4.2.3.4 Statistical analysis .................................................................................................... 77
4.2.4 Results ..................................................................................................................... 77
4.2.4.1 Pharmacokinetic/pharmacodynamic and clinical outcome measures ...................... 81
4.2.4.2 Outcome measures predictors .................................................................................. 82
4.2.5 Discussion ............................................................................................................... 89
4.2.6 Conclusion ............................................................................................................... 91
4.2.7 Acknowledgements .................................................................................................. 92
4.2.7.1 Authors’ Contribution .............................................................................................. 92
xxii
4.2.7.2 Members of the DALI Study group ......................................................................... 92
4.2.7.3 Funding information ................................................................................................. 98
4.2.7.4 Transparency declarations ........................................................................................ 99
4.3 Conclusion ......................................................................................................................... 100
Chapter 5: The ideal characteristics of a clinical trial investigating continuous infusion
versus intermittent bolus dosing of beta-lactam antibiotics....................................................... 101
5.1 Synopsis............................................................................................................................. 101
5.2 Manuscript entitled “Continuous beta-lactam infusion in critically ill patients: the clinical
evidence” ...................................................................................................................................... 102
5.2.1 Abstract ................................................................................................................. 104
5.2.2 Introduction ........................................................................................................... 105
5.2.3 PK/PD considerations ............................................................................................ 109
5.2.3.1 Inconsistent PD end-points for comparison ........................................................... 109
5.2.3.2 The role of post-antibiotic effect ............................................................................ 110
5.2.3.3 Revision in antibiotic breakpoints .......................................................................... 110
5.2.3.4 The role of optimal PK/PD targets in the prevention of antibiotic resistance ........ 110
5.2.4 Controversies surrounding data interpretation ........................................................ 111
5.2.4.1 Heterogeneous patient populations ........................................................................ 115
5.2.4.2 Inclusion of patients with a low level of illness severity ....................................... 115
5.2.4.3 Inconsistent antibiotic dosing regimen ................................................................... 116
5.2.4.4 Pathogens with low MIC values ............................................................................. 116
5.2.4.5 Concomitant administration of other antibiotics .................................................... 117
5.2.4.6 Insufficient sample sizes ........................................................................................ 117
5.2.5 Other relevant concerns ......................................................................................... 118
5.2.6 Methodology concerns and the proposed characteristics of an “ideal” trial ............. 118
5.2.7 Conclusion ............................................................................................................. 122
5.3 Conclusion ......................................................................................................................... 123
xxiii
Chapter 6: Continuous beta-lactam infusion in critically ill patients with severe sepsis: A
prospective, two-centre, open-labelled, randomized controlled trial ........................................ 124
6.1 Synopsis............................................................................................................................. 124
6.2 Manuscript entitled “BLISS: Beta-Lactam Infusion in Severe Sepsis: a prospective, two-
centre, open-labelled, randomized controlled trial of continuous versus intermittent beta-lactam
infusion in critically ill patients with sepsis” ............................................................................... 125
6.2.1 Abstract ................................................................................................................. 128
6.2.1.1 Purpose ................................................................................................................... 128
6.2.1.2 Methods .................................................................................................................. 128
6.2.1.3 Results .................................................................................................................... 128
6.2.1.4 Conclusions ............................................................................................................ 128
6.2.2 Introduction ........................................................................................................... 129
6.2.3 Methods ................................................................................................................. 130
6.2.3.1 Study design ........................................................................................................... 130
6.2.3.2 Participants and randomization .............................................................................. 130
6.2.3.3 Intervention ............................................................................................................ 130
6.2.3.4 Outcomes and measurements ................................................................................. 132
6.2.3.5 Pharmacokinetic sampling and bioanalysis ............................................................ 134
6.2.3.6 Sample size calculations ......................................................................................... 135
6.2.3.7 Statistical analysis .................................................................................................. 135
6.2.4 Results ................................................................................................................... 136
6.2.4.1 Baseline demographics and clinical characteristics ............................................... 136
6.2.4.2 Outcome measures ................................................................................................. 140
6.2.4.3 Outcome measures predictors ................................................................................ 141
6.2.4.4 Pharmacokinetic/pharmacodynamic data ............................................................... 154
6.2.4.5 Adverse events ....................................................................................................... 155
6.2.5 Discussion ............................................................................................................. 156
6.2.6 Conclusion ............................................................................................................. 158
6.3 Conclusion ......................................................................................................................... 159
xxiv
Chapter 7: Optimizing antibiotic treatment in critically ill patients via
pharmacokinetic/pharmacodynamic principles .......................................................................... 160
7.1 Synopsis............................................................................................................................. 160
7.2 Manuscript entitled “Applying pharmacokinetic/pharmacodynamic principles in critically
ill patients: optimizing efficacy and reducing resistance development” ...................................... 161
7.2.1 Abstract ................................................................................................................. 163
7.2.2 Introduction ........................................................................................................... 164
7.2.3 Applied clinical pharmacology of antibiotics ......................................................... 165
7.2.3.1 Pharmacokinetic considerations ............................................................................. 166
7.2.3.2 Pharmacodynamic considerations .......................................................................... 166
7.2.4 Pharmacokinetic/pharmacodynamic considerations and the resistance descriptors.. 168
7.2.4.1 Mutant selection window ....................................................................................... 169
7.2.4.2 Mutant prevention concentration............................................................................ 170
7.2.4.3 Application of experimental mixture models ......................................................... 171
7.2.5 Specific antibiotic classes ...................................................................................... 171
7.2.5.1 Quinolones.............................................................................................................. 172
7.2.5.2 Aminoglycosides .................................................................................................... 175
7.2.5.3 Beta-lactams ........................................................................................................... 176
7.2.5.4 Carbapenems .......................................................................................................... 177
7.2.5.5 Vancomycin............................................................................................................ 179
7.2.5.6 Linezolid ................................................................................................................. 180
7.2.5.7 Daptomycin ............................................................................................................ 180
7.2.5.8 Fosfomycin ............................................................................................................. 181
7.2.5.9 Colistin ................................................................................................................... 182
7.2.6 Modifying treatment approaches to prevent emergence of resistance ...................... 183
7.2.6.1 Combination antibiotic therapy .............................................................................. 183
7.2.6.2 Duration of therapy ................................................................................................ 184
7.2.6.3 Altered dosing approaches ..................................................................................... 184
7.2.7 Conclusion ............................................................................................................. 185
7.3 Conclusion ......................................................................................................................... 187
xxv
Chapter 8: Summary of findings, general discussion, conclusion and future directions ...... 188
8.1 Summary of findings and general discussion .................................................................... 188
8.2 Future directions for research ............................................................................................ 192
8.3 Conclusion ......................................................................................................................... 193
References ....................................................................................................................................... 194
xxvi
List of Tables
Chapter 1
Table 1-1: Pharmacokinetic characteristics of hydrophilic and lipophilic antibiotics in general ward
versus ICU patients .............................................................................................................................. 5
Table 1-2: Characteristics of previously published studies of continuous versus bolus dosing of
beta-lactam antibiotics ....................................................................................................................... 16
Table 1-3: Antibiotics dosage and outcome data of previously published studies for CI versus IB
dosing of beta-lactam antibiotics ....................................................................................................... 19
Table 1-4: Possible advantages and disadvantages of employing CI versus IB dosing of beta-lactam
antibiotics ........................................................................................................................................... 23
Chapter 2
Table 2-1: Clinical and demographic details of the enrolled patients................................................ 37
Table 2-2: Typical population parameter estimates for the base and final covariate model and the
2000 bootstrap runs ............................................................................................................................ 38
Chapter 3
Table 3-1: Comparison of respective plasma pharmacokinetic between continuous and intermittent
administration of beta-lactams in critically ill or septic patients ....................................................... 54
Table 3-2: Penetration of beta-lactams into various tissues when administered as continuous or
intermittent administration ................................................................................................................. 58
Table 3-3: Clinical outcome data for patients receiving bolus or continuous infusion/extended-
dosing of beta-lactam antibiotics ....................................................................................................... 64
Chapter 4
Table 4-1: Definitions used for pharmacokinetic/pharmacodynamic end-points and clinical outcome
variables ............................................................................................................................................. 76
Table 4-2: Baseline demographics and characteristics ...................................................................... 79
xxvii
Table 4-3: Differences in patient characteristics and treatment-related variables between those who
demonstrated positive and negative clinical outcome ........................................................................ 83
Table 4-4: Factors predicting clinical cure and 30-day survival for all patients who received
antibiotics for treatment of infections ................................................................................................ 87
Chapter 5
Table 5-1: Possible advantages and disadvantages of employing continuous or intermittent
administration of beta-lactam antibiotics ......................................................................................... 108
Table 5-2: Characteristics of previously published studies of continuous versus bolus dosing of
beta-lactam antibiotics ..................................................................................................................... 112
Table 5-3: Antibiotics dosage and outcome data of previously published studies for CI versus IB
dosing of beta-lactam antibiotics ..................................................................................................... 113
Table 5-4: Description of a randomized clinical trial that should be performed to investigate CI
versus IB of beta-lactam antibiotics ................................................................................................. 119
Chapter 6
Table 6-1: Antibiotic dosing protocol according to treatment arm in the BLISS study .................. 131
Table 6-2: Definitions used for primary and secondary clinical end-points .................................... 132
Table 6-3: Baseline demographic and clinical characteristics of the intention-to-treat population . 137
Table 6-4: Microbiological characteristics of the intention-to-treat population .............................. 140
Table 6-5: Primary and secondary end-points by treatment arm in the intention-to-treat population
and the sub-groups of interest .......................................................................................................... 142
Table 6-6: Primary and secondary end-points by treatment arm in the modified intention-to-treat
population......................................................................................................................................... 145
Table 6-7: Primary and secondary end-points by treatment arm in the per-protocol population .... 147
Table 6-8: Differences in clinical characteristics and treatment-related variables between
participants who demonstrated clinical cure and clinical failure in the ITT population.................. 149
Table 6-9: Factors predicting clinical cure in the ITT population ................................................... 152
xxviii
Chapter 7
Table 7-1: Optimal pharmacokinetic/pharmacodynamic indices for antibiotic activity and the
magnitudes associated with maximal therapeutic outcomes and resistance suppression ................ 173
xxix
List of Figures
Chapter 1
Figure 1-1: A diagram outlining the relationship between pharmacokinetics (PK) and
pharmacodynamics (PD) of an antibiotic ............................................................................................. 2
Figure 1-2: Pharmacokinetic (PK) and pharmacodynamic (PD) of antibiotics on a hypothetical
concentration versus time curve ........................................................................................................... 3
Figure 1-3: The simulated concentration-time profile of cefepime when administered by IB or CI
dosing ................................................................................................................................................. 11
Figure 1-4: Description of the current limitations and methodological flaws associated with current
clinical trials ....................................................................................................................................... 14
Chapter 2
Figure 2-1: Goodness-of-fit plots associated with final population pharmacokinetic model for
doripenem........................................................................................................................................... 39
Figure 2-2: Visual predictive check plot associated with the final population pharmacokinetic model
for doripenem ..................................................................................................................................... 40
Figure 2-3: The probability of target attainment for various simulated doripenem dosing regimens to
achieve 40% fT>MIC in patients with a creatinine clearance of (a) 30 mL/min; (b) 50 mL/min; (c) 70
mL/min; (d) 100 mL/min; and (e) 150 mL/min ................................................................................. 41
Chapter 3
Figure 3-1: Comparative flucloxacillin concentration between continuous (CI) and intermittent
administration (IB) assuming similar pharmacokinetic properties in ICU patients. The same daily
dose for IB and CI was simulated from a previous population pharmacokinetic study whereby 2 g 6
hourly for IB and 8 g over 24 hours was simulated for CI ................................................................ 53
Chapter 4
Figure 4-1: Study flowchart demonstrating the number of patients who were included and excluded
in each stage of the planned analysis ................................................................................................. 78
xxx
Figure 4-2: Method of piperacillin/tazobactam and meropenem administration according to
participating countries ........................................................................................................................ 81
Figure 4-3: Clinical cure rates comparison between prolonged infusion and intermittent bolus
dosing for patients who received antibiotics for treatment of infections, stratified according to sub-
groups ................................................................................................................................................. 85
Figure 4-4: Comparison of 30-day survival between prolonged infusion and intermittent bolus
dosing for patients who received antibiotics for treatment of infections, stratified according to sub-
groups. ................................................................................................................................................ 86
Chapter 5
Figure 5-1: Study flowchart demonstrating the number of patients who were included and excluded
in each stage of the planned analysis ............................................................................................... 106
Figure 5-2: The simulated concentration-time profile of a beta-lactam when administered by
intermittent bolus dosing or continuous infusion ............................................................................. 106
Figure 5-3: Observed steady state plasma and tissue concentrations for meropenem administered to
critically ill patients with sepsis by intermittent bolus dosing and continuous infusion ................. 107
Figure 5-4: The summary of the current limitations and flaws associated with the available clinical
trial ................................................................................................................................................... 115
Chapter 6
Figure 6-1: The BLISS study CONSORT flow diagram ................................................................. 136
Figure 6-2: Free plasma antibiotic concentration by beta-lactam antibiotics and treatment groups
measured at (a) 50% of the dosing interval on Day 1 (b) 100% of the dosing interval on Day 1 (c)
50% of the dosing interval on Day 3 and (d) 100% of the dosing interval on Day 3 ...................... 154
Figure 6-3: Free plasma antibiotic concentration to minimum inhibitory concentration (MIC) ratio
by beta-lactam antibiotics and treatment groups measured at (a) 50% of the dosing interval on Day
1 (b) 100% of the dosing interval on Day 1 (c) 50% of the dosing interval on Day 3 and (d) 100% of
the dosing interval on Day 3 ............................................................................................................ 155
xxxi
Chapter 7
Figure 7-1: The graphical illustration of fundamental pharmacokinetic and pharmacodynamic
parameters of antibiotics on a hypothetical concentration-time curve ............................................ 167
Figure 7-2: Graphical illustration of the mutant selection window and mutant prevention
concentration on a hypothetical concentration-time curve .............................................................. 170
xxxii
Abbreviations
% fT>MIC The percentage of time that free (unbound) drug concentration
remains above the minimum inhibitory concentration during a
dosing interval
The influence of creatinine clearance on drug clearance
ACCP The American College of Chest Physicians
AKI Acute kidney injury
APACHE II Acute Physiology and Chronic Health Evaluation II
ARC Augmented renal clearance
AUC Area under the concentration-time curve over a dosing interval
AUC0-24 Area under the concentration-time curve over a 24-hour period
AUC0-24/MIC The ratio of the area under the concentration-time curve during a
24-hour period to minimum inhibitory concentration
AUC0-24/MPC The ratio of the area under the concentration-time curve during a
24-hour period to mutant prevention concentration
BLING Beta-Lactam Infusion Group
BLISS Beta-Lactam In Severe Sepsis
BMI Body mass index
BOV Between-occasion variability
BSV Between-subject variability
BTCCRC Burns, Trauma and Critical Care Research Centre
CAP Community-acquired pneumonia
CART Classification and Regression Tree
CFR Cumulative fraction of response
CI Continuous infusion
CL Clearance
CLCR Creatinine clearance
CLSI Clinical and Laboratory Standards Institute
Cmax Peak drug concentration over a dosing interval
Cmax/MIC The ratio of peak drug concentration to minimum inhibitory
concentration
Cmin Minimum drug concentration over a dosing interval
CMS Colistin methanesulfonate
CNS Central nervous system
xxxiii
CO Cardiac output
COPD Chronic obstructive pulmonary disease
CPB Cardiopulmonary bypass
CRP C-reactive protein
CRRT Continuous renal replacement therapy
Css Steady-state concentration
CV Coefficient of variation
CVVH Continuous venovenous haemofiltration
CWRES Conditional weighted residual
DALI Defining Antibiotic Levels in Intensive care unit patients
ECMO Extracorporeal membrane oxygenation
EDD Extended-daily dosing
EI Extended infusion
ELF Epithelial lining fluid
ESBL Extended-spectrum beta-lactamase
EUCAST European Committee on Antimicrobial Susceptibility Testing
FEV1 Forced expiratory volume in 1 second
FOCE-I First-order conditional estimation with interaction
fT>4 x MIC The time that free (unbound) drug concentration remains four times
above the minimum inhibitory concentration during a dosing
interval
fT>MIC The duration time that free (unbound) drug concentration remains
above the minimum inhibitory concentration during a dosing
interval
GFR Glomerular filtration rate
HFIM Hollow-fibre infection model
HPLC High-performance liquid chromatography
HR Hazard ratio
IAI Intra-abdominal infection
IB Intermittent bolus
ICU Intensive care unit
IPRED Individual predicted concentration
IQR Interquartile range
ISF Interstitial fluid
ITT Intention-to-treat
xxxiv
IV Intravenous
IWRES Individual weighted residual
LD Loading dose
LOS Length of stay
MDR Multi-drug resistant
MIC Minimum inhibitory concentration
MIC90 Minimum inhibitory concentration required to inhibit the growth of
90% of organisms
mITT Modified intention-to-treat
MPC Mutant prevention concentration
MRSA Methicillin-resistant Staphylococcus aureus
MSSA Methicillin-susceptible Staphylococcus aureus
MSW Mutant selection window
MV Mechanical ventilation
OFV Objective function value
OR Odds ratio
PAE Post-antibiotic effect
PD Pharmacodynamics
PD50 The dose needed to protect 50% of animals from death
PK Pharmacokinetics
PK/PD Pharmacokinetic/pharmacodynamic
PP Per-protocol
PRED Population predicted concentration
PsN Perl-Speaks-NONMEM®
PTA Probability of target attainment
Q Inter-compartmental clearance
RCT Randomized controlled trial
RRT Renal replacement therapy
RUV Residual unexplained variability
SCCM The Society of Critical Care Medicine
SIRS Systemic inflammatory response syndrome
SLED Sustained low-efficiency dialysis
SOFA Sequential Organ Failure Assessment
SSTI Skin and skin-structure infection
SW Selective window
xxxv
T Time
TDM Therapeutic drug monitoring
tMSW The time spent in the mutant selection window
UTI Urinary tract infection
V1 Central volume of distribution
V2 Peripheral volume of distribution
VAP Ventilator-associated pneumonia
Vd Volume of distribution
VISA Vancomycin-intermediately susceptible Staphylococcus aureus
VPC Visual predictive check
VRE Vancomycin-resistant enterococci
WCC White cell counts
ΔOFV The change in objective function value
θCLpop The typical value of clearance in the population
1
Chapter 1: Introduction and literature overview
1.1 Introduction
The mortality rate due to severe sepsis and septic shock in the intensive care unit (ICU) setting
remains high despite recent therapeutic advances [1]. Source control of the infection, along with
early and appropriate antibiotic administration, are the most effective strategies available to
clinicians for the management of critically ill septic patients [2-4]. However, appropriate antibiotic
administration is not straightforward as critically ill patients may develop pathophysiological
changes that can alter the antibiotic pharmacokinetics (PK). Indeed, dosing that does not account for
these alterations may lead to inadequate antibiotic exposure and therapeutic failure [5-8]. Beta-
lactam antibiotics are key in the treatment of severe infections due to their spectrum of antibiotic
activity and overall tolerability. These antibiotics display time-dependent pharmacodynamics (PD),
whereby the time which the antibiotic concentration remains above the minimum inhibitory
concentration (MIC) best characterizes bacterial killing [9-12]. Based on this property, maximal
beta-lactam activity is likely to be achieved through a continuous infusion (CI) or an extended
infusion (EI) strategy which maintains concentrations at higher concentrations throughout a dosing
interval, rather than traditional intermittent bolus (IB) dosing [13-17]. Different dosing approaches
in critically ill patients with sepsis may lead to better attainment of PK and PD targets potentially
leading to greater clinical success.
1.2 Applied clinical pharmacology of antibiotics
Pharmacology is the science of drugs or study of drug actions. The two main areas of pharmacology
are PK and PD. Knowledge on PK and PD is essential to comprehend the complex effect of
pathophysiological changes in critically ill patients and how they alter plasma and tissue antibiotic
concentrations. Furthermore, a personalized dosing regimen can be established for critically ill
patients by using pharmacokinetic/pharmacodynamic (PK/PD) principles.
1.2.1 Pharmacokinetic considerations
PK refers to the study of concentration changes of a drug over a given time period. It provides a
mathematical basis to assess the time course of drugs and their effects in the body. The important
PK parameters for antibiotics are: (a) volume of distribution (Vd); (b) clearance (CL); (c) peak drug
concentration over a dosing interval (Cmax); (d) minimum drug concentration during a dosing
2
interval (Cmin); and (e) area under the concentration-time curve over a dosing interval (AUC) or
over a 24-hour period (AUC0-24) [18].
1.2.2 Pharmacodynamic considerations
PD is the study of the relationship between measures of drug exposure and pharmacological effect.
For antibiotics, PD relates concentration to the ability of an antibiotic to kill or inhibit the growth of
a pathogen. This can be done by integrating antibiotic PK data with information on pathogen
susceptibility (e.g., MIC). PD indices include the following: (a) the duration of time (T) that the free
(unbound) drug concentration remains above the MIC during a dosing interval (fT>MIC); (b) the ratio
of peak drug concentration (Cmax) to MIC (Cmax/MIC); and (c) the ratio of the area under the
concentration-time curve during a 24-hour period (AUC0-24) to MIC (AUC0-24/MIC) [18]. Together,
PK parameters and PD indices describe the dose-concentration-effect relationship. Figure 1-1
outlines the interrelationship of PK and PD.
Figure 1-1: A diagram outlining the relationship between pharmacokinetics (PK) and
pharmacodynamics (PD) of an antibiotic
1.2.3 Bacterial kill characteristics of different antibiotics
Different classes of antibiotics have been shown to have different kill characteristics on pathogens.
These kill characteristics have been determined predominantly from in vitro studies and describe
the PK measurements that represent optimal bactericidal activity [19]. Generally, antibiotics can be
classified into three categories based on their modes of bacterial killing: (a) concentration-
dependent antibiotics (e.g., aminoglycosides); (b) time-dependent antibiotics (e.g., beta-lactams);
and (c) both i.e., concentration and time-dependent antibiotics (e.g., vancomycin and
fluoroquinolones) [12]. The fundamental concepts of antibiotic kill characteristics are further
3
illustrated in Figure 1-2. As an example, for time-dependent antibiotics such as the beta-lactams,
fT>MIC is strongly correlated with bacteriostasis and bactericidal activity [12, 20-26]. Thus, for a
time-dependent antibiotic, the longer the effective drug concentration is maintained over a dosing
period the greater drug efficacy [25, 27, 28].
Figure 1-2: Pharmacokinetic (PK) and pharmacodynamic (PD) of antibiotics on a
hypothetical concentration versus time curve
1.3 Sepsis
Severe sepsis and septic shock are the most common causes of morbidity and mortality in critically
ill patients [1, 29-35]. In a multicentre point prevalence study involving 1265 ICUs across 75
countries, 51% of the ICU patients were classified as infected on the day of study with an ICU
mortality rate of 25.3% [31]. Data from a large European ICU study has further corroborated severe
sepsis status as a major healthcare burden, whereby severe sepsis accounted for 26.7% of ICU
admissions with mortality rates for patients with severe sepsis and septic shock were 32.2% and
54.1%, respectively [33]. Based on the Malaysian Registry of Intensive Care report for year 2011,
23.2% of Malaysian ICU patients developed severe sepsis within 24 hours of ICU admission with a
mortality rate approaching 60% [36]. Despite an emerging trend for improved survival in ICU
patients [32, 37-39], the mortality rate in critically ill patients remains unacceptably high
4
worldwide, ranging from 30-50% in severe sepsis and 40-87% in patients with septic shock [37, 40-
45]. As a consequence, huge hospital resources are spent worldwide on septic patients [46, 47].
The “older” definition of sepsis [48] has been refined in 2005 by The American College of Chest
Physicians (ACCP) and the Society of Critical Care Medicine (SCCM) [49, 50] as an infection in
the presence of systemic inflammatory response syndrome (SIRS) [50]. SIRS has been described as
a constellation of physiological (e.g., temperature, heart rate, respiratory rate) and laboratory
abnormalities (e.g., white cell count [WCC]) that accompany inflammation independent of its
underlying aetiology [48]. Severe sepsis is defined as sepsis complicated by at least one organ
dysfunction or tissue hypoperfusion. Organ dysfunction can be described using definitions that were
previously developed by Marshall et al., [51] or a more recent definition used in the Sequential
Organ Failure Assessment (SOFA) score [52]. Septic shock refers to acute circulatory failure
characterized by persistent arterial hypotension unexplained by other causes. Specifically, septic
shock can be defined as sepsis induced hypotension (hypotension is defined as a systolic blood
pressure of <90 mmHg or mean arterial pressure of <70 mmHg or a systolic blood pressure
decrease >40 mmHg), which persists despite adequate volume resuscitation in the absence of other
causes for hypotension [48, 50].
1.4 Pathophysiological changes in critically ill patients with sepsis that can
affect drug pharmacokinetics
Physiological changes that can occur from either pharmacological interventions or the natural
course of sepsis may alter antibiotic PK and consequently affect antibiotic exposure in critically ill
patients. Vd and drug CL are the most important PK parameters in terms of calculating a drug
dosing requirements and both may be significantly altered in critically ill patients with severe
sepsis. Table 1-1 describes the anticipated changes in Vd and CL of various antibiotics in ICU
patients compared to the general population.
5
Table 1-1: Pharmacokinetic characteristics of hydrophilic and lipophilic antibiotics in general
ward versus ICU patients
Antibiotic PK parameters General PK Altered PK in ICU patients
Hydrophilic Vd Low Vd Vd
e.g., aminoglycosides,
beta-lactams, colistin,
glycopeptides, linezolid
CL Predominantly
renal
or depending on renal
function
Intracellular
penetration
Poor interstitial penetration
Lipophilic Vd High Vd Unchanged
e.g., fluoroquinolones,
lincosamides,
macrolides, tigecycline
CL Predominantly
hepatic
or depending on renal
function
Intracellular
penetration
Good Unchanged
Abbreviation: CL, clearance; ICU, intensive care unit; PK, pharmacokinetics; Vd, volume of
distribution.
1.4.1 Changes of volume of distribution
The Vd of a drug is defined as the apparent volume of fluid (usually expressed in L or L/kg) that
drug distributes into to give a total concentration the same as is measured in the plasma. Changes in
antibiotic Vd have been noted in critically ill patients [6, 53-57], and the contributing factors are
discussed below.
Sepsis involves release of various inflammatory mediators [49, 58-60] that eventually increases
capillary permeability [61-63]. This capillary leak syndrome causes fluid shifting from the
intravascular compartment to the interstitial space, which is commonly described as the third
spacing phenomenon. This phenomenon increases the Vd of hydrophilic antibiotics, decreasing their
plasma and tissue concentrations in critically ill patients [64]. Consequently, a higher dose of such
antibiotics is needed in order to achieve effective antibiotic exposure in critically ill patients with
severe sepsis. In contrast, fluid shifts have a minimal effect on lipophilic antibiotics as they
inherently possess a larger Vd due to their greater partitioning out of the blood stream (typically into
intracellular and adipose compartments). In addition, several medical interventions in the ICU such
as aggressive fluid resuscitation [65-68], mechanical ventilation [69-72], extracorporeal circuits
[73], the presence of postsurgical drains [74, 75] and total parenteral nutrition [76] have also been
6
reported to be associated with increased Vd and consequently decreased concentrations of
hydrophilic antibiotics.
1.4.1.1 Tissue perfusion and target site distribution of antibiotics
Effective antibiotic concentrations need to be achieved in the interstitial fluid of tissues as most
infections are thought to occur here [77]. However, critically ill patients with sepsis have shown
diminished microvascular perfusion, which results in impaired distribution of drugs especially to
sites of infection such as soft tissues [78-82]. This phenomenon can be attributed to capillary
leakage, tissue oedema and microvascular failure which are frequently seen in such patients. Using
an in vivo sampling technique known as microdialysis, the extent of antibiotic penetration into
tissues of critically ill patients has been described [72, 83-88]. Critically ill patients with septic
shock are initially managed with large boluses of intravenous (IV) fluids to increase blood pressure.
However, in the presence of increased permeability, large administration of IV fluids eventually
leads to extreme volume expansion in the interstitial space which markedly increases Vd for
hydrophilic antibiotics [56, 89]. In patients with septic shock, antibiotic concentrations in interstitial
fluid may be 5- to 10-times lower than corresponding plasma concentrations as well as those
concentrations observed in healthy volunteers [90]. However, in patients with sepsis but without
shock, there seems to be a less significant effect on tissue distribution and penetration of antibiotics
[85, 91]. The difference in these findings may be attributed to the level of sickness severity (sepsis
versus septic shock) whereby septic shock causes greater impairment in microvascular perfusion
that leads to lower antibiotic penetration than patients with sepsis.
1.4.1.2 Protein binding and hypoalbuminaemia
Hypoalbuminaemia is a common condition in the ICU with reported incidences as high as 40-50%
[92, 93]. In critically ill patients, hypoalbuminaemia is usually caused by the increase in capillary
permeability [94], downregulation of its hepatic synthesis [95] and malnutrition [96]. What follows
is an increase in the free concentration of drugs that are usually bound to this negative acute phase-
protein. The unbound concentration of such antibiotics is not only available for elimination, but also
for distribution [97-106]. For moderate-to-highly-protein bound antibiotics, this phenomenon has
been associated with a 90% increase in Vd [106, 107]. However, tissue concentrations remain low
despite increased drug distribution, due to significant fluid shifts during the acute phase response
and the large requirements for IV fluids in critically ill patients [97, 100, 102, 105, 108].
7
1.4.2 Changes in drug clearance
CL can be defined as the volume of blood (usually expressed in L/hr or L/hr/kg) cleared of drug per
unit time. CL measures the irreversible elimination of a drug from the body by either excretion
and/or metabolism. Changes in drug CL have been noted in critically ill patients [109, 110] with
contributing factors discussed below.
1.4.2.1 Increase in cardiac output and augmented renal clearance
Critically ill patients with severe sepsis frequently develop SIRS. A major component of this
inflammatory response is a hyperdynamic cardiovascular state, which is characterized by an
increase in cardiac output (CO) and enhanced blood flow to major organs [111-113]. One of the
major organs affected are the kidneys whereby the increase in renal blood flow associated with
increases in CO leads to increases glomerular filtration rates (GFR) [109]. Furthermore, therapeutic
interventions used to reverse hypotension in critically ill patients usually include large boluses of IV
fluid and administration of vasopressor infusions, which are also associated with an early increase
in CO and GFR [60, 111, 112, 114, 115]. Consequently, all of these factors lead to increased renal
CL of some drugs, a phenomenon referred to as augmented renal clearance (ARC, defined as a
creatinine clearance [CLCR] >130 mL/min). As hydrophilic antibiotics are predominantly cleared by
the kidney, ARC in critically ill patients usually causes lower plasma concentrations [116-124].
Identifying patients with ARC is not easy as critically ill patients may have elevated renal function
despite normal serum creatinine concentrations [125-128]. Thus, antibiotic dosing in this unique
patient population is usually flawed as most clinicians fail to address this phenomenon [129].
1.4.2.2 End-organ dysfunction
As disease progresses in a critically ill patient, myocardial depression may occur leading to
decreased organ perfusion and microcirculatory failure eventually resulting in end-organ damage or
in extreme cases, multiple organ dysfunction syndrome [60, 130, 131]. This syndrome often
includes renal and/or hepatic dysfunction that consequently results in a decrease in antibiotic CL.
The resulting accumulation of drugs and their metabolites in plasma increases the likelihood of
toxicity [132]. It is imperative to note that certain antibiotics can be cleared by other organs when
the primary eliminating organ (usually the kidneys) is impaired. By way of example, some
antibiotics such as ticarcillin and piperacillin demonstrate increased biliary CL that causes little
change in their plasma concentration despite mild to moderate renal dysfunction [133, 134].
8
1.4.2.3 Extra-corporeal circuits
Sepsis is the most common cause of acute kidney injury (AKI) in critically ill patients and the
associated mortality rates are higher in septic AKI population compared to those with non-septic
AKI [135-137]. The PK of antibiotics in this population are highly variable as parameters may be
altered by both AKI and critical illness. In addition, patients with AKI may be receiving
extracorporeal therapies including continuous renal replacement therapy (CRRT) or sustained low-
efficiency dialysis (SLED) to remove fluid and wastes from the body, and extracorporeal membrane
oxygenation (ECMO) to support impaired cardiac and/or pulmonary systems to maintain
appropriate blood gas concentrations. These interventions may influence antibiotic dosing
requirements as critically ill patients with CRRT and SLED were reported to have variable
antibiotic CL [138-142]. There is limited data on the influence of ECMO [141, 143-146].
1.4.3 Beta-lactam antibiotics and their pharmacokinetic and pharmacodynamic
properties
The beta-lactam antibiotics are made up of penicillins, cephalosporins, carbapenems and
monobactams. This group of antibiotics are generally hydrophilic in nature, demonstrate low Vd
(0.1-0.6 L/kg), and are predominantly cleared by the kidneys [8]. In relation to protein binding
properties, most beta-lactams have a moderate (30-70%) to low (<30%) degree of protein binding.
However, ertapenem, cefazolin, ceftriaxone and flucloxacillin demonstrate high protein-binding
(>90%) when compared to the other beta-lactams members, highlighting that PK variability may
exist within the group.
The fT>MIC is regarded as the optimal PD index for beta-lactams and as such, maintaining effective
drug concentration above the MIC should be the priority when this antibiotic class is used [9, 11,
12, 24]. Specifically, the percentage (%) of fT>MIC (% fT>MIC) needed for bacteriostasis is 35-40%,
30%, 20% for cephalosporins, penicillins and carbapenems, respectively and for bactericidal is 60-
70%, 50%, 40% for cephalosporins, penicillins and carbapenems, respectively [10-12, 24].
However, emerging clinical data from critically ill patients suggests that these patients may benefit
from higher and longer antibiotic exposures than those described in in vitro and in vivo studies [22,
23, 25-28, 147]. In a study specifically investigating critically ill patients with sepsis, McKinnon et
al., found a % fT>MIC of 100% was associated with higher rates of bacteriological eradication and
clinical cure than lesser % fT>MIC values [28]. Thus, it has been suggested that maintaining
concentrations above the MIC for 90-100% of the dosing interval is an appropriate PD target for
9
critically ill patients and may prevent antibiotic resistance [5, 148, 149]. It has also been
demonstrated that maximal bactericidal activity occurs when drug concentrations are maintained at
four- to five-times the MIC, with higher concentrations providing little added benefit [23, 25, 26,
147, 150-152]. Thus, it has been suggested that beta-lactam concentrations should be maintained at
least four- to five-times the MIC for extended periods during each dosing interval [5, 7, 153].
Another consideration for optimizing antibiotic exposure is the post-antibiotic effect (PAE), i.e., the
suppression of bacterial growth even with antibiotic concentrations below the MIC [154-158]. The
beta-lactams except for the carbapenems, produce minimal or no PAE against Gram-negative
pathogens. Carbapenems have been found to have a significant PAE against Gram-negative bacilli,
including Pseudomonas aeruginosa strains [155, 157, 158]. This PAE property of carbapenems
may explain their faster bacterial killing rate and shorter % fT>MIC for optimal bactericidal activity
[158-162].
Maintaining effective beta-lactams exposure for extended periods or increasing % fT>MIC would be
especially appropriate in immunocompromised patients including critically ill patients [7, 27, 163].
Furthermore, achieving an optimal PD index may increase the likelihood of therapeutic success in
these patients [20-23, 26, 27, 147]. Traditional IB dosing produces antibiotic concentrations below
the MIC for much of the dosing interval [67, 85, 86, 106, 151, 164-175]. This has prompted
clinicians to consider several dose optimization strategies that maximize the value of % fT>MIC.
Research has shown that improved antibiotic exposure can be obtained via three general
approaches: (1) increasing the antibiotic dose; (2) increasing the frequency of antibiotic dosing or;
(3) by utilizing EI or CI [67, 85, 86, 106, 151, 164-175]. However, increasing the antibiotic dose
has been shown to be less effective to adequately maintain effective drug concentration during a
dosing period. Increasing the antibiotic dose only raises the % fT>MIC for one half-life, which is
usually short (i.e., 1 or 2 hours) for most beta-lactams. Although study findings have been
inconclusive, increasing the antibiotic dose could theoretically lead to toxicity issues, which has
indeed been described in a recent meta-analysis [176] and several case reports [177-180]. Hence, EI
and CI of beta-lactam antibiotics have been proposed as a means of achieving optimal PK/PD
targets in critically ill patients without increasing a patient’s total daily dose [85]. These new
administration approaches may be especially important in patients who develop ARC and/or have
increased Vd which are common in critical illness [6, 7]. Specific PK changes associated with beta-
lactam use in critically ill patients are discussed below.
10
1.4.4 Pharmacokinetic and pharmacodynamic considerations for critically ill patients
with sepsis
It is being increasingly shown that heterogeneity in beta-lactam PK is significant among critically ill
patients and this phenomenon may affect treatment outcomes [6, 7]. Large Vd and CL differences
are common [56, 181]. For example, mean Vd for meropenem in severe sepsis can range from 0.3-
0.5 L/kg (healthy volunteers Vd 0.2 L/kg) [86, 182-195]. The increased Vd in critical illness can
result in sub-therapeutic antibiotic concentrations particularly in the early phase of the disease and
thus, should prompt clinicians to use higher loading doses to achieve optimal concentrations rapidly
[57, 196-199].
Apart from antibiotic Vd, high and variable beta-lactam CL is also frequently noted in patients with
severe sepsis [181, 200]. For beta-lactams, CL is frequently correlated with CLCR, which may
increase in critical illness [69, 117, 118, 120, 121, 175, 201-206]. A review by Goncalves-Pereira
and Povoa reported high CL with variable antibiotic trough concentrations in most clinical studies
investigating beta-lactam PK in ICU patients [56]. Chapuis et al., found 40-fold variations in
cefepime trough concentrations in his study and interestingly, 50% of the patients had antibiotic
concentrations lower than the target concentration (i.e., 4 mg/L) when a standard cefepime dosing
regimen was used [198]. The low antibiotic concentrations commonly observed are likely to be
caused by the presence of ARC [117, 121, 129]. To account for this PK change, altered dosing
approaches for beta-lactams such as the use of higher doses or increased frequency is necessary to
ensure adequate fT>MIC is achieved [207]. However, drug CL may increase or decrease based on
patient organ function and reduced beta-lactam CL can occur with renal and/or hepatic dysfunction.
In this situation, dose reduction may be indicated to prevent toxicity from elevated drug
concentrations.
Reduction in tissue penetration of beta-lactams has been described in critically ill patients and is
likely to be caused by microcirculatory failure [66, 72, 80, 83-88, 90, 91, 189, 208]. Emerging
PK/PD data from critically ill patients suggests better antibiotic tissue penetration and optimal PD
target attainment can be achieved via CI of beta-lactam antibiotics [79, 81, 82, 85, 86, 167, 209-
212].
Numerous PK/PD studies have suggested potential flaws in the current mode of beta-lactam
administration (i.e., IB administration) in terms of achieving optimal PK/PD targets in patients with
severe sepsis. Generally, IB administration produces high unnecessary peaks, which confer no PD
11
advantage for this antibiotic class and results in low trough concentrations (Figure 1-3) [7]. Lipman
et al., performed a prospective PK/PD clinical study to describe the PK properties and PD
characteristics associated with twice daily dosing of cefpirome in patients with severe sepsis [67].
Using 60% fT>MIC as the PD target, the authors reported that only 60% and 10% of the patients met
the PD target for MIC of 4 and 16 mg/L, respectively. In addition, the authors also concluded that
the standard dosing regimen produces low cefpirome trough concentrations and may not be
sufficient to treat severe infections in critically ill patients. Apart from this study, numerous other
PK/PD modelling and dosing simulation studies concluded that an improved beta-lactam PK/PD
profile is achieved with more frequent dosing or via EI or CI [53, 67, 79, 82, 85, 86, 106, 167-171,
173-175, 184, 187, 190, 204, 205, 213, 214]. All present in vitro and in vivo animal data also
support the use of CI compared to IB dosing in patients with altered PK [15]. Therefore, CI and EI
dosing of beta-lactam antibiotics may be meritorious and may maximize the likelihood of
therapeutic success.
Figure 1-3: The simulated concentration-time profile of cefepime when administered by IB or
CI dosing
Abbreviation: CI, continuous infusion dosing; IB, intermittent bolus dosing; MIC, minimum
inhibitory concentration.
12
1.4.5 Continuous beta-lactam infusion
CI of beta-lactam antibiotics is likely to offer the greatest advantage over IB administration when
less susceptible pathogens (e.g., P. aeruginosa) are present [85, 86, 169, 215, 216]. When
susceptible pathogens are involved, because of a lower MIC, the mode of administration (i.e., CI or
IB) is likely to be less important. Therefore, CI of beta-lactam antibiotics is unlikely to be
advantageous for all patients but may be particularly important in specific patient cohorts such as
critically ill patients with high level of sickness severity, who are also more likely to have less-
susceptible pathogens [217].
1.4.5.1 In vitro models simulating human pharmacokinetics
Although results from several animal studies clearly show that CI of beta-lactam antibiotics is more
efficacious than IB administration, the half-life of these drugs in animals (i.e., rodents) is much
shorter than in humans and thus, extrapolating the results to patients may not be completely
representative [15]. In vitro models that mimic human PK may provide better information with
regards to antibiotic exposure and its effect in humans [218].
In one of their earlier in vitro PK models, Mouton and den Hollander suggested that continuous
ceftazidime administration was more efficacious against P. aeruginosa compared to IB dosing
[152]. After the fourth dose, a marked difference in bacterial counts was observed between the two
dosing approaches (CI; 2.2 log10 versus IB; 2.8 log10). The authors added that maximal
bactericidal activity may be achieved with sustained antibiotic concentrations at four- to five-times
the MIC, with higher concentrations providing little further benefit. Other investigators have
confirmed these results in their studies [219-225].
1.4.5.2 In vivo animal studies
The effectiveness of CI versus IB administration of beta-lactam antibiotics has also been examined
in in vivo animal studies [226-237]. In one of their leading reviews, Craig and Ebert concluded that
based on numerous in vitro and in vivo animal studies, CI of beta-lactam antibiotics demonstrated
many potential advantages, particularly in Gram-negative infections and in immunocompromised
hosts [17]. Roosendaal et al., found similar results when the efficacy of CI of ceftazidime was
studied in a cohort of neutropenic rats [231]. In this study, the daily dose needed to protect 50% of
the animals from death (PD50) was 16-times lower with CI (1.52 mg/kg per day versus 24.37 mg/kg
per day; p <0.001). However, when the authors studied non-neutropenic rats, the differences
13
between the two dosing methods almost completely disappeared. This interesting finding suggests
that CI administration may be more beneficial in immunocompromised hosts. Similar findings have
been reported in several other studies [17, 233, 235]. Importantly, some in vivo models have shown
more rapid bactericidal activity with IB [232, 234]. However, the administration of a loading dose
prior to CI will enable faster achievement of effective concentration for CI [238].
1.4.5.3 Clinical outcomes
Despite strong in vitro and in vivo PK/PD data supporting the administration of beta-lactams by CI,
there is currently no “convincing” data on patient outcomes that differentiate the two dosing
methods. This may be attributed to several methodological flaws in studies that may mask the
benefits of CI previously observed in pre-clinical studies [13, 14, 217, 239, 240]. Findings from
clinical trials suggest that CI of beta-lactam antibiotics may have variable efficacy in different
patient groups [166, 241-243]. It has been suggested that patients who are most likely to benefit
from CI are critically ill patients with a high level of illness severity [166, 242, 243], but with
conserved renal function [241, 244, 245].
Numerous clinical comparative studies have been conducted with beta-lactams testing various
dosing strategies in various patient populations including critically ill patients [85, 86, 151, 166,
169, 171, 172, 241-243, 246-252], patients receiving extracorporeal renal circuit [244, 245, 253],
trauma patients [254], patients with malignant diseases [255], patients with intra-abdominal
infections [256], patients with chronic obstructive pulmonary disease (COPD) [257, 258] and non-
specific hospitalized patients [173, 259-262] (Table 1-2). These studies have not shown whether
alternative dosing approaches (i.e., CI and EI) are advantageous nor which patient groups may
benefit. Most of these trials were conducted in North America and Europe between 1979 and 2015,
with all but five studies published after 2010 [166, 241, 242, 246, 259]. A number of articles have
also discussed the potential advantages and disadvantages of CI [13-17, 263-265]. A recent
systematic review of the published literature by Abdul-Aziz et al., [13] found no statistically
significant differences in critically ill patients with regards to mortality rate [151, 172, 243, 248],
clinical cure [172, 243, 266], time to normalization of leukocytosis or pyrexia [248, 254],
mechanical ventilation [172, 243, 254, 266], hospital or ICU length of stay [172, 243, 254, 266] and
adverse events [266] between CI and IB dosing. In addition, three meta-analyses have been
published to determine if any clinical benefits of CI beta-lactams can be found from the combined
clinical data of the present studies [217, 240, 267]. Again, the analyses have not reported any
significant difference between CI and IB dosing with regards to clinical cure and survival.
14
However, wide confidence intervals can be observed in the meta-analyses that suggest a clinically
relevant difference between the two dosing approaches may still exist if more stringent
methodology was used in the studies [217]. Nevertheless, Kasiakou et al., suggested that fewer
daily CI doses are needed to produce similar outcomes as IB dosing [267]. Despite these findings,
there are currently four recent meta-analyses which reported significant patient benefits with altered
dosing approaches [239, 268-271]. However, the recent findings should be interpreted with caution
as the meta-analyses have included a significant number of retrospective and non-randomized
studies in their pooled analysis. A large-scale prospective clinical trial with a robust design is
required to answer the controversy surrounding the effectiveness of CI versus IB dosing in critically
ill patients. Future trials need to address the methodological flaws associated with current studies.
These methodological flaws have been described in detail by Abdul-Aziz et al., in a recent review
article [13, 14]. Figure 1-4 summarizes the current limitations and flaws associated with the
available clinical trials.
Figure 1-4: Description of the current limitations and methodological flaws associated with
current clinical trials
15
It is also imperative to highlight the clinical findings of three recent randomized controlled trials
(RCT) which demonstrated some clinical outcome advantages favouring CI administration of beta-
lactam antibiotics when only critically ill patients were recruited [166, 242, 243]. In a prospective,
open-labelled RCT which recruited Australian ICU patients (n = 57), Roberts et al., [243]
demonstrated higher clinical cure rates favouring CI administration as opposed to IB dosing of
ceftriaxone (52% versus 20%; p = 0.04). In a prospective, multicentre, double-blind, RCT (Beta-
Lactam Infusion Group [BLING] I; n = 60), Dulhunty et al., [166] showed that participants in the
CI treatment arm demonstrated higher clinical cure rates (77% versus 50%; p = 0.032) compared to
the IB arm. In a single-centre RCT which recruited 240 critically ill Czech participants, Chytra et
al., [242] reported higher microbiological cure rates in the CI treatment arm as opposed to the IB
arm (91% versus 78%; p = 0.020). However, none of the studies demonstrated significant patient
survival advantages.
It follows that, CI administration of beta-lactam antibiotics may not result in better outcomes for all
critically ill patients. This was recently highlighted in a multicentre, double-blind, RCT (BLING II;
n = 420) [241]. Despite recruiting only patients with severe sepsis, Dulhunty et al., [241] found no
significant difference between CI and IB participants, in all five clinical end-points evaluated. In
this study, Dulhunty et al., included patients receiving renal replacement therapy (RRT) (~25% of
participants) and this inclusion criterion may have reduced PK/PD exposure differences between CI
and IB dosing because patients with reduced drug clearances, as seen during RRT, are less likely to
manifest sub-therapeutic antibiotic exposures [211, 244, 245, 253]. Patients receiving RRT are
therefore less likely to benefit from altered dosing approaches such as CI administration. Based on
these inconsistent findings and other relevant retrospective clinical data [272-276], we await the
outcome of future clinical trials that use a more rigorous and stringent methodology to demonstrate
the clinical outcome differences between CI and IB, if they do exist.
16
Table 1-2: Characteristics of previously published studies of continuous versus bolus dosing of beta-lactam antibiotics
Study Setting
(Country)
Antibiotic Critically ill Population Sample
size
Agea Allocation
sequence
generator
Allocation
concealment
Masking Concomitant
antibiotic CI IB
Angus et al.,
[151]
Not specified
(Thailand)
Ceftazidime Yes Septicaemic
melioidosis
21 48
(29-58)
43
(27-73)
Not specified Not specified Not specified Various
Bodey et al.,
[255]
Non-ICU
(USA)
Cefamandole No Malignant diseases
with neutropenia
204 Not specified Adequate Adequate Not specified Carbenicillin
Buck et al.,
[173]
Non-ICU
(Germany)
Piperacillin/tazobactam No Hospitalized
infections
24 60-88b 32-76b Not specified Adequate No Nil stated
Chytra et al.,
[242]
ICU
(Czech)
Meropenem Yes Critically ill patients
with severe sepsis
240 45±18 47±16 Yes Adequate No Various
Cousson et al.,
[249]
ICU
(France)
Ceftazidime Yes Critically ill patients
with nosocomial
pneumonia
16 61 (21-81) Yes Not specified Not specified Not specified
De Jongh et al.,
[247]
ICU
(Belgium)
Temocillin Yes Critically ill patients
with nosocomial
infections
17 58±8 56±9 Not specified Not specified No Various
Dulhunty et al.,
[241]
ICU
(Australia, New
Zealand & Hong
Kong)
Meropenem,
piperacillin/tazobactam,
ticarcillin/clavulanate
Yes Critically ill patients
with severe sepsis
432 64 (54-72) 65 (53-72) Yes Yes Yes Various
Dulhunty et al.,
[166]
ICU
(Australia &
Hong Kong)
Meropenem,
piperacillin/tazobactam,
ticarcillin/clavulanate
Yes Critically ill patients
with severe sepsis
60 54±19 60±19 Adequate Adequate Yes Various
Georges et al.,
[172]
ICU
(France)
Cefepime Yes Critically ill with
Gram-negative
infections
50 50±17 46±24 Not specified Not specified No Amikacin
Hanes et al.,
[254]
ICU
(USA)
Ceftazidime Yes Critically ill trauma 32 33.5±12.5 36.1±12.8 Not specified Not specified No Nil stated
Jamal et al.,
[244]
ICU
(Malaysia)
Meropenem Yes Critically ill patients
with severe
sepsis/septic shock
receiving CVVH
16 48 (32-63) 45 (29-61) Not specified Yes No Nil stated
Jamal et al.,
[245]
ICU
(Malaysia)
Piperacillin/tazobactam Yes Critically ill patients
with severe
sepsis/septic shock
receiving CVVH
16 44 (34-70) 63 (46-71) Yes Yes No Nil stated
Lagast et al.,
[262]
Not specified
(Belgium)
Cefoperazone No Gram-negative
septicaemia
45 37-77b Not specified Not specified No Nil stated
17
Laterre et al.,
[259]
ICU
(Belgium)
Temocillin Yes Critically ill patients
with intra-abdominal
and LRTI
32 68±11 65±15 Not specified Not specified No Various
Lau et al.,
[256]
ICU
(USA)
Piperacillin/tazobactam No Complicated intra-
abdominal infections
262 50.4±16.6 49.3±17.8 Not specified Not specified No Nil stated
Lipman et al.,
[250]
ICU
(Hong Kong)
Ceftazidime Yes Critically ill patients 18 64±9 53±14 Yes Not specified Not specified Nil stated
Lubasch et al.,
[258]
Not specified
(Germany)
Ceftazidime No Hospitalized patients
with COPD
exacerbation
81 65.3±10.1 Not specified Not specified No Nil stated
Nicolau et al.,
[251]
ICU
(USA)
Ceftazidime Yes Critically ill patients 34 43±15 51±21 Not specified Not specified Not specified Tobramycin
Nicolau et al.,
[252]
ICU
(USA)
Ceftazidime Yes Critically ill patients
with nosocomial
pneumonia
24 37±13 45±19 Not specified Not specified Not specified Tobramycin
Nicolau et al.,
[266]
ICU
(USA)
Ceftazidime Yes Critically ill patients
with sepsis
41 46±16 56±20 Adequate Not specified No Tobramycin
Okimoto et al.,
[260]
Not specified
(Japan)
Meropenem No Elderly patients with
CAP
50 80 Not specified Not specified Not specified Nil stated
Pedeboscq et al.,
[261]
ICU
(France)
Piperacillin/tazobactam Yes Severe sepsis 7 58±12 Not specified Not specified No Ofloxacin
Rafati et al.,
[248]
ICU
(Iran)
Piperacillin Yes Critically ill patients
with sepsis
40 50.1±22.2 48.0±20.7 Not specified Not specified No Amikacin
Roberts et al.,
[169]
ICU
(Australia)
Piperacillin/tazobactam Yes Critically ill patients
with sepsis
16 30 (23-40) 41 (22-65) Yes Yes No Nil stated
Roberts et al.,
[85]
ICU
(Australia)
Piperacillin/tazobactam Yes Critically ill patients
with sepsis
13 25 (19-35) 42 (23-65) Not specified Yes No Nil stated
Roberts et al.,
[86]
ICU
(Australia)
Meropenem Yes Critically ill patients
with sepsis
10 57 (54-63) 55 (48-61) Yes Yes No Nil stated
Roberts et al.,
[243]
ICU
(Australia)
Ceftriaxone Yes Critically ill patients
with sepsis
57 43±19 52±16 Adequate Adequate Adequatec Multiple
depending on
indication
Sakka et al.,
[171]
ICU (Germany) Imipenem/cilastatin Yes Critically ill patients
with sepsis
20 62±16 59±16 Not specified Adequate No Nil stated
Tamer et al.,
[246]
ICU
(Egypt)
Meropenem Yes Critically ill patients
with severe sepsis
100 Not specified Not specified Not specified Not specified Nil stated
Van Zanten et
al.,
[257]
Not specified
(Netherlands)
Cefotaxime No Hospitalized patients
with COPD
exacerbation
93 65.3±8.4 68.6±5.3 Not specified Not specified No Nil stated
Abbreviation: CAP, community-acquired pneumonia; CI, continuous infusion; COPD, chronic obstructive pulmonary disease; CVVH, continuous venovenous haemofiltration; IB, intermittent bolus; ICU, intensive care unit.
aValues are reported according to published results as mean (±SD) or median (interquartile range).
18
bValues are reported as range. cOnly outcome assessment was blinded.
19
Table 1-3: Antibiotics dosage and outcome data of previously published studies for CI versus IB dosing of beta-lactam antibiotics
Study Types of infection Number of patients
(APACHE II scorea)
Antibiotic dosage regimen Concurrent
PK/PD analysis
Clinical outcome
measures
CI IB p-valueb
CI IB CI IB
Angus et al.,
[151]
Septicaemic melioidosis 10 (15) 11 (21) 12 mg/kg LD, then 4
mg/kg every 1 hr
40 mg/kg every 8 hrs Yes Mortality 20% 36.4% 0.89
Bodey et al.,
[255]
Pneumoniae, UTI &
neutropenic fever
167 (ND) 162 (ND) 3 g LD, then 12 g/24
hrs
3 g every 6 hrs No Clinical cure 64% 57% ND
Buck et al.,
[173]
Pneumoniae, IAI & fever
of unknown origin
12 (ND) 12 (ND) 2 g LD, then 8 g/24 hrs 4 g every 8 hrs Yes Clinical response 67% 67% ND
Chytra et al.,
[242]
Pneumoniae, IAI, UTI,
CNS infection, SSTI &
blood stream infection
120 (21) 120 (22) 2 g LD, then 4 g/24 hrs 2 g every 8 hrs No Clinical cure 83% 75% 0.18
Bacteriological cure 91% 78% 0.02
ICU mortality 12% 14% 0.7
ICU LOS 10 days 12 days 0.04
De Jongh et al.
[247]
Pneumoniae & UTI 7 (12) 10 (13) 2 g LD, then 4g/24 hrs 2 g every 12 hrs Yes Clinical cure 100% 86% ND
Survival at day 28 100% 86% ND
Dulhunty et al.,
[241]
Pneumoniae, IAI, UTI,
CNS infection, SSTI &
blood stream infection
212 (21) 220 (20) Three different beta-lactams standard ICU daily
doses
No Clinical cure 52% 50% 0.56
Survival at day 90 74% 73% 0.67
Alive ICU-free days 18 20 0.38
Organ failure-free days 6 6 0.27
Duration of bacteraemia 0 0 0.24
Dulhunty et al.,
[166]
Pneumoniae, IAI, UTI,
CNS infection, SSTI &
blood stream infection
30 (21) 30 (23) Three different beta-lactams standard ICU daily
doses
Yes Clinical cure 70% 43% 0.37
ICU mortality 93% 87% 0.67
Days to clinical resolution 11 17 0.14
ICU LOS 8 days 9 days 0.5
Georges et al.,
[172]
Pneumoniae & blood
stream infection
24 (45)c 23 (44)c 2 g/12 hrs twice daily 2 g every 12 hrs No Clinical cure 85% 67% ND
Mortality 12% 13% ND
Duration of MV 24 days 25 days ND
ICU LOS 34 days 40 days ND
Hanes et al.,
[254]
Pneumoniae 17 (13) 14 (11) 2 g LD, then 60 mg/kg
every 24 hrs
2 g every 8 hrs Yes Duration of leukocytosis 8 days 11 days 0.35
Duration of pyrexia 8 days 4 days 0.06
Duration of MV 23 days 12 days 0.16
ICU LOS 27 days 16 days 0.11
Hospital LOS 41 days 29 days 0.37
Jamal et al.,
[244]
Pneumoniae, IAI, UTI,
CNS infection, SSTI &
blood stream infection
with CVVH
8 8 1 g LD, then 125 mg/hr
every 24 hrs
2 g LD, then 1 g every
8 hrs
Yes Adverse events 0% 0% ND
20
Jamal et al.,
[245]
Pneumoniae, IAI, UTI,
CNS infection, SSTI &
blood stream infection
with CVVH
8 (33) 8 (34) 2.25 g LD, then 37.5
mg/hr every 24 hrs
4.5 g LD, then 2.25 g
every 6 hrs
Yes Adverse events 0% 0% ND
Lagast et al.,
[262]
Blood stream infection 20 (ND) 25 (ND) Day 1: 1 g LD, then 3
g/24 hrs
Day 2 +: 4 g/24 hrs
2 g every 12 hrs No Clinical cure 25% 16% ND
ICU mortality 70% 80% ND
Laterre et al.,
[259]
Pneumoniae, IAI, UTI,
SSTI & blood stream
infection
14 (17) 14 (16) 2 g LD, then 6 g/24 hrs 2 g every 8 hrs Yes Clinical cure 93% 79% NS
ICU mortality 14% 36% NS
Treatment duration 7 days 6 days NS
Lau et al.,
[256]
IAI 81 (8) 86 (8) 2 g LD, then 12 g /24
hrsg
3 g every 6 hrsg No Clinical cure 86% 88% 0.817
Bacteriological cure 77% 88% 0.628
Lipman et al.,
[250]
Pneumoniae, IAI, UTI,
CNS infection, SSTI &
blood stream infection
9 (21) 9 (16) 12 mg/kg LD, then 2 g
over 478 mins,
followed by 2 g every 8
hrs
12 mg/kg LD, then 2 g
over 28 mins, followed
by 2 g every 8 hrs
Yes Adverse events 0% 0% ND
Lubasch et al.,
[258]
Pneumoniae 41 (ND) 40 (ND) 2 g LD, then 2 g/7 hrs
twice daily
2 g every 8 hrs Yes Clinical cure 90% 90% ND
Bacteriological cure 90% 88% ND
Nicolau et al.,
[251]
Pneumoniae 17 (14) 17 (15) 1 g LD, then 3 g/24 hrs 2 g every 8 hrs Yes Adverse events 0% 0% ND
Nicolau et al.,
[252]
Pneumoniae 11 (14) 13 (15) 1 g LD, then 3 g/24 hrs 2 g every 8 hrs Yes Adverse events 0% 0% ND
Nicolau et al.,
[266]
Pneumoniae 17 (14) 18 (16) 1 g LD, then 3 g/24 hrsh 2 g every 8 hrsh No Clinical cure 41% 33% 0.592
Duration of MV 8 days 8 days 0.97
Days to defervescence 3 days 5 days 0.015
Days to WCC
normalization
7 days 6 days 0.259
LOS ICU 9 days 9 days 0.691
Pedeboscq et al.,
[261]
IAI 3 (ND) 4 (ND) 12 g/24 hrs 4 g every 8 hrs Yes Mortality 0% 0% ND
Rafati et al.,
[248]
Pneumoniae, IAI, UTI,
CNS infection, SSTI &
blood stream infection
20 (16) 20 (14) 2 g LD, then 8 g/24 hrs 3 g every 6 hrs Yes Mortality 30% 25% 0.72
Decrease in illness
severity
CI>ITd
Duration of pyrexia 2 days 1 day 0.08
WCC normalization 75% 83% ND
Roberts et al.,
[169]
Pneumoniae, IAI, UTI,
CNS infection, SSTI &
blood stream infection
8 (20) 8 (24) Day 1: 4.5 g LD, then
8g/24 hrs
Day 2 +: 13.5 g/24 hrs
4.5 g every 6 hrs or 8
hrs
Yes Survival 100% 100% 1.00
21
Roberts et al.,
[85]
Pneumoniae, IAI, UTI,
CNS infection, SSTI &
blood stream infection
6 (18) 7 (24) Day 1: 4.5 g LD, then
8g/24 hrs
Day 2 +: 13.5 g/24 hrs
4.5 g every 6 hrs or 8
hrs
Yes Clinical cure 100% 100% ND
Roberts et al.,
[86]
Pneumoniae, IAI, UTI,
CNS infection, SSTI &
blood stream infection
5 (ND) 5 (ND) 0.5 g LD, then 3 g/24
hrs
1.5 g LD, then 1 g
every 8 hrs
Yes Survival 60% 100% 0.06
Roberts et al.,
[243]
Pneumoniae, IAI, UTI,
CNS infection, SSTI &
blood stream infection
29 (19) 28 (16) 0.5 g LD, then 2 g/24
hrs
Day 1: 2.5 g/24 hrs
Day 2: 2 g/24 hrs
No Clinical curee 52% 20% 0.04
Mortality 10% 0% 0.25
Duration of MV 4 days 3 days 0.33
ICU LOS 11 days 6 days 0.29
Hospital LOS 42 days 24 days 0.34
Sakka et al.,
[171]
Pneumoniae 10 (26) 10 (28) 1 g LD, then 2 g /24 hrs 1 g every 8 hrs Yes Mortality 10% 20% ND
Tamer et al.,
[246]
Pneumoniae, IAI, UTI,
CNS infection, SSTI &
blood stream infection
50 (ND) 50 (ND) 2 g LD, then 4 g/24 hrs 2 g every 8 hrs No Clinical cure 74% 62% 0.198
Mortality at day 28 26% 38% 0.198
SOFA at the EOT 3 5 <0.001
WCC at day 5 of therapy 14 15 0.042
CRP at day 7 of therapy 109 119 0.035
LOS ICU 10 days 12 days <0.001
Van Zanten et al.,
[257]
COPD exacerbation 40 (ND) 43 (ND) 1 g LD, then 2 g/24 hrs 1 g every 8 hrs Yes Clinical cure 93% 93% 0.93
Abbreviation: APACHE, Acute Physiology and Chronic Health Evaluation; CI, continuous infusion; CNS, central nervous system; CRP, C-reactive protein; IAI, intra-abdominal infection; IB, intermittent bolus; ICU,
intensive care unit; LD, loading dose; LOS, length of stay; MV, mechanical ventilation; ND, not described; PK/PD, pharmacokinetic/pharmacodynamic; SOFA, Sequential Organ Failure Assessment; SSTI, skin and skin-
structure infection; UTI, urinary tract infection; WCC, white cell counts.
Legend:
aValues are reported as mean or median.
bBold values indicate statistical significance at p <0.05.
cValues are SAPS scores.
dStatistically significant difference in APACHE II scores on days 2, 3 and 4.
eA priori analysis.
22
1.4.6 Extended beta-lactam infusion
Although potential efficacies have been described, there are unfortunately several drawbacks
associated with CI such as the need for a dedicated IV line (Table 1-4) [13, 15, 264, 277].
Furthermore, some beta-lactams lack the physicochemical stability to be continuously exposed to
room temperatures that may lead to formation of degradation products [278-285]. Thus, extending
the infusion time, typically for three to four hours, has been suggested as an alternative way to
maximize the fT>MIC for some of these antibiotics [13, 286-288]. Several observational and
retrospective studies have suggested potential benefits associated with EI of beta-lactam antibiotics
particularly in patients with severe infections [164, 165, 286, 289-298]. In a recent multicentre,
retrospective cohort study, Yost et al., compared the effectiveness between EI of
piperacillin/tazobactam infusion and IB dosing of comparator antibiotics in 359 patients with
documented Gram-negative infections [295]. The authors found a decrease in mortality in the EI
group (9.7% versus 17.9%; p = 0.02) and further analysis confirmed that the dosing approach
prolonged survival by 2.77 days (p <0.01) in this study. Another non-randomized study of note
reported a significant lower 14-day mortality rate in patients with an Acute Physiology and Chronic
Health Evaluation II (APACHE II) score ≥17 favouring EI compared to IB administration of
piperacillin/tazobactam in critically ill patients infected with P. aeruginosa (12.2% versus 31.6%; p
= 0.04) [298]. Therefore, it has been suggested that EI of beta-lactam antibiotics is a suitable
alternative to IB dosing in critically ill patients. However, further prospective, clinical studies are
required to support the clinical benefits that were reported in these retrospective studies.
23
Table 1-4: Possible advantages and disadvantages of employing CI versus IB dosing of beta-
lactam antibiotics
Administration
method
Advantages Disadvantages
Continuous infusion Stable and predictable antibiotic PK
profiles
Intensive educational effort to
update clinical staff on the
administration method prior to
implementation
Lower antibiotic daily dose is a
possibility with this approach
Requires special infusion pumps
and infusion bags that are costly
Reduces drug acquisition costs
when lower antibiotic doses are
used
Some beta-lactams are not stable
under prolonged exposure at room
temperature
Intermittent bolus Effective resource consumption
(e.g., reduce the time required for
pharmacists or nurses to prepare
and administer antibiotic)
Risk of drug wastage is high with
this approach (e.g., when a patient
dies during treatment)
A simple antibiotic administration
method
PD targets may not be met
especially in critically ill patients
Does not require dedicated line
access for drug administration thus
incompatibility with other drugs is
not an issue
Neurological adverse effects are
theoretically more possible with
high Cmax
Less likely to have unexpected
device failures and dosing delivery
rate error
Abbreviation: Cmax, peak drug concentration over a dosing interval; PK, pharmacokinetic; PD,
pharmacodynamic.
1.4.6.1 Doripenem
Doripenem is a new member in the carbapenem class of beta-lactam antibiotics, which
demonstrates broad antibiotic coverage against Gram-positive, Gram-negative and anaerobic
pathogens including the highly resistant multi-drug resistant (MDR) strains [299, 300].
Furthermore, doripenem has enhanced activity compared to meropenem against P. aeruginosa
(doripenem minimum inhibitory concentration required to inhibit the growth of 90% of organisms
[MIC90]; 8 mg/L versus meropenem MIC90; 16 mg/L), one of the most frequently isolated
pathogens in the ICU [300]. With promising results in several clinical studies, doripenem has been
approved for the treatment of severe infections namely complicated intra-abdominal infections
24
[301], complicated urinary tract infections [302-304] and for nosocomial pneumonia [305, 306]. In
all these studies, doripenem was reported as effective and non-inferior to its comparator drug (i.e.,
imipenem, meropenem, piperacillin/tazobactam or levofloxacin) and to significantly reduce
mechanical ventilation and hospitalization days [307-312].
In the earlier phase of development, doripenem dosing was guided using a PK/PD approach [313-
316]. This approach is especially important for finding the most advantageous dosing regimen for
the treatment of less susceptible Gram-negative pathogens. Like other beta-lactams, doripenem
displays time-dependent activity whereby its efficacy is related to fT>MIC [317-319]. Combined with
its favourable stability profile, administering doripenem via EI to extend the fT>MIC is an appropriate
and appealing approach compared to CI and IB dosing. Furthermore, several PK/PD modelling
studies have provided data supporting extended doripenem infusion particularly if severe infections
are involved [53, 185-188, 313-316, 320-326].
A typical doripenem dose of 500 mg to 1000 mg every 8 hours, administered as a 1- to 4-hour IV
infusion, is recommended to enhance PK/PD target attainment, especially when dealing with severe
infections [313, 314, 316, 326]. However, to date, population PK/PD models to describe doripenem
usage have mostly been developed in heterogeneous patient groups [313, 314, 316, 326-329] which
are unlikely to address the PK differences and the disease severity of critically ill patients [6-8,
330]. For example, a doripenem dose of 500 mg every 8 hours as a 1-hour infusion is only effective
against pathogens with a MIC of ≤2 mg/L. This standard doripenem dose is likely to fail in
critically ill patients, who may have altered PK and who are commonly infected with pathogens
with higher MICs [331-335]. In this context, it is important to highlight the recent termination of an
industry-sponsored clinical trial investigating the use of doripenem in ventilator-associated
pneumonia (VAP) [336]. This phase III, prospective, multicentre, double-blind RCT aimed to
demonstrate the non-inferiority of a fixed 7-day course of doripenem (1 g every 8 hours as a 4-hour
infusion) compared to a 10-day course of imipenem-cilastatin (1 g every 8 hours as a 1-hour
infusion) in adult patients with VAP. The trial was terminated when interim analyses showed
greater clinical failure and mortality rates in the doripenem treatment arm. Further analysis (i.e.,
modified intention to treat [mITT] analysis group) also revealed that patients receiving doripenem
with high CLCR (150 mL/min) had clinical cure rates that were 27% worse than the comparator
group (doripenem 44.4% versus imipenem-cilastatin 71.4%, 95% confidence interval: -55.4% to
1.4%). This among other findings [187, 188, 322, 337] indicates that “one-dose-fits-all” dosing
approach is no longer relevant in critically ill patients due to their possible altered physiology and
25
thus, PK/PD analyses of doripenem are needed to develop clinically relevant dosing guidelines in
this population.
1.4.7 Summary
Several important pathophysiological changes in critically ill patients may alter antibiotic PK and
consequently influence PK/PD target attainment. Use of a standard dosing regimen, which is
usually derived from healthy volunteers, does not address the altered PK phenomenon and may
increase the likelihood of therapeutic failure. Furthermore, pathogens that are commonly isolated in
the ICU differ from the general wards in a way that their MICs tend to be relatively higher [334,
335]. Altered dosing approaches (i.e., CI and EI) may be needed to ensure effective antibiotic
exposure and may produce better therapeutic outcomes in critically ill patients.
26
Aims
This Thesis aims to better characterize the PK/PD of beta-lactam antibiotics in critically ill patients
and to determine whether there is any therapeutic advantage associated with the PI dosing strategy
(i.e., CI and EI) as compared to traditional IB dosing in this unique patient population.
The specific aims of the Thesis are:
1. To describe the population PK of doripenem in critically ill patients with sepsis in a
Malaysian ICU and to investigate sources of PK variability
To determine PK parameter estimates of doripenem in critically ill patients with
sepsis.
To identify potential covariates which would help to explain PK variability in this
population.
To develop clinically relevant dosing guidelines for this population which would
help to maximize therapeutic efficacy and minimizing antibiotic resistance.
2. To review the published literature describing the PK/PD and clinical outcomes associated
with CI versus IB dosing of beta-lactam antibiotics in hospitalized patients.
3. To perform a post hoc analysis on the Defining Antibiotic Levels in Intensive care unit
patients (DALI) study data to compare the PK/PD and clinical outcomes associated with PI
(i.e., CI and EI) versus IB dosing of beta-lactam antibiotics in a large cohort of critically ill
patients.
4. To identify the methodological shortcomings associated with current clinical studies seeking
to compare CI versus IB and to describe the criteria that should be considered for
performing a definitive clinical trial of this intervention in critically ill patients.
5. To perform a randomized controlled trial in order to determine if CI administration of beta-
lactam antibiotics is associated with improved clinical outcomes as compared to IB dosing
in a large cohort of critically ill patients with severe sepsis in a Malaysian ICU setting.
6. To review the published literature on the relevance of PK exposure and PD characteristics of
different antibiotic classes on maximizing therapeutic efficacy and minimizing development
of antibiotic resistance in critically ill patients.
27
Chapter 2: Population pharmacokinetics of doripenem in critically ill
patients with sepsis
2.1 Synopsis
Beta-lactam antibiotics are commonly used to treat severe infections due to their wide antibiotic
spectrum and overall tolerability. However, inappropriate usage has contributed to increases in
resistance to many beta-lactams and consequently, threatens the utility of this antibiotic family.
Furthermore, infection caused by MDR pathogens, such as P. aeruginosa, is significantly
associated with patient’s morbidity and mortality. Doripenem, the latest addition to the carbapenem
class of antibiotic, offers a glimmer of hope in the management of severe Gram-negative infections
as it demonstrates broad antimicrobial coverage against Gram-positive, Gram-negative and
anaerobic pathogens, including the “troublesome” MDR strains. For this reason, doripenem has
been approved for several indications, including complicated intra-abdominal infections,
complicated urinary tract infections and for nosocomial pneumonia. Like other beta-lactam
antibiotics, the length of time that drug concentrations remains above the MIC of infection-causing
pathogen is related to doripenem’s effectiveness. A typical doripenem dose of 500 mg to 1000 mg
every 8 hours, administered as a 1-hour IV infusion, is currently recommended for severe
infections. However, this dosing recommendation was developed based on the PK of doripenem in
healthy volunteers and therefore, pathophysiological alterations in critically ill patients were not
taken into consideration. As reported in previous studies, failing to account for critical-illness
related changes may lead to inadequate antibiotic exposure and therapeutic failure. Furthermore,
previous PK/PD analyses of doripenem have mainly been performed in non-infected, heterogeneous
Caucasian patient groups and therefore, the existing PK data may not accurately characterize the PK
differences of other population such as in the Malaysian critically ill population. This chapter
therefore aims to describe the population PK of doripenem in Malaysian critically ill patients with
sepsis and use Monte Carlo dosing simulations to develop clinically relevant dosing guidelines
specifically for these patients.
28
2.2 Manuscript entitled “Population pharmacokinetics of doripenem in
critically ill patients with sepsis in a Malaysian intensive care unit”
The manuscript entitled “Population pharmacokinetics of doripenem in critically ill patients with
sepsis in a Malaysian intensive care unit” has been accepted for publication in the Antimicrobial
Agents and Chemotherapy (2015).
The co-authors contributed to the manuscript as follows: Conception and development of the study
design was performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz, under the guidance of Prof.
Jason A. Roberts and Dr. Christine E. Staatz. Literature review was performed by the PhD
candidate, Mohd-Hafiz Abdul-Aziz, under the guidance of Prof. Jason A. Roberts and Dr. Christine
E. Staatz. Data collection was performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz, Azrin N.
Abd Rahman and Dr. Mohd-Basri Mat-Nor. Sample bioanalysis was performed by the PhD
candidate, Mohd-Hafiz Abdul-Aziz, under the supervision of Dr. Steven C. Wallis. PK/PD analysis
was performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz and Azrin N. Abd Rahman under
the supervision of Prof. Jason A. Roberts and Dr. Christine E. Staatz. The PhD candidate took the
leading role in manuscript preparation and all co-authors reviewed and contributed to the final draft
of the manuscript.
The accepted version of this manuscript is presented and incorporated in this chapter. However,
some text, tables and figures may have been inserted at slightly different positions to fit the overall
style of the thesis. Numbering of pages, tables and figures may also change to fit the thesis
requirements. Manuscript references have been collated with all other references in the thesis.
Permission has been granted by the publisher and copyright owner, American Society of
Microbiology, to reproduce the manuscript in this Thesis.
29
Population pharmacokinetics of doripenem in critically ill patients with sepsis in a Malaysian
intensive care unit
Authors
Mohd H. Abdul-Aziz (1, 2), Azrin N. Abd Rahman (2, 3), Mohd-Basri Mat-Nor (4), Helmi
Sulaiman (5), Steven C. Wallis (1), Jeffrey Lipman (1, 6), Jason A. Roberts (1, 6), Christine E.
Staatz (3, 7)
Affiliations
(1) Burns, Trauma and Critical Care Research Centre, The University of Queensland, Brisbane,
Australia.
(2) School of Pharmacy, International Islamic University of Malaysia, Kuantan, Pahang, Malaysia.
(3) School of Pharmacy, The University of Queensland, Brisbane, Australia.
(4) Department of Anaesthesiology and Intensive Care, School of Medicine, International Islamic
University of Malaysia, Kuantan, Pahang, Malaysia.
(5) Infectious Diseases Unit, Department of Medicine, Faculty of Medicine, University of Malaya,
Kuala Lumpur, Malaysia.
(6) Royal Brisbane and Women’s Hospital, Brisbane, Australia.
(7) Australian Centre of Pharmacometrics, Brisbane, Australia.
Running title: Population pharmacokinetics of doripenem.
Keywords: beta-lactams; carbapenems; intensive care; modelling; pharmacodynamics; prolonged
infusion.
Corresponding author:
Mr. Mohd Hafiz Abdul Aziz,
Burns, Trauma & Critical Care Research Centre, The University of Queensland,
Level 3, Ned Hanlon Building, Royal Brisbane & Women’s Hospital,
Herston, Queensland 4029, Australia
Ph +61736361847; Fax +61736463524
Email: [email protected]
30
2.2.1 Abstract
Doripenem has been recently introduced in Malaysia and is used for severe infections in the ICU.
However, limited data currently exist to guide optimal dosing in this scenario. We aimed to describe
the population PK of doripenem in Malaysian critically ill patients with sepsis and use Monte Carlo
dosing simulations to develop clinically relevant dosing guidelines for these patients. In this PK
study, 12 critically ill adult patients with sepsis receiving 500 mg of doripenem 8-hourly as a 1-hour
infusion were enrolled. Serial blood samples were collected on two different days and population
PK analysis was performed using a non-linear mixed effects modelling approach. A two-
compartment linear model with between-subject and between-occasion variability on CL was
adequate in describing the data. Typical Vd and CL of doripenem in this cohort was 0.47 L/kg and
0.14 L/kg/hr, respectively. Doripenem CL was significantly influenced by patients’ CLCR such that
a 30 mL/min increase in estimated CLCR would increase doripenem CL by 52%. Monte Carlo
dosing simulations suggested that for pathogens with a MIC of 8 mg/L, a dose of 1000 mg 8-hourly
as a 4-hour infusion is optimal for patients with CLCR of 30-100 mL/min whilst a dose of 2000 mg
8-hourly as a 4-hour infusion is best for patients manifesting a CLCR >100 mL/min. Findings from
this study suggest that for doripenem usage in Malaysian critically ill patients, an alternative dosing
approach may be meritorious, particularly when MDR pathogens are involved.
31
2.2.2 Introduction
Doripenem, a member of the carbapenem class of antibiotics, demonstrates broad antibiotic activity
including against the troublesome MDR pathogens [338]. The PK profile of doripenem closely
resembles that of other carbapenems. Similarly, this antibiotic demonstrates time-dependent
activity, where the PK/PD index that best correlates with its efficacy is fT>MIC [317]. Doripenem has
been approved for complicated intra-abdominal and urinary tract infections in the United States, and
is also indicated for nosocomial pneumonia in Europe and the Asia-Pacific. In Malaysia, doripenem
is commonly reserved for the management of complicated infections deemed to be caused by P.
aeruginosa and to some extent, Acinetobacter baumannii. As per local antibiotic guidelines,
patients receiving doripenem in a Malaysian ICU typically receive a standard dose of 500 mg 8-
hourly as a 1-hour IV infusion. However, the appropriateness of this dosing regimen is disputable as
it is based on PK/PD data derived from earlier studies which mostly recruited heterogeneous
cohorts of healthy volunteers and non-critically ill Caucasian patients [313, 314, 316, 326].
Importantly, results of subsequent PK/PD studies suggest that current recommendations may be
grossly flawed in critically ill patients and optimal dosing requirements may significantly differ
from that initially proposed [187, 188, 322].
Antibiotic dosing in critically ill patients is rarely a straightforward process [6]. Extreme alterations
in antibiotic PK, particularly increases in Vd and profound increases or decreases in renal drug CL,
are common occurrences in the ICU and may severely influence drug exposure [56, 121]. To further
complicate matters, pathogens that are usually isolated in the ICU differ from general wards, as they
are commonly less susceptible to the current antibiotic armamentarium [334, 335]. Additionally,
local microbiology and antibiotic resistance patterns may greatly vary across different geographical
regions affecting antibiotic dosing requirements [332]. In this context, it is imperative to consider
regional antibiotic susceptibility data whereby in the Asia-Pacific region, the MIC90 for doripenem
against P. aeruginosa was reported as 8 mg/L [332, 333]. As previously mentioned, the commonly
administered dose of 500 mg 8-hourly as a 1-hour infusion is reported to only be effective against
pathogens with an MIC of ≤2 mg/L and its application is therefore likely to fail in such a scenario
[313, 316].
Current population PK models which describe doripenem disposition have mostly been developed
in heterogeneous Caucasian patient groups [186, 187, 313, 314, 316, 321, 322]. However, it is
likely that the PK of doripenem may vary across different races and therefore, the existing PK
models may not accurately characterize the PK differences in Malaysian critically ill patients [339].
32
Interethnic differences, such as relatively smaller body size and lower body fat distribution among
Malaysian critically ill patients as opposed to their Caucasian counterparts, may influence
doripenem exposure and consequently, dosing requirements may also differ between these two
patient populations.
In this study, we aimed to describe the population PK of doripenem in Malaysian critically ill
patients with sepsis and also, to investigate sources of PK variability. With this resulting model, we
then sought to develop clinically relevant dosing guidelines specifically for these patients.
2.2.3 Materials and methods
2.2.3.1 Setting
This prospective, open-label PK study was undertaken in a general ICU of a tertiary hospital in
Pahang, Malaysia between November 2012 and October 2013. The study was registered and
approved by the Medical Research Ethics Committee Malaysia (ID: NMRR-12-649-13058).
Written informed consent to participate in the study was obtained from each participant or their
legally-authorized representative.
2.2.3.2 Study population
Patients were eligible for recruitment if they were; (a) adult (≥18 years old) ICU patients; and (b)
were prescribed doripenem for the treatment of sepsis (defined as presumed or confirmed infection
with SIRS manifesting in the previous 48 hours). Patients were excluded if they; (a) required any
form of extracorporeal renal support; (b) were pregnant or lactating mothers; or (c) were known or
presumed to be allergic to doripenem or any of the carbapenem antibiotics.
2.2.3.3 Doripenem administration and ancillary treatments
Doripenem (Doribax®; Janssen-Cilag, Raritan, NJ) was administered over 1-hour using a
volumetric infusion pump controller at a dose of 500 mg in 100 mL of 0.9% sodium chloride as part
of the patients prescribed course of therapy. All subsequent patient management, including the
addition of other antibiotics and drugs, was at the discretion of the treating clinician and was not
affected by study procedures.
33
2.2.3.4 Study protocol
PK sampling was performed during one 8-hour dosing interval on Day 1 (i.e., representing a
scenario when patients were presumed to be at their worst clinically) and Day 3 (i.e., representing a
scenario when patients were presumed to be more clinically stable) of doripenem treatment. Blood
samples (3 mL) were drawn from a central line and were collected into lithium-heparinised tubes at
the following times on Day 1 (occasion 1) and Day 3 (occasion 2) of therapy, immediately before
the first doripenem dose was administered, then 0.5, 0.75, 1, 1.5, 2, 4, and 8 hours after the start of
the infusion.
Blood samples were immediately refrigerated at 4°C and within 1 hour, centrifuged at 3000 rpm for
10 minutes to separate plasma. Plasma samples were frozen at -80°C within 24 hours of collection.
The frozen plasma samples were shipped on dry ice by a commercial courier company and were
then assayed at the Burns, Trauma and Critical Care Research Centre (BTCCRC), The University of
Queensland, Australia.
Apart from blood collection, various demographic, anthropometric and clinical data were also
collected prospectively. The severity of illness indices, which included the APACHE II score on
admission [340] and the SOFA scores on each occasion of sampling [52], were recorded. CLCR was
estimated on each occasion of sampling using the Cockcroft-Gault formula [341].
2.2.3.5 Doripenem assay
Doripenem concentrations in plasma samples were measured, after protein precipitation, by a
validated high-performance liquid chromatography (HPLC) method with ultraviolet detection on a
Shimadzu Prominence (Shimadzu Corporation, Kyoto, Japan) instrument. Cefotaxime was used as
the internal standard. Samples were assayed in batches, alongside calibration standards and quality
control replicates at high, medium and low concentrations. All bioanalysis techniques were
conducted in accordance with the US Food and Drug Administration’s guidance for industry on
bioanalysis [342]. The assay limit for doripenem in plasma was 0.2 mg/L, with precision and
accuracy determined at 5.7% and 4.4%, respectively. Linearity of the assay was demonstrated in the
range of 0.2-100 mg/L. Inter-assay precision and accuracy, determined at three different
concentrations over three separate days, were all within 7%. Observed concentrations of doripenem
were corrected for protein binding by reducing the concentrations by 10% [343].
34
2.2.3.6 Population pharmacokinetic analysis
2.2.3.6.1 Software
Plasma concentration-time data for doripenem were analysed using non-linear mixed-effect
modelling approach in NONMEM® version 7.3 (Icon Development Solutions, Ellicott City, MD,
USA) with an Intel® FORTRAN compiler and Perl-Speaks-NONMEM® (PsN) version 4.0 [344].
Throughout the model building process, typical population PK parameter estimates, between-
subject variability (BSV), between-occasion variability (BOV) and residual unexplained variability
(RUV) were estimated using the first-order conditional estimation with interaction (FOCE-I)
method. Data exploration and visualization, as well as model diagnostics were performed using PsN
version 4.0 [345], Pirana version 2.7.1 [346], and Xpose version 4.0 (http://xpose.sourceforge.net) in
R (http://www.r-project.org) [347].
2.2.3.6.2 Structural and stochastic model development
Plasma concentration-time data for doripenem were fitted to one-, two- and three-compartment
disposition models with first-order elimination using the ADVAN subroutines from the
NONMEM® library. BSV and BOV were evaluated using an exponential variability model. BSV
was evaluated on all PK parameter estimates and when significant, it was then included in the next
model-building step. Covariance between values of BSV was estimated using a variance-covariance
matrix. Additive, proportional and combined residual random error models were tested to describe
RUV.
Competing models were assessed on the basis of minimum objective function value (OFV),
goodness-of-fit diagnostics and their physiological plausibility. A reduction in the OFV of >3.84 for
one-degree of freedom was considered a statistically significant improvement (p <0.05) for a nested
model. Observed versus population predicted concentration (PRED) or individual predicted
concentration (IPRED) plots, individual weighted residual (IWRES) versus IPRED plots, and
conditional weighted residual (CWRES) versus time after dose plots were used to evaluate the
graphical goodness-of-fit of various models.
2.2.3.6.3 Covariate screening and model development
Potential covariates that were clinically plausible were screened for their influence on the PK of
doripenem. Factors tested included patient total body weight, estimated CLCR and SOFA score on
35
the day of investigation. Covariate effects were identified via visual (scatter plots) and also
numerical (stepwise, generalized additive models by Xpose version 4.0) methods. Allometric
scaling was applied a priori and fixed to theory based values of ¾ for CL and 1 for Vd, all
standardized to a bodyweight of 70 kg [348]. The covariate-parameter models that were evaluated
were linear, piecewise-linear, exponential, power and sigmoidal models. During the covariate
model-building process, stepwise forward inclusion and backward elimination approaches were
employed. A reduction in the OFV of >3.84 (p <0.05) and >10.83 (p <0.01) was required for a
covariate to be considered significant in the forward inclusion and backward elimination steps,
respectively.
2.2.3.6.4 Model evaluation and prediction
A non-parametric bootstrap method (n = 2000) was used to assess the final model accuracy and
stability. From the bootstrap empirical posterior distribution, 95% confidence interval for the
bootstrap replicates were obtained and compared with parameter estimates from the final model. A
visual predictive check (VPC) was also performed by simulating 5000 patients to evaluate the
predictive performance of the final model. Visual checks were performed by overlaying the
observed data points with the 95% confidence intervals of the simulated 5th, 50th and 95th percentile
curves.
2.2.3.6.5 Dosing simulations
Different doripenem dosing regimens in subjects with various degrees of renal function were
examined using Monte Carlo simulation in NONMEM®. Final PK model parameter estimates were
used to generate concentration-time profiles based on 1000 simulations. Both a 1- and 4-hour
infusion of 250 mg, 500 mg, 1000 mg and 2000 mg of doripenem every 8 hours was examined in
subjects with a CLCR of 30 mL/min, 50 mL/min, 70 mL/min, 100 mL/min and 150 mL/min,
respectively. The probability of target attainment (PTA) for a dosing regimen was calculated as the
percentage of patients achieving an fT>MIC of 40% for a given MIC. These probabilities were then
plotted against a range of MICs and optimal dosing was denoted by achieving at least 90% PTA.
36
2.2.4 Results
2.2.4.1 Demographic and clinical data
A total of 140 plasma samples across two sampling occasions were collected from 12 critically ill
patients. Demographic and clinical characteristics of the recruited patients are presented in Table 2-
1. More than 65% of the cohort were males and ≥45 years of age. Median APACHE II and SOFA
score on admission was 19 and 6, respectively. Median SOFA scores were similar on both sampling
occasions. More than half of the patients had an estimated CLCR of ≥80 mL/min on ICU admission.
The median CLCR on occasion 1 (88.0 mL/min) was higher than on occasion 2 (72.0 mL/min). The
majority (66.7%) received doripenem for VAP and the most prevalent causative pathogen identified
was A. baumannii. All patients required invasive mechanical ventilation and vasopressor support.
Three patients died during their ICU stay and the deaths were more likely to be related to patients’
pre-existing comorbidities and progressive worsening of their clinical conditions. All three patients
had a pre-ICU hospital stay of ≥2 months prior to study inclusion.
2.2.4.2 Pharmacokinetic model-building
The time course of doripenem in plasma was adequately described by a two-compartment linear
model with combined residual error. BSV on CL (ΔOFV = -97.1), central volume of distribution
(V1; ΔOFV = -46.6) and peripheral volume of distribution (V2; ΔOFV = -8.04) significantly
improved the model fit. Introduction of BOV on CL (ΔOFV = -26.9) resulted in further model
improvement.
During covariate testing inclusion of an influence of CLCR (normalized to the population mean
value of 82.5 mL/min) on CL improved the model fit (decreasing the OFV by 32.3 points and
reducing BSV on CL from 56.7% to 10.4%). The influence of CLCR on CL of doripenem was best
described in an exponential relationship as shown in Eq. 1:
(1)
where CL is the estimated doripenem clearance in a given individual (in L/hr/70 kg), θCLpop is the
typical value of doripenem clearance in the population; describes the influence of creatinine
clearance on doripenem clearance and CLCR is the patient’s estimated creatinine clearance (in
mL/min). Typical PK parameter estimates from the base and final model are summarized in Table
2-2.
37
Table 2-1: Clinical and demographic details of the enrolled patients
Subject Sex Age
(in years)
BMI
(kg/m2)
APACHE IIa SOFAb Admission diagnosis CLCR
(mL/min)c
Causative
pathogen
Clinical outcome
1 M 68 23.4 22 10 Intra-abdominal sepsis 30 Nil Survived
2 M 39 21.8 17 7 VAP 77 A. baumannii Died
3 F 19 16.7 11 3 VAP 161 A. baumannii Survived
4 M 74 29.7 18 5 Intra-abdominal sepsis 65 A. baumannii Died
5 M 61 29.7 12 6 VAP 119 Nil Survived
6 M 49 23.2 19 6 VAP 116 Nil Survived
7 M 31 22.6 16 7 Intra-abdominal sepsis 92 Nil Survived
8 M 44 20.8 21 5 VAP 126 A. baumannii Died
9 M 54 24.2 39 7 VAP 36 Nil Survived
10 M 58 24.7 20 5 VAP 44 A. baumannii Survived
11 M 57 19.3 15 4 VAP 99 P. aeruginosa Survived
12 F 31 22.2 23 5 Intra-abdominal sepsis 66 Nil Survived
Median 52 22.9 19 6 85
IQR 33-60 21.1-24.6 15-22 5-7 49-118
Abbreviation: APACHE II, Acute Physiology and Chronic Health Evaluation II; BMI, body mass index; CLCR, estimated Cockcroft-Gault creatinine
clearance; F, female; M, male; SOFA, Sequential Organ Failure Assessment; VAP, ventilator-associated pneumonia.
Legend:
aAPACHE II score on admission.
bSOFA score on admission.
cEstimated creatinine clearance on admission.
38
Table 2-2: Typical population parameter estimates for the base and final covariate model and
the 2000 bootstrap runs
Base
Model
Final
Model
Bootstrap (n = 2000)
Mean Median 95% CI
2.5% 97.5%
Objective function value,
OFV
381.03 348.76
Fixed effects
CL (L/hr/70kg) 11.5 10.1 9.9 9.9 8.9 10.9
V1 (L/70kg) 15.5 15.5 16.1 15.8 10.5 22.0
V2 (L/70kg) 17.9 17.7 18.6 18.1 12.2 26.6
Q (L/hr/70kg) 36.6 36.3 36.1 36.8 28.4 41.5
- 0.014 0.014 0.014 0.012 0.017
Between-subject variability,
BSV
CL (%) 56.7 10.4 14.8 14.3 4.8 21.5
V1 (%) 62.0 59.7 59.3 57.2 22.8 87.0
V2 (%) 73.3 73.8 68.4 64.7 40.0 94.0
Between-occasion
variability, BOV
CL (%) 33.9 22.2 16.2 8.7 4.11 28.3
Random error
Proportional (% CV) 8.3 9.0 10.0 9.1 3.7 18.8
Additive (SD, mg/L) 1.31 1.25 0.97 1.17 0.17 1.64
Abbreviation: CL, clearance; CV, coefficient of variation; Q, inter-compartmental clearance; V1,
volume of distribution of central compartment; V2, volume of distribution of peripheral
compartment; , effect of estimated Cockcroft-Gault creatinine clearance on doripenem
clearance.
Final model:
39
Basic goodness-of-fit plots, including the CWRES versus time after dose plot, demonstrated that the
final model adequately described the data with little model mis-specification (Figure 2-1). PRED
and IPRED values were in good agreement with observed doripenem concentrations. CWRES
values were generally homogeneously distributed over the sampling period. In a VPC plot
associated with the final model the predicted median curve demonstrated a good fit to the observed
data, albeit with a slight over-prediction of concentrations during the elimination phase (Figure 2-
2). Results from the non-parametric bootstrap further corroborated the robustness of the final
model, demonstrating narrow 95% confidence interval with bootstrap median values close to typical
population PK parameter estimates of the final model (Table 2-2).
Figure 2-1: Goodness-of-fit plots associated with final population pharmacokinetic model for
doripenem
Legend: The solid black line represents the line of identity and the dashed grey line represents the
smooth fitting for observations. Clinical observations are represented by the black solid circles.
40
Figure 2-2: Visual predictive check plot associated with the final population pharmacokinetic
model for doripenem
Legend: The solid black circles represent the observed data, the solid grey line represents the 50th
percentile of the observed data, the solid black line represents the 50th percentile of the simulated
data, the dashed grey lines represent the 5th and 95th percentiles of the observed data, the dashed
black lines represent the 5th and 95th percentiles of the simulated data and the shaded areas represent
the 95% confidence intervals of the 5th, 50th and 95th percentiles of the simulated plasma
concentrations.
2.2.4.3 Dosing simulations
The PTA for 40% fT>MIC for various doripenem dosing regimens, with varying MIC and CLCR
values, are presented in Figure 2-3. In patients with a CLCR of 70 mL/min, a standard doripenem of
500 mg 8-hourly as a 1-hour infusion demonstrated optimal rates of PTA (>90%) against pathogens
with an MIC of ≤2 mg/L. In other scenarios, alternative dosing strategies showed better rates of
target attainment; with 1000 mg and 2000 mg 8-hourly as a 4-hour infusion demonstrating optimal
rates of PTA against pathogens with an MIC of ≤8 and ≤16 mg/L, respectively. Increasing CLCR
values were associated with lower rates of PTA for the same MIC. With increasing MIC values, the
likelihood of obtaining optimal PTA diminishes whilst increasing the dose and prolonging the
duration of infusion resulted in higher rates of PTA.
41
Figure 2-3: The probability of target attainment for various simulated doripenem dosing
regimens to achieve 40% fT>MIC in patients with a creatinine clearance of (a) 30 mL/min; (b)
50 mL/min; (c) 70 mL/min; (d) 100 mL/min; and (e) 150 mL/min
Abbreviation: MIC, minimum inhibitory concentration.
Legend: The dashed black lines denote optimal doripenem dosing, which was signified by
achieving at least 90% of probability of target attainment.
2.2.5 Discussion
Despite profound PK and physiological differences to the non-critically ill population, critically ill
patients are typically given conventional dosing regimens [27], potentially leading to sub-optimal
antibiotic exposure and subsequently, therapeutic failures. Failure of emerging antibiotics in several
recent clinical trials recruiting critically ill patients underscores the deficiencies associated with the
licensed “one-dose-fits-all” dose in this unique population [336, 349]. Furthermore, the
ramifications of this simplistic dosing approach may be more severe in some geographical regions,
42
particularly among the Southeast Asian countries, where local microbiology and antibiotic
resistance patterns significantly vary from that of the Western countries. In our current study, we
were able to demonstrate how bacterial susceptibility and physiological changes associated with
critical illness substantially influence optimal doripenem exposure and importantly, how these
alterations may be circumvented via alternative dosing strategies.
In our cohort of critically ill patients, the PK of doripenem was best described using a two-
compartment model with zero-order input and first-order elimination. Such a disposition model is in
agreement with other currently available literature in critically ill patients with conserved renal
function [185-188]. Typical Vd (V1 + V2) of doripenem in our cohort was 0.47 L/kg (range: 0.14-
1.7 L/kg), which is generally consistent with other reports in critically ill patients with conserved
renal function (0.30-0.54 L/kg) [185-188]. This estimate is considerably larger than that previously
described in healthy volunteers (0.22-0.24 L/kg) [328, 329] and non-critically ill patients (0.18-0.24
L/kg) [320, 321, 323, 327]. This is anticipated as the Vd of hydrophilic antibiotics, such as
aminoglycosides [350, 351] and beta-lactams [56], are often reported to be two-fold greater in
critically ill patients. This could be attributed to extreme fluid extravasation into the interstitium, a
phenomenon commonly associated with increasing sickness severity [61]. Furthermore, medical
interventions including aggressive fluid resuscitation [66] and mechanical ventilation [71], both of
which were provided to all of our patients during their earlier course of therapy, have been
associated with increased Vd.
Typical CL of doripenem in this cohort was 0.14 L/kg/hr (range: 0.06-0.45 L/kg/hr), which is
generally consistent with that reported in critically ill patients with conserved renal function (0.12-
0.25 L/kg/hr) [185-188]. However, this estimate is notably lower than that previously described in
healthy volunteers (0.22-0.25 L/kg/hr) [328, 329] and non-critically ill patients (0.16-0.25 L/kg/hr)
[320, 322, 323, 327]. The differences are expected as the non-critically ill population would
presumably have better end-organ function than our patient cohort. Consistent with previous data
[185, 313, 320, 327], estimated Cockcroft-Gault CLCR, a surrogate measure for renal function in our
analysis albeit being less accurate as measured CLCR, was a key predictor of doripenem CL. This
relationship is highly predictable since doripenem is extensively cleared via renal elimination;
approximately 75% and in some reports, up to 90% of doripenem is cleared via the renal route
[329]. Based on Eq. 1, a 30 mL/min increase in the estimated CLCR would increase doripenem CL
by 52%.
43
Our model was also significantly improved with the incorporation of BOV on CL, denoting a
certain degree of variability in doripenem CL between the first and second sampling occasion.
Based on Eq. 1, doripenem CL on Day 1 (0.16 L/kg/hr) was approximately 30% higher than on Day
2 (0.12 L/kg/hr). Essentially, this means that dosing requirements in this population may be
dynamic and as such, regular dosing reviews and modifications may also be needed throughout
antibiotic treatment. Given the variability in antibiotic exposures is being increasingly reported in
critically ill patients, beta-lactam therapeutic drug monitoring (TDM) is highly warranted in this
population and the approach would appear to be meritorious, not only to prevent underdosing which
may increase the likelihood of antibiotic resistance, but also to minimize the risk of adverse effects
during therapy.
ARC [109] is highly prevalent in most ICU settings (17.9-41.1%) [352, 353], including Malaysian
critically ill populations [354] and has been linked with sub-therapeutic concentrations of beta-
lactams and poor clinical outcomes [120, 121, 164]. In patients with an elevated CLCR (≥130
ml/min), a conventional “one-dose-fits-all” approach to doripenem dosing appears to be grossly
flawed. Our Monte Carlo simulations highlighted that while a standard dose of 500 mg 8-hourly as
a 1-hour infusion in a patient with a CLCR of 70 mL/min would have 98.7% PTA against pathogens
with an MIC of 2 mg/L, a patient with ARC manifesting a CLCR of 150 mL/min, would only have
9.9% PTA. The repercussions of neglecting the phenomenon when dosing antibiotics in critically ill
patients can be highlighted by the premature termination of a Phase III, prospective, multicentre,
double-blind, RCT comparing a fixed 7-day course of doripenem (1000 mg 8-hourly as a 4-hour
infusion) with a 10-day course of imipenem-cilastatin (1000 mg 8-hourly as a 1-hour infusion) in
critically ill adult patients with VAP [336]. The trial was terminated when interim analyses revealed
greater clinical failure and mortality rates in the doripenem treatment arm. Crucially, further
analysis in the modified intention to treat group also showed that patients receiving doripenem with
high CLCR (>150 mL/min) had clinical cure rates 27% worse than the comparator group (95%
confidence interval 1.4% to 55.4%). Essentially, patients at high risk of ARC, such as young trauma
patients without significant organ dysfunction [109], need to be identified early so that appropriate
dose modifications can be implemented immediately.
In Malaysia, particularly in our ICU, doripenem monotherapy is reserved for the management of
complicated infections deemed to be caused by P. aeruginosa, and to some extent A. baumannii. In
two large antibiotic susceptibility prevalence studies conducted in the Asia-Pacific region [332,
333], the MIC90 for doripenem against P. aeruginosa was 8 mg/L. Our data suggest that for such an
MIC, a dose of 1000 mg 8-hourly as a 4-hour infusion is optimal for patients with CLCR of 30-100
44
mL/min and a dose of 2000 mg every 8-hourly as a 4-hour infusion is best for patients manifesting a
CLCR >100 mL/min. Such recommendations are consistent with several large PD simulation studies
conducted in the Asia-Pacific region [331, 355] as well as other parts of the world [314, 356]. This
study provides additional PK/PD data to support an alternative doripenem dosing approach in
critically ill patients, particularly when pathogens with high MIC are involved. However, future
clinical studies, preferably in the form of a multinational RCT, are required to ascertain the clinical
efficacy and safety of the suggested doripenem dosing regimen in this patient group. For A.
baumannii, which is commonly MDR, empirical combination antibiotic therapy is currently
preferred than doripenem monotherapy in our ICU. Furthermore, the MIC90 for doripenem against
A. baumannii in the Asia-Pacific region was reported as ≥32 mg/L [332, 333]. For such an MIC,
even with a dose of 2000 mg 8-hourly as a 4-hour infusion, optimal exposure is only achieved for
patients with reduced CLCR in our cohort (e.g., <70 mL/min).
This study has several limitations. A relatively small number of critically ill patients (n = 12) with a
narrow bodyweight- and CLCR-range were included and thus, our model may not fully characterize
the PK of doripenem in all Malaysian ICU patients. A number of patients with conserved renal
function were recruited to examine altered dosing approaches in this cohort. Dosing
recommendations derived from our Monte Carlo simulations should not be extrapolated to other
patient populations such as the obese or those on extra-corporeal renal support. We also
acknowledge limitations with the Cockcroft-Gault formula in estimating renal function in this
cohort, with measured CLCR more appropriate in the ICU setting. Neither free (unbound) doripenem
concentrations nor drug concentration at the sites of infections (e.g., epithelial lining fluid
concentrations) were measured in this study. Total doripenem concentration was measured and
applied in the analysis with correction for protein binding. We believe that this approach is highly
acceptable for drugs with low protein-binding properties, such as doripenem (approximately 10%
protein bound) [99]. Although data on concomitant drugs were available, we did not evaluate the
PK of those drugs and their potential influence on doripenem exposure in critically ill patients.
2.2.6 Conclusions
Critically ill patients frequently manifest extreme physiological changes, which may alter antibiotic
PK and subsequently reduce effective drug exposure. Importantly, findings from this study further
show that the licensed “one-dose-fits-all” dosing strategy for doripenem is likely to be flawed in the
critically ill population. An alternative dosing approach such as the empirical use of a prolonged 4-
45
hour infusion may be considered to account for PK and illness-severity differences in this unique
patient population, particularly when MDR Gram-negative organisms are involved.
2.2.7 Acknowledgments
This project has received funding from the International Islamic University of Malaysia (IIUM)
Research Endowment Grant. Mohd H. Abdul-Aziz and Azrin N. Abd Rahman would like to
acknowledge the support of the Ministry of Education, Malaysia in the form of scholarship. Jason
A. Roberts is funded by a Career Development Fellowship from the National Health and Medical
Research Council of Australia (APP1048652).
46
2.3 Conclusion
This chapter describes how critically ill patients are markedly different from those in general ward
settings and demonstrates how these differences influence doripenem dosing requirements. The Vd
and CL of doripenem in this patient cohort were observed to be substantially different than those
usually described in healthy volunteers and non-critically ill patients. As current dosing
recommendations were mostly derived from these two populations, findings from this study further
emphasize that the licensed “one-dose-fits-all” dosing strategy for doripenem is likely to be flawed
in critically ill patients. The findings of presented in this chapter also provides additional PK/PD
data which supports alternative dosing approaches for doripenem in critically ill patients,
particularly when less-susceptible pathogens are involved.
47
Chapter 3: Continuous beta-lactam infusion in critically ill patients: a
structured review of published literatures
3.1 Synopsis
Mortality rates due to severe sepsis and septic shock in critically ill patients remain persistently high despite
recent therapeutic advances. Beta-lactam antibiotics are commonly used and are regarded as first-line
therapies around the world, particularly in the management of critically ill patients with severe sepsis.
However, dosing modifications for these antibiotics are frequently needed in critically ill patients to prevent
therapeutic failures due to significant pathophysiological perturbations in this patient population over time.
Beta-lactam antibiotics display time-dependent bacterial kill characteristics, whereby fT>MIC best describes
their antimicrobial properties. In terms of drug administration, CI administration of beta-lactam antibiotics,
as opposed to conventional IB dosing, is more likely to achieve this PK/PD end-point. Despite this
theoretical advantage, a global shift away from the traditional dosing method towards CI administration has
been difficult to be instigated as comparative studies in humans mostly fail to demonstrate a significant
difference in clinical outcomes between the two dosing approaches. However, comparisons between the two
dosing approaches were mostly performed in heterogeneous non-critically ill patient population and thus, the
question still remains whether there is any real benefit of administering beta-lactam antibiotics via CI dosing
in critically ill patients. Therefore, this chapter aims to critically analyse the available literature, by
comparing the PK/PD data and clinical outcomes associated with by CI and IB dosing, in order to establish
any potential benefits supporting either of the two dosing approaches for critically ill patients.
48
3.2 Manuscript entitled “Continuous infusion vs. bolus dosing: implications
for beta-lactam antibiotics”
The manuscript entitled “Continuous infusion vs. bolus dosing: implications for beta-lactam
antibiotics” has been accepted for publication in the Minerva Anestesiologica (2012; 78 (1): 94-
104).
The co-authors contributed to the manuscript as follows: Conception and development of the study
design was performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz, under the guidance of Prof.
Jason A. Roberts and Prof. Jeffrey Lipman. Literature review was performed by the PhD candidate,
Mohd-Hafiz Abdul-Aziz, under the guidance of Prof. Jason A. Roberts. The PhD candidate took the
leading role in manuscript preparation and all co-authors reviewed and contributed to the final draft
of the manuscript.
The accepted version of this manuscript is presented and incorporated in this chapter. However,
some text, tables and figures may have been inserted at slightly different positions to fit the overall
style of the thesis. Numbering of pages, tables and figures may also change to fit the thesis
requirements. Manuscript references have been collated with all other references in the thesis.
Permission has been granted by the publisher and copyright owner, Edizioni Minerva Medica, to
reproduce the manuscript in this Thesis.
49
CONTINUOUS INFUSION VS. BOLUS DOSING: IMPLICATIONS FOR BETA-LACTAM
ANTIBIOTICS
Authors
Mohd H. Abdul-Aziz (1), Christine E. Staatz (2), Carl M. J. Kirkpatrick (3), Jeffrey Lipman (4, 5),
Jason A. Roberts (4, 5, 6)
Affiliations
(1) School of Pharmacy, International Islamic University of Malaysia, Kuantan, Malaysia.
(2) School of Pharmacy, University of Queensland, Brisbane, Australia.
(3) Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, Australia.
(4) Burns, Trauma and Critical Care Research Centre, University of Queensland, Brisbane,
Australia.
(5) Department of Intensive Care, Royal Brisbane and Women’s Hospital, Brisbane, Australia.
(6) Pharmacy Department, Royal Brisbane and Women’s Hospital, Brisbane, Australia.
Keywords: Beta-lactam antibiotic; clinical outcome; continuous infusion; bolus dosing;
pharmacodynamics; pharmacokinetics.
Address for correspondence
Prof. Jeffrey Lipman,
Burns, Trauma & Critical Care Research Centre,
Level 3 Ned Hanlon Building, Royal Brisbane and Women’s Hospital,
Butterfield St, Brisbane,
Queensland 4029 Australia.
Ph: +61736361852 Fax: +61736363542
50
3.2.1 Abstract
Beta-lactam antibiotics display time-dependant PD whereby constant antibiotic concentrations
rather than high peak concentrations are most likely to result in effective treatment of infections
caused by susceptible bacteria. CI administration has been suggested as an alternative strategy, to
conventional IB dosing, to optimize beta-lactam PK/PD properties. With increasing data emerging,
we elected to systematically investigate the published literature describing the comparative PK/PD
and clinical outcomes of beta-lactam antibiotics administered by CI or IB. We found that the studies
have been performed in various patient populations including critically ill, cancer and cystic fibrosis
patients. Available in vitro PK/PD data conclusively support the administration of beta-lactams via
CI for maximizing bacterial killing from consistent attainment of PD end-points. In addition,
clinical outcome data supports equivalence of CI and IB, even with the use of a lower dose with CI.
However, the present clinical data is limited with small sample sizes commonly associated with
insufficient power to detect advantages in favour of either dosing strategy. With abundant positive
pre-clinical data as well as document in vivo PK/PD advantages, large multicentre RCTs are needed
to describe whether CI administration of beta-lactams is truly more effective than IB dosing.
51
3.2.2 Introduction
The mortality rate due to severe sepsis and septic shock remains high despite recent therapeutic
advances. Source control of the pathogen along with early and appropriate antibiotic administration
remains the best strategy available to clinicians in the management of critically ill septic patients
[330, 357]. However, appropriate antibiotic administration is not straightforward as critically ill
patients may develop pathophysiological changes that alter the PK of the prescribed antibiotic [8,
64]. Indeed dosing that does not account for these pathophysiological changes may lead to
inadequate antibiotic concentrations and therapeutic failure. Therefore, different dosing approaches
may be required to ensure that antibiotic concentrations meet PK/PD targets likely to enable clinical
success.
Beta-lactam antibiotics are still regarded as key antibiotics in severe infections due to their spectrum
of antibacterial activity and overall tolerability. These antibiotics display time-dependent PD
whereby fT>MIC best describes their bacterial kill characteristics (5). Based on this property,
maximal beta-lactam activity is thought to be achieved by utilizing either smaller doses more
frequently than standard IB dosing or utilizing EI or CI.
The aim of this paper is to systematically review and critically analyse the published literature
comparing the PK and clinical outcomes of administering beta-lactams by IB and CI in various
patient populations. The review will address the question on which administration strategy most
consistently achieves PK/PD targets and results in improvement of clinical endpoints.
Data for this review were identified by incorporating PUBMED searches (1966 to February 2011)
and references from relevant papers. Search terms were “continuous infusion” or “intermittent
infusion”, “antibiotic” or “antibacterial” or “antimicrobial”, “beta-lactams” or “penicillins” or
“cephalosporins” or “monobactams” or “carbapenems” and “pharmacokinetics” or
“pharmacodynamics”. Relevant primary research papers comparing the administration of beta-
lactams by IB and CI were identified and evaluated. All relevant English original articles were
systematically evaluated. To emphasize new developments in this area, we have given particular
focus to the more recently published studies. Below, we discuss the published studies in terms of
PK and clinical outcomes and then outline the results that have been obtained in specific patient
populations.
52
3.2.3 The Pharmacodynamics of Beta-lactams
Beta-lactam antibiotics include the penicillins, cephalosporins, carbapenems and monobactams.
These antibiotics have slow bacterial kill characteristics which are almost exclusively dependent on
the serum free drug concentration exceeding the MIC of the pathogen [12]. Maximal beta-lactam
bacterial killing is achieved when the serum free drug concentration is maintained at 4-5 times the
MIC [152]. The PD of beta-lactams have been extensively reviewed by Turnidge previously [358].
One of the main areas of contention for the PD of beta-lactams relates to the comparative target
exposures required for CI and for IB. Mouton and den Hollander used an in vitro PK model that
was able to replicate plasma ceftazidime concentrations administered by IB or by CI [152]. In this
study, the authors found that maintaining a CI concentration near the MIC does not provide
bacterial killing advantages over IB. However, when concentrations are maintained at 4 x MIC, CI
is associated with significantly greater bacterial killing. In combination with other available PD
data, this data suggests that therapeutic targets for CI therapy should be a steady-state concentration
(Css) that is at least 4 x MIC. It follows, that comparative PK studies should be evaluating the
relative ability of IB to achieve a Cmin greater than the MIC of the likely pathogen (this is likely to
ensure 40-70% of the time that free (unbound) drug concentration remains four times above the
MIC during a dosing interval [fT>4xMIC]) and for CI, a Css greater than 4 x MIC.
Of particular importance, published PK/PD studies need to be interpreted in light of the new
susceptibility breakpoints that have been classified by the European Committee on Antimicrobial
Susceptibility Testing (EUCAST; available at: http://www.eucast.org/clinical_breakpoints) [359]
and Clinical and Laboratory Standards Institute (CLSI; available at http://www.clsi.org/) [360, 361].
Specifically, the recent EUCAST susceptibility breakpoint recommendations are lower than those
of CLSI, which may in turn influence clinicians’ view on the results from PK/PD studies. These
new data may mean that the present dosing approaches are more, or less likely to achieve PK/PD
targets.
3.2.4 Comparative Studies between Intermittent and Continuous Administration
3.2.4.1 Plasma Pharmacokinetics
Before describing the published data, it is important to note that the PK advantages reported by
studies comparing the Cmin from IB and Css from CI of beta-lactams are expected based on PK
principles. Statistically significant differences favouring CI would be seen as the Css will always be
53
higher than Cmin from IB. This concept is described in Figure 3-1 which uses PK modelled data,
adapted from a previous study with flucloxacillin [102], to describe the inevitability of achieving a
higher Css from CI in critically ill patients. This limitation has also been discussed in a review article
by Roberts et al., identifying the deficient reporting approach in some PK studies resulting
disadvantages to IB [277]. The key comparison in the PK studies should be the achievement of the
PD end-points, 100% fT>MIC for IB and 100% fT>4xMIC for CI. We would advocate a PD target of
100% fT>MIC for IB as this is likely to result in a concentration 4 x MIC for 40-70% of the dosing
interval as required for the different classes of beta-lactams.
Figure 3-1: Comparative flucloxacillin concentration between continuous (CI) and
intermittent administration (IB) assuming similar pharmacokinetic properties in ICU
patients. The same daily dose for IB and CI was simulated from a previous population
pharmacokinetic study whereby 2 g 6 hourly for IB and 8 g over 24 hours was simulated for
CI
Legend:
Continuous infusion (dotted lines); intermittent bolus dosing (solid lines).
Studies comparing the plasma PK of IB and CI administration of beta-lactams have generally
shown that administration via CI maintains superior concentrations throughout a treatment period.
Table 3-1 compares the published data of plasma pharmacokinetic exposures for each
administration method.
54
Table 3-1: Comparison of respective plasma pharmacokinetic between continuous and intermittent administration of beta-lactams in critically ill or septic patients
Antibiotic n Design MIC
(mg/L)
Dosage Regimen AUCa
(mg/L*h)
Cmaxa
(mg/L)
Cmina
(mg/L)
Cssa
(mg/L)
%fT>MIC
(%)
CI IB CI IB IB IB CI CI IB
Piperacillinb
[85]
13 RCT
(critically ill septic)
- 12 g/24 hrs 4 g q6/8hrs 464 803 152
(90-275)
2
(2-8)
17
(11-24)
- -
Piperacillinb
[253]
7 Randomized crossover
(critically ill septic)
- 4 g LD then 8 g/24 hrs 4 g q8hrs 210±120 391±183 228
(172-359)
4.8
(1-43)
22
(14-53)
- -
Piperacillin
[362]
52 RCT
(complicated intra-abdominal infections)
- 2 g LD then 12/24 hrs 3 g q6hrs - - 122±30 - 35±12 100 95
Piperacillinb
[173]
24 RCT
(severe infections)
- 2 g LD then 8 g/24 hrs 4 g q8hrs 936 - - - 39 - -
Meropenem
[253]
6 Randomized crossover
(critically ill with CRRT)
8 0.5 g LD then 2 g/24 hrs 1 g q12hrs 227
(182-283)
233
(202-254)
63
(51-85)
8
(5-18)
19
(13-25)
100 46
Meropenemb
[193]
15 Randomized crossover
(critically ill septic)
- 2 g LD then 3 g/24 hrs 2 g q8hrs 118±13 194±21 110±7 9±1 12±5 - -
Meropenem
[86]
10 RCT
(critically ill septic)
4 0.5 g LD then 3g/24 hrs 1.5 g LD then 1 g q8hrs 99c 97c 93
(74-119)
0
(0-2)
7d
(5-16)
100e 80e
Ceftazidime
[82]
18 RCT
(severe intra-abdominal infections)
8 1 g LD then 4.5 g/24 hrs 1.5 g q8hrs 1131
(505-2230)
1064
(505-1950)
89
(58-125)
19
(6-68)
47
(21-93)
67f 69f
Ceftazidime
[254]
30 RCT
(critically ill, trauma, VAP)
- 2 g LD then 60 mg/kg/24
hrs
2 g q8hrs - - 91±44 4±4 19±9 100 100g
Ceftazidimeb
[363]
12 Randomized crossover
(critically ill septic)
P. aeruginosa
isolate
2 g LD then 3 g/24 hrs 2 g q8hrs 112±56 331±165 124±53 25±18 30±17 100 92
Ceftazidimeb
[364]
56 Randomized crossover
(Cystic fibrosis-chronic)
- 100 mg/kg over 23.5 hrs 200 mg/kg divided thrice
daily
- - 159±44 9±5 32±12 - -
Ceftazidime
[365]
49 Randomized crossover
(Cystic fibrosis-acute exacerbation)
- 60 mg/kg LD then 200
mg/kg over 23 hrs
200 mg/kg divided thrice
daily
- - 216±72 12±9 56±23 - -
Ceftazidimeb
[366]
14 (Cystic fibrosis-chronic) - 100 mg/kg over 24 hrs 200 mg/kg divided thrice
daily
- - - 10±12h 30±10h - -
Temocillin
[247]
13 RCT
(critically ill septic)
16 2 g LD then 4 g/24 hrs 2 g q12hrs 1759±188 1856±282 147±12 28±5 73±3 100 51
Cefazolin
[168]
20 RCT
(peri-operative-CPB)
8 2 g LD then 3 g/18 hrs 2 g LD, 1 g after CPB, 1 g
at 9 hrs &15 hrs after 2nd
dose
1700±205 1551±310 184±20 15±10.3i 53±19i 90j 30j
Cefotaxime
[79]
15 RCT
(peri-operative-liver transplant)
4 1 g LD then 4 g/24 hrs 1 g q6hrs 53±23k 72±21k 43±13 2±2 18±5 100 60
Abbreviation: AUC, area under the concentration-time curve; CI, continuous infusion; Cmax, peak concentrations; Cmin, trough concentrations; ; CPB, cardiopulmonary bypass; CRRT, continuous renal replacement therapy; Css, steady-state concentrations; IB,
intermittent bolus; LD, loading dose; MIC, minimum inhibitory concentration; RCT, randomized controlled trial; VAP, ventilator-associated pneumonia; % fT>MIC, percentage of time (dosing interval) where free (unbound) antibiotic concentration remains
above MIC.
Legend:
aValues are described according to published results as mean (±SD) or median (range).
bLower CI dose used.
cDay 1 AUC0-8.
dDay 1 Cmin.
55
e% of patients achieving 40% fT>MIC.
f4 x MIC.
gAll patients achieved % fT>MIC of 100% except 1 who achieved 92%.
hDay 3.
iAverage concentration at 24 hours.
j% of patients achieving 90% fT>MIC.
kAUC0-8.
56
Below, we will specifically discuss the previously published PK studies comparing the two study
approaches in specific populations. The issues identified relating to different PK/PD targets are
relevant to some of the studies depicted below.
3.2.4.1.1 Critically ill
Critically ill patients have been the focus of many studies (Table 3-1) as they are postulated to be
likely to benefit most from the PK/PD advantages of CI [82, 85, 86, 173, 193, 247, 253, 254, 363,
367]. These patients commonly develop an increased Vd and ARC thus producing low drug
concentrations in the presence of standard dosing [357].
Roberts et al., reported a superior PK/PD profile for piperacillin in an RCT where CI was compared
to IB in 13 critically ill patients with sepsis [85]. Despite a 25% lower dose, the median Cmin on Day
2 of therapy was 16.6 versus 4.9 mg/L for CI and IB respectively (p = 0.007). Langgartner et al.,
observed higher median Css (18.6 mg/L) when meropenem was administered via CI compared to
trough concentrations (8.2 mg/L) provided by IB in 6 critically ill patients who also received CRRT
[253]. De Jongh et al., also reported significantly higher temocillin Css (73 mg/L) in CI compared to
IB (trough concentrations; 28 mg/L) [247]. The authors also added that CI of temocillin achieved a
plasma concentration that is 4 times the MIC of the least susceptible pathogens in the study. Other
studies have described PK/PD advantages in critically ill patients [79, 82, 86, 172, 173, 193, 253,
254, 362, 363].
3.2.4.1.2 Peri-operative non-infected patients
Several studies (Table 3-1) have sought to investigate the PK properties of CI of beta-lactams in
preventing infections after surgical procedures [79, 168, 368]. The majority of these studies support
the PK/PD superiority of CI compared to IB dosing. Adembri et al., described stable serum
cefazolin concentrations with low interpatient variability using CI for antibiotic prophylaxis in
cardiopulmonary bypass surgery [168].
3.2.4.1.3 Cystic fibrosis
Several studies (Table 3-1) have shown PK/PD advantages supporting the use of CI of ceftazidime
in cystic fibrosis patients [364-366, 369]. The idea of administering ceftazidime as CI was proposed
due to the drug’s rapid renal elimination whereby 65% urinary recovery within 2 hours of 50 mg/kg
ceftazidime bolus dose was reported in the sub-population [370]. Hubert et al., performed an RCT
57
to compare the PK properties of ceftazidime administered as either thrice-daily or 24-hour CI in 49
cystic fibrosis patients with acute exacerbation of chronic pulmonary P. aeruginosa infection [365].
The authors found superior concentration-time profile benefits which favoured CI of ceftazidime
whereby the mean Css was significantly higher compared to the Cmin of thrice-daily administration
(CI; 56.2 mg/L versus IB; 12.1 mg/L, p <0.05). Some of the Cmin values were reported to be very
low, even lower than the MIC of the offending pathogens whereas the Css remained constantly
above the MIC throughout CI administration. However, it is unknown if these concentrations were
indeed 4 x MIC to demonstrate maximal antibacterial activity. Riethmueller et al., found higher
mean Css (32 mg/L) of CI compared to Cmin (8.5 mg/L) of thrice-daily administration of ceftazidime
in 56 cystic fibrosis patients with chronic P. aeruginosa infection [364]. The authors described
superior target ceftazidime concentration achievement by CI despite using a lower ceftazidime dose
of 100 mg/kg/day compared to the conventional 200 mg/kg/day in three divided doses. Studies by
Rappaz et al., and Vinks et al., also reported similar findings with a lower ceftazidime dose of 100
mg/kg/day administered as continuous application [366, 371]. Each of the studies reported higher
average steady-state beta-lactams concentrations in CI administration compared to trough
concentrations of IB up to a factor of 4 which is theoretically likely to enable PK/PD superiority in
favour of CI.
3.2.4.1.4 Cancer patients
Comparative studies on CI and IB dosing of beta-lactams in cancer patients are lacking. Most of the
studies that are available have focused on the safety and efficacy of CI in cancer patients without the
inclusion of an IB regimen for comparison [255, 372, 373]. Studies have also supported the notion
of using CI administration in cancer patients based on the postulated superior PK/PD properties
compared to IB dosing as neutropenic patients may develop increased Vd and higher drug CL [255,
372, 373]. More prospective comparative studies are needed in to further describe the clinical
applicability of CI in this sub-population.
3.2.4.1.5 Paediatric population
Studies (Table 3-1) comparing the PK properties of CI and IB in paediatric population are lacking
[366, 372]. Robust prospective comparative studies are warranted in this specific patient group.
58
3.2.4.2 Tissue pharmacokinetics
Antibiotic-bacteria interactions usually occur at the tissue level (e.g., interstitial fluid) thus, any
administration method that could enhance antibiotic penetration into tissues is vital in predicting
response. Significant antibiotic concentration is needed at the target site but most antibiotics are
unevenly partitioned and serum concentration does not always reflect tissue concentrations. Table
3-2 describes the penetration of beta-lactam antibiotics into various tissues when administered via
CI or IB.
Table 3-2: Penetration of beta-lactams into various tissues when administered as continuous or
intermittent administration
Antibiotic Population n Measurement site % Tissue penetration
CI IB
Piperacillina
[277]
Critically ill
septic patients
13 Subcutaneous tissue
(AUCtissue/AUCserum)
21% 20%
Piperacillin/tazobactam
[211]
Critically ill
septic patients
40 ELF 40-50% 57%
Piperacillin/tazobactam
[80]
Critically ill
septic patients
10 ELF - 57%
Meropenem
[86]
Critically ill
septic patients
10 Subcutaneous tissue
(AUCtissue/AUCserum)
89% 74%
Cefotaxime
[79]
Peri-operative
non-infected
patients
15 Bile
(AUCbile/AUCserum)
90% 80%
Ceftazidime
[82]
Peri-operative
infected
patients
18 Peritoneal exudate
(AUCexudate/AUCserum)
56% 35%
Abbreviation: AUC, area under the concentration-time curve; CI, continuous infusion; ELF,
epithelial lining fluid; IB, intermittent bolus.
Legend:
aLower CI dose used.
Roberts et al., found similar plasma and tissue PK of piperacillin when administered by IB or CI
[85]. However, the RCT also described higher PD targets attainment by CI despite utilizing 25%
smaller dose compared to IB. The authors also added that the clinical significance of this difference
is only important in pathogens with high MICs (2 or 4 mg/L). In a prospective comparative study,
Boselli et al., sought to investigate plasma and alveolar PK of piperacillin/tazobactam administered
via CI in critically ill patients with VAP and various degrees of renal impairment [211]. The authors
59
reported large variability in the drug’s concentrations with an alveolar percentage penetration of 40-
50% and 65-85% for piperacillin and tazobactam respectively. It is interesting to note that in
patients with no/mild renal impairment, a CI daily dose of piperacillin/tazobactam 16/2 g achieved
the alveolar target concentration which was not observed with 12/1.5 g per day. In this study, it was
postulated that the latter dosing regimen in patients with no/mild renal impairment might produce
inadequate antibiotic concentration in epithelial lining fluid (ELF) in patients with VAP caused by
pathogens with high MICs.
In one RCT involving 10 critically ill septic patients, Roberts et al., reported that CI of meropenem
maintains higher median Cmin compared to IB, in both plasma (CI; 7 mg/L versus IB; 0 mg/L, p =
0.02) and subcutaneous tissue (CI; 4 mg/L versus IB; 0 mg/L, p = 0.02) [86]. The authors also
concluded that CI of meropenem achieves superior cumulative fraction of response (CFR) against
less-susceptible microorganisms (P. aeruginosa and Acinetobacter spp.) in patients without renal
impairment.
3.2.4.3 Clinical outcomes
Although the PK/PD data of beta-lactams support the use of CI, there is little data to confirm that
this results in improved clinical outcomes. The published data on comparative clinical outcomes is
scarce and insufficient to support a global practice change from conventional IB to CI. Lack of
significance in the published results are likely to be due to the use of study designs that were not
sufficient to explore the effect of both dosing approaches on clinical outcomes as well as the
consistent, small sample sizes that resulted in insufficient power. Further to this, a single therapeutic
intervention in a critically ill setting rarely influences mortality and clinical cure in the setting of a
study [264].
Another possible contributor to a lack of clinical differences being measured between the methods
of administration is that treatment of infections caused by highly susceptible pathogens will always
result in similar outcomes for IB and CI. This is because even a low Cmin achieved during IB is still
likely to exceed the MIC for a sufficient period of each dosing interval. If studies include many
patients with highly susceptible pathogens, then the sample size required to show differences
between the respective dosing methods increases dramatically. For less susceptible organisms, the
likelihood of achieving target concentrations is less likely may risk therapeutic failure.
60
Below, we discuss the published clinical outcome data that have been reported in specific patient
populations.
3.2.4.3.1 Mortality
Several studies, mostly in critically ill patients, have sought to evaluate the mortality outcome
produced by beta-lactams administered via CI or IB (Table 5-3) [151, 172, 243, 248, 256, 274,
298]. It is important to note that the number of RCTs in this area is limited and these trials described
no significant mortality benefits achieved by either administration methods. The problem lies in the
fact that many studies are underpowered and the mortality is often studied as a secondary end-point.
A retrospective cohort study by Lorente et al., revealed similar mortality rate in 83 VAP patients
receiving either IB or CI of piperacillin/tazobactam (IB; 30.5% versus CI; 21.6%, p = 0.46) [274].
Another non-randomized study that’s worth a mention is by Lodise et al., where they reported a
significant lower 14-day mortality rate in patients with an APACHE II score ≥17 favouring EI
compared to IB of piperacillin/tazobactam in critically ill patients infected with P. aeruginosa (IB;
31.6% versus CI; 12.2%, p = 0.04) [298]. Intention-to-treat (ITT) analysis of an RCT by Roberts et
al., found no significant difference in the mortality rate of 57 ICU patients (CI; 10% versus IB; 0%,
p = 0.25) [243]. A recent systematic review of 14 randomized controlled trials performed by
Roberts et al., reported that CI of beta-lactams were not associated with a significant improvement
in mortality rate (odds ratio [OR]: 1.00, 95% confidence interval: 0.48-2.06, p = 1.00, I2 = 14.8%)
[217].
Hughes et al., compared 30-day mortality rate in patients receiving CI or IB of oxacillin for the
treatment of infective endocarditis caused by Methicillin-susceptible Staphylococcus aureus
(MSSA) [374]. The two groups were similar with respect to mortality rate (CI; 8% versus IB; 10%,
p = 0.7) whether synergistic gentamicin (11%) was or not added (5%) into the studied regimen (p =
0.2).
3.2.4.3.2 Clinical cure
Lorente et al., also compared the clinical cure rate in 83 VAP patients receiving either CI or IB of
piperacillin/tazobactam [274]. CI was associated with greater clinical cure rate (CI; 89.2% versus
IB; 56.5%, p = 0.001) and regression analysis further showed higher clinical cure of VAP by CI
when the offending pathogen had a MIC of 8 mg/L or 16 mg/L. A priori analysis by Roberts et al.,
found significant advantage favouring CI of ceftriaxone compared to IB administration in critically
ill septic patients receiving at least 4 days of therapy [243]. The authors also reported that low
61
APACHE II score was predictive of clinical cure. However, the systematic review by Roberts et al.,
found that the use of CI of a beta-lactam antibiotic was not associated with an improvement with
clinical cure rate (OR: 1.04, 95% confidence interval: 0.74-1.46, p = 0.83, I2 = 0%) [217]. Again,
the number of RCTs (Table 2-3) investigating this outcome is limited and most of them were
underpowered [172, 243, 255-257, 266, 274, 375].
The clinical utility of CI and IB in cystic fibrosis have been compared in several studies [364-366].
These studies reported similar clinical outcomes. These studies have also compared patient
improvements in pulmonary, inflammatory and nutritional parameters in both methods after
antibiotic administration. However, these improvements were short-lived and patients frequently
returned to pre-treatment values after cessation of therapy.
Riethmueller et al., compared anti-infectious properties of CI and thrice-daily administration of
ceftazidime in 56 cystic fibrosis patients in a randomized crossover study [364]. The authors found
no significant difference between the two methods in terms of decrease in leukocyte counts,
clinical, lung function and inflammatory parameters. Another randomized crossover study by
Rappaz et al., had similar findings where CI of ceftazidime produced better pulmonary,
inflammatory and nutritional improvements compared to IB [366]. However, the only significant
improvement was in pre-albumin concentration. Hubert et al. reported similar improvements in
forced expiratory volume in 1 second (FEV1) values between the two administration methods but
the benefit of CI was seen in patients with resistant P. aeruginosa isolates (p <0.05) [365]. The
interval between the next antibiotic administration was longer in CI compared to short infusion of
ceftazidime in cystic fibrosis patients (p = 0.04).
Van Zanten et al., reported similar clinical success rates in patients with acute exacerbations of
COPD receiving either CI or thrice-daily administration of cefotaxime [257]. Clinical cure was
achieved in 37/40 (93%) and 40/43 (93%) patients in the CI and IB dosing group respectively (p =
0.93). Bodey et al., randomized cancer patients with febrile neutropenia to receive either CI or IB of
cefamandole with carbenicillin [255]. Although no difference in clinical outcome was reported, a
sub-analysis result revealed that CI administration in comparison to IB produced clinical benefits in
patients with severe persistent neutropenia (CI; 65% versus IB; 21%, p = 0.03).
62
3.2.4.3.3 Severity of Illness
The rate of resolution of infection as described by improvements in the level of severity of illness in
critically ill patients has been used as a comparative index in some studies. In a study of 40
critically ill septic patients by Rafati et al., reduction in APACHE II scores was faster in a CI
compared to an IB group [248]. Significant difference in reduction of score was reported on Days 2,
3 and 4 of treatment.
3.2.4.3.4 Fever resolution/white blood cell normalization
Most studies (Table 3-3) that have investigated fever resolution or WCC normalization between
patients receiving CI or IB of beta-lactam antibiotics have found similar results [248, 254, 266, 364,
374]. However, an RCT by Nicolau et al., reported shorter defervescence time with CI compared to
IB of ceftazidime in 35 critically ill septic patients (CI; 3.1±2.1 days versus IB; 5.2±2.3 days, p =
0.015) [266]. Hughes et al., reported similar defervescence time in 107 patients with infective
endocarditis receiving either CI or IB dosing of oxacillin (CI; 3 days versus IB; 3 days, p = 0.8)
[374]. However, it is interesting to note that defervescence time was significantly different when
synergistic gentamicin was added, favouring the group without gentamicin addition.
Riethmueller et al., found a decrease in WCC favouring CI of ceftazidime in cystic fibrosis patients
[364]. However, the differences obtained in the randomized crossover study were insignificant
when compared to IB (CI; -2216 versus IB; 2209, p = 0.98).
3.2.4.3.5 Mechanical ventilation
The duration of mechanical ventilation has been compared in several studies (Table 3-3), mostly in
critically ill septic population but without significant differences favouring neither IB nor CI
method [172, 243, 254, 274, 375]. Roberts et al., postulated that as the duration of mechanical
ventilation is quite long, other confounding factors may influence the ventilation time in critically
ill patients [264].
3.2.4.3.6 Length of ICU/hospital stay
To date, no significant difference has been reported in length of hospital [243, 254, 298, 374, 375]
or ICU stay [172, 243, 254, 266, 274, 375] between patients receiving CI or IB of beta-lactam
antibiotics (Table 3-3). Studies are often underpowered to detect any significant difference and the
63
studied outcome is usually confounded by several factors other than the intervention given [264].
Whilst the data that describes the effect of CI on length of stay, data from studies which examined
the use of EI are worthy of noting. Among them is a retrospective cohort study by Lodise et al., who
reported a significant shorter hospital stay favouring EI of piperacillin/tazobactam compared to IB
in critically ill patients with P. aeruginosa infections (EI; 21 days versus IB; 38 days, p = 0.02)
[298].
3.2.4.3.7 Adverse events
Several studies (Table 3-3) have compared adverse events from CI and bolus administration of beta-
lactams, although no significant differences are evident [193, 256, 363-365, 375]. Interestingly,
some studies have reported no adverse events [193, 363, 364] while others have made multiple
identifications [256, 365, 375]. Hubert et al., reported 124 adverse events in a randomized crossover
study comparing the safety and efficacy of the two antibiotic protocols in a cystic fibrosis
population [365]. Fifty-six and 68 adverse events were reported during CI and IB respectively in the
study. However, only 2 were considered as severe (one in CI and one in IB) and the majority of the
adverse events were gastrointestinal related.
3.2.4.4 Other considerations
3.2.4.4.1 Stability Issues
Increasing the % fT>MIC for beta-lactams has been associated with increased therapeutic efficacy
and delaying the emergence of resistance and these benefits can be achieved with CI method.
However, carbapenems such as meropenem may be unsuitable for administration via CI due to
stability issues [284]. Meropenem is only stable for 8-12 hours at room temperature thus casting
doubts on any potential benefit of continuous delivery. This is still an important issue in tropical
countries where meropenem concentrations decreased by 4% and 12% when stored at room
temperature for 3 and 8 hours respectively [376] although 24-hour stability can be maintained if
meropenem’s temperature is kept below 4°C [369]. In tropical countries, EI (3-hour infusion) may
be a useful alternative to CI as it is still likely to produce superior PK/PD end-points compared to
IB dosing [376].
64
Table 3-3: Clinical outcome data for patients receiving bolus or continuous infusion/extended-dosing of beta-lactam antibiotics
Drug Population Study Clinical Outcome
Measure
CI IB Result
Cefepime
[172]
Critically ill, Gram-negative
infection
(n = 50)
RCT Mortality 12% 13% NS
Clinical cure 85% 67% NS
Duration of MV 24 ± 13 days 25.3 ± 10 days NS
LOS ICU 34 ± 17 days 40 ± 15 days NS
Ceftazidime
[254]
Trauma patients, NP
(n = 35)
RCT Duration of MV 22.9 ± 19.9 days 13.3 ± 6.1 days NS
LOS Hospital 41.7 ± 30.5 days 28.7 ± 15.9 days NS
LOS ICU 26.8 ± 20.1 days 15.5 ± 5.9 days NS
Duration of leucocytosis 7.8 ± 7.3 days 11.3 ± 4.7 days NS
Duration of pyrexia 7.9 ± 4.4 days 4.3 ± 4.7 days NS
Meropenem
[193]
Severe infection
(n = 15)
Randomized,
crossover
Adverse events None None NS
Ceftazidime
[363]
Critically ill, Gram-negative
infections
(n = 12)
Randomized,
crossover
Adverse events None None NS
Ceftazidime
[364]
Cystic fibrosis
(n = 56)
Randomized,
crossover
Decrease in WCC -2216 ± 2689 -2209 ± 3710 NS
Adverse events None None NS
Ceftazidime
[365]
Cystic fibrosis
(n = 49)
Randomized,
crossover
Change in FEV1 +7.6% +5.5% NS
Adverse events 1 severe event 1 severe event NS
Ceftazidime
[366]
Cystic fibrosis
(n = 14)
Randomized,
crossover
Pre-albumin
improvement
+0.11 +0.08 p =0.015
Cefamandole
[255]
Malignant disease with neutropenia
(n = 164)
RCT Clinical cure 64.8% 56.5% NS
Ceftriaxone Sepsis RCT Mortality 10% 0% NS
65
[243] (n = 57) Duration of MV 4.3 ± 4.5 days 3.4 ± 4.1 days NS
Clinical cure (a priori) 52% 20% p <0.04
LOS Hospital 42 ± 6.9 days 24 ± 2.1 days NS
LOS ICU 10.8 ± 23.2 days 5.6 ± 6.0 days NS
Piperacillin
[248]
Critically ill patients, septicaemia
(n = 40)
RCT Mortality 30% 25% NS
Decrease in illness
severity
CI>IBa
Duration of pyrexia 2.4 ± 1.5 days 1.7 ± 0.7 days NS
WBC normalization 75% 83% NS
Pip-Tazo
[256]
Intra-abdominal infections
(n = 258)
RCT Mortality 0.76% 2.6% NS
Clinical cure 86.4% 88.4% NS
Adverse events 89.2% 87.1% NS
Ceftazidime
[151]
Septicaemic melioidosis
(n = 21)
RCT Mortality 20% 36.4% NS
Pip-Tazo
[274]
VAP, Gram-negative bacilli
(n = 83)
Retrospective,
cohort
Clinical cure 89.2% 56.5% p = 0.001
Mortality 21.6% 30.4% NS
Duration of MV 18.0 ± 10.2 days 21.7 ± 18.1 days NS
LOS ICU 21.8 ± 12.3 days 25.6 ± 19.8 days NS
Pip-Tazo
[298]
P. aeruginosa, critically ill
(n = 194)
Retrospective,
cohort
Mortality 12.2% (EI) 31.6% p = 0.04
LOS Hospital 21 days (EI) 38 days p = 0.02
Oxacillin
[374]
Infective endocarditis
(n = 107)
Retrospective,
cohort
Mortality 8% 10% NS
LOS Hospital 20 days 25 days NS
Time to defervescence 3 days 3 days NS
Ceftazidime
[266]
NP, critically ill
(n = 35)
RCT Clinical cure 41% 33% NS
Duration of MV 7.9 ± 4.0 days 8.3 ± 4.3 days NS
LOS ICU 8.5 ± 3.4 days 9.3 ± 4.0 days NS
66
Time to defervescence 3.1 ± 2.1 days 5.2 ± 2.3 days p = 0.015
WBC normalization 7.3 ± 3.0 x 109/l 5.5 ± 4.2 x 109/l NS
Ceftazidime
[375]
NP, critically ill
(n = 35)
RCT Clinical cure 41% 33% NS
LOS 11.8 ± 6.3 days 15.3 ± 9.6 days NS
Adverse events 9 13 NS
Cefotaxime
[257]
COPD
(n = 83)
RCT Clinical cure 93%
93% NS
Abbreviation: CI, continuous infusion; COPD, chronic obstructive pulmonary disorder; EI, extended-infusion; IB, intermittent bolus; ICU, intensive
care unit; LOS, length of stay; MV, mechanical ventilation; NP, nosocomial pneumonia; NS, non-significant; Pip-Tazo, piperacillin/tazobactam;
RCT, randomized controlled trial; VAP, ventilator-associated pneumonia; WCC, white cell counts.
Legend:
Significant difference in APACHE II scores on Days 2, 3 and 4.
67
3.2.5 Conclusions
Based on the data presented in this chapter, CI of beta-lactams may be meritorious. All of the
present pre-clinical and PK/PD simulation data supports CI. The available clinical data suggests that
CI and IB are associated with similar outcomes, even with the use of lower daily doses in CI. To
date, no data has conclusively shown any superiority of CI in terms of clinical outcomes, although
this is largely because existing studies were underpowered and unable to detect any significant
difference between the two approaches. Similarly, no data has ever demonstrated inferiority of CI
compared with IB. The available data in this chapter supports the undertaking of large scale
prospective clinical outcome studies, particularly in critically ill or immunocompromised patients to
confirm if these apparent advantages, do indeed translate into clinical superiority of CI.
68
3.3 Conclusion
Based on the published literatures that were presented in this chapter, it can be deduced that CI
administration of beta-lactam antibiotics will not be meritorious to all critically ill patients but may
potentially be advantageous to specific subset of patients with severe infections. Although all of the
present in vitro and PK/PD data supports CI administration, the current evidence also suggest
neither superiority nor inferiority of the approach compared to IB administration in terms of clinical
outcomes. Thus, the available data supports the undertaking of large-scale prospective clinical
outcome studies, particularly in patients with severe infections to confirm if these compelling
PK/PD advantages, do translate into clinical superiority favouring CI administration.
69
Chapter 4: Prolonged beta-lactam infusion in critically ill patients: a post
hoc analysis on a large dataset of critically ill patients
4.1 Synopsis
Sepsis remains one of the major problems for patients in the ICU. Given the intrinsic relationship
between infection and sepsis, optimizing antibiotic therapy has been suggested as one of the
approaches by which clinical outcomes in critically ill patients can be improved. However, optimal
antibiotic administration is not straightforward as critically ill patients may develop extreme PK
derangements that alter the exposure of the prescribed antibiotic. It is highly likely that
conventional antibiotic dosing does not account for these PK derangements and this may
consequently lead to therapeutic failure. Aiming to improve antibiotic treatment in the ICU, the
DALI study, a large multinational, PK point prevalence study, was undertaken to describe whether
conventional dosing of beta-lactam antibiotics attains drug concentrations associated with
therapeutic benefits in critically ill patients. The DALI study concluded that different dosing
approaches are required in critically ill patients as compared to non-critically ill patients, to ensure
optimal antibiotic exposures are achieved that can increase the opportunity for clinical success.
However, this large dataset of critically ill patients were not specifically analysed to investigate the
potential benefits of altered beta-lactam dosing in such patient population. Therefore, using the
database of the DALI study, this chapter aims to compare the PK/PD target attainment and clinical
outcomes between PI (i.e., CI and EI) and IB dosing of beta-lactam antibiotics in a large cohort of
critically ill patients. Additionally, the patient sub-groups who are most likely to benefit from
altered dosing approaches were also explored in this post hoc analysis.
70
4.2 Manuscript entitled “Is prolonged infusion of piperacillin/tazobactam and
meropenem in critically ill patients associated with improved
pharmacokinetic/pharmacodynamic and patient outcomes? An observation
from the Defining Antibiotic Levels in Intensive care unit patients (DALI)
cohort”
The manuscript entitled “Is prolonged infusion of piperacillin/tazobactam and meropenem in
critically ill patients associated with improved pharmacokinetic/pharmacodynamic and patient
outcomes? An observation from the Defining Antibiotic Levels in Intensive care unit patients
(DALI) cohort” has been accepted for publication in the Journal of Antimicrobial Chemotherapy
(2016; 71(1): 196-207).
The co-authors contributed to the manuscript as follows: Conception and development of the study
design was performed by Prof. Jason A. Roberts and Prof. Jeffrey Lipman. Literature review was
performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz, under the guidance of Prof. Jason A.
Roberts, Prof. Jan J. De Waele and Prof. Jordi Rello. Data collection was performed by Dr. Murat
Akova, Prof. Matteo Bassetti, Prof. Jan J. De Waele, Dr. George Dimopoulos, Dr. Kirsi-Maija
Kaukonen, Dr. Despoina Koulenti, Prof. Claude Martin, Prof. Philippe Montravers, Prof. Jordi
Rello, Prof. Andrew Rhodes and Therese Starr. Sample bioanalysis was performed by the PhD
candidate, Mohd-Hafiz Abdul-Aziz, under the guidance of Dr. Steven C. Wallis. Data analysis was
performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz, under the guidance of Prof. Jason A.
Roberts and Dr. Joel M. Dulhunty. The PhD candidate took the leading role in manuscript
preparation and all co-authors reviewed and contributed to the final draft of the manuscript.
The accepted version of this manuscript is presented and incorporated in this chapter. However,
some text, tables and figures may have been inserted at slightly different positions to fit the overall
style of the thesis. Numbering of pages, tables and figures may also change to fit the thesis
requirements. Manuscript references have been collated with all other references in the thesis.
Permission has been granted by the publisher and copyright owner, Oxford University Press
(License no: 3886910071822), to reproduce the manuscript in this Thesis.
71
Is prolonged infusion of piperacillin/tazobactam and meropenem in critically ill patients
associated with improved pharmacokinetic/pharmacodynamic and patient outcomes? An
observation from the Defining Antibiotic Levels in Intensive care unit patients (DALI) cohort
Authors
Mohd H. Abdul-Aziz (1), Jeffrey Lipman (1, 2), Murat Akova (3), Matteo Bassetti (4), Jan J. De
Waele (5), George Dimopoulos (6), Joel Dulhunty (1, 2), Kirsi-Maija Kaukonen (7), Despoina
Koulenti (1, 6), Claude Martin (8, 9), Philippe Montravers (10), Jordi Rello (11), Andrew Rhodes
(12), Therese Starr (2), Steven C. Wallis (1), Jason A. Roberts (1, 2), DALI Study Authors†
Affiliations
(1) Burns Trauma and Critical Care Research Centre, The University of Queensland, Brisbane,
Australia.
(2) Royal Brisbane and Women’s Hospital, Brisbane, Australia.
(3) Hacettepe University, School of Medicine, Ankara, Turkey.
(4) Azienda Ospedaliera Universitaria Santa Maria della Misericordia, Udine, Italy.
(5) Ghent University Hospital, Ghent, Belgium.
(6) Attikon University Hospital, Athens, Greece.
(7) Helsinki University Central Hospital, Helsinki, Finland.
(8) Hospital Nord, Marseille, France.
(9) AzuRea Group, Paris, France.
(10) Centre Hospitalier Universitaire Bichat-Claude Bernard, AP-HP, Université Paris VII, Paris,
France.
(11) CIBERES, Vall d'Hebron Institut of Research, Universitat Autonoma de Barcelona, Barcelona,
Spain.
(12) St. George’s Healthcare NHS Trust and St. George’s University of London, London, England.
†All members of the DALI Study group are listed in the Acknowledgements section.
Running title: prolonged infusion vs. intermittent bolus dosing.
Keywords: antibiotic; beta-lactam; continuous infusion; extended infusion; bolus dosing;
pharmacokinetics, pharmacodynamics.
72
Address for correspondence:
Prof. Jason A. Roberts,
Burns Trauma & Critical Care Research Centre, The University of Queensland,
Level 3 Ned Hanlon Building, Royal Brisbane and Women’s Hospital,
Butterfield St, Brisbane, Queensland, Australia 4029
73
4.2.1 Abstract
4.2.1.1 Objectives
We utilized the database of the DALI study to statistically compare the PK/PD and clinical
outcomes between PI and IB dosing of piperacillin/tazobactam and meropenem in critically ill
patients using inclusion criteria similar to those used in previous prospective studies.
4.2.1.2 Methods
This was a post-hoc analysis of a prospective, multicentre PK point-prevalence study (DALI) which
recruited a large cohort of critically ill patients from 68 ICUs across 10 countries.
4.2.1.3 Results
Of the 211 patients receiving piperacillin/tazobactam and meropenem in the DALI study, 182 met
inclusion criteria. Overall, 89.0% (162/182) of patients achieved the most conservative target of
50% fT>MIC. Decreasing CLCR and the use of PI significantly increased the target attainment for
most PK/PD targets. In the sub-group of patients who had respiratory infection, patients receiving
beta-lactams via PI demonstrated significantly better 30-day survival when compared to IB patients
(86.2% [25/29] versus 56.7% [17/30]; p = 0.012). Additionally, in patients with a SOFA score of
≥9, administration by PI compared with IB dosing demonstrated significantly better clinical cure
(73.3% [11/15] versus 35.0% [7/20]; p = 0.035) and survival rates (73.3% [11/15] versus 25.0%
[5/20]; p = 0.025).
4.2.1.4 Conclusions
The analysis of this large dataset provides additional data of the niche benefits of administration of
piperacillin/tazobactam and meropenem by PI in critically ill patients, particularly for patients with
respiratory infections.
74
4.2.2 Introduction
Beta-lactam antibiotics are routinely prescribed for severe infections in the ICU. As time-dependent
antibiotics, the most important PK/PD index for its activity is fT>MIC [11]. IB dosing, the standard
method of beta-lactam administration, commonly produces sub-optimal drug concentrations in
critically ill patients with conserved renal function [86, 165, 169]. Such patients generally exhibit
extreme physiological derangements which may alter the beta-lactam PK and consequently, reduce
its exposure [6, 7]. Numerous PK/PD simulation studies suggest that optimal beta-lactam exposures
are readily obtained via CI or an extended 2 to 4-hour infusion (i.e., EI) [86, 165, 169, 187]. CI and
EI are jointly referred to as PI, with either approach considered to be potentially advantageous
compared to traditional IB administration.
Owing to persisting poor sepsis-related clinical outcomes in the ICU, there has been growing
concerns that conventional antibiotic dosing in critically ill patients is sub-optimal. If this notion is
true, global antibiotic prescribing practices may need to change accordingly. Aiming to improve
antibiotic treatment in the ICU, the DALI study [213], a large multinational, PK point prevalence
study, was undertaken to describe whether conventional dosing of beta-lactam antibiotics attains
drug concentrations associated with therapeutic benefits in critically ill patients. The implications of
the study are profound; 16% of the patients did not achieve the most conservative PK/PD target and
these patients were 32% more likely to demonstrate negative clinical outcomes. Although these data
concluded that different dosing strategies are needed in the ICU, they were not discretely analysed
to ascertain the potential merits of altered beta-lactam infusion in critically ill patients. Of note, with
the exception of piperacillin/tazobactam and meropenem, the other six beta-lactam antibiotics
included in the DALI study were almost exclusively administered by IB dosing, which signifies its
“authority” over PI dosing in current prescribing practices.
Despite compelling pre-clinical and PK/PD data, clinical comparative trials have failed to
demonstrate the perceived clinical advantage of PI over IB dosing [13]. Furthermore, most meta-
analyses of the clinical trials are still indecisive over the notion of PI clinical superiority over IB
dosing [217, 239, 240, 267-271, 377]. There are currently four recent meta-analyses which report
significant improvement in clinical cure [239, 268, 269] and survival [239, 268, 270] favouring PI
administration. However, their findings should be interpreted with caution as these meta-analyses
have included a considerable number of retrospective and non-randomized studies in their pooled
analysis. Given the above uncertainty, we utilized the database of the DALI study with the primary
aim of distinguishing the relative ability of PI and IB dosing of piperacillin/tazobactam and
75
meropenem to achieve specific PK/PD exposure targets in relation to the offending pathogens MIC
during antibiotic therapy. Secondary aims were to describe clinical response and 30-day survival
for both administration approaches and which patient sub-groups were most likely to benefit from
this intervention.
4.2.3 Materials and methods
4.2.3.1 Study design
This is a post-hoc analysis of the DALI study which the detailed study protocol has been described
elsewhere [213, 378]. Briefly, during a single dosing interval on the investigation day, each patient
had two blood samples drawn for the beta-lactams they were receiving (mid-dose and a trough
concentration). Various demographic, clinical and treatment-related variables were collected on the
day of investigation. CLCR was estimated using the Cockcroft-Gault formula [341].
Patients were included if they received either piperacillin/tazobactam or meropenem, which were
administered by PI (either CI or EI) or IB dosing. We followed the inclusion criteria used in
previous randomized clinical trials of this intervention [166, 242, 243], which meant that patients
who received any form of extracorporeal renal support were excluded as patients with reduced drug
clearances are less likely to benefit from altered administration approaches [211, 244, 245]. For
clinical outcome assessment, only patients who received antibiotic for treatment of infection, as
opposed to prophylaxis, were included.
The lead site was The University of Queensland, Australia (ethical approval no. 201100283).
4.2.3.2 Sample integrity and bioanalysis
Blood samples were processed and stored per protocol prior to shipment to the BTCCRC, The
University of Queensland, Australia, where they were assayed. The details concerning bioanalysis
have been described in detailed elsewhere [379].
4.2.3.3 Pharmacokinetic/pharmacodynamic and clinical outcome measures
The primary end-point, which was PK/PD target attainment, is described in detail in Table 4-1.
Briefly, to assess the relative dosing adequacy of PI and IB administration, the observed unbound
antibiotic concentrations were compared against the causative pathogens actual or “surrogate” MIC.
76
The secondary end-points, clinical response and 30-day survival, were assessed using definitions
described in Table 4-1. Additionally, to investigate clinical differences between PI and IB dosing
within the sub-group of patients with the highest illness severity, as described by Lodise et al.,
[298], we performed a Classification and Regression Tree (CART) analysis to further stratify
patients based on SOFA score to identify the patients who were at the greatest risk for clinical
failure and 30-day mortality.
Table 4-1: Definitions used for pharmacokinetic/pharmacodynamic end-points and clinical
outcome variables
Primary PK/PD end-pointsa,b Definition
50% fT>MIC Free drug concentration maintained above the MIC of the
pathogen for at least 50% of dosing interval.
50% fT>4 x MIC Free drug concentration maintained above a concentration four-
times the MIC of the pathogen for at least 50% of dosing
interval.
100% fT>MIC Free drug concentration maintained above the MIC of the
pathogen throughout the dosing interval.
100% fT>4 x MIC Free drug concentration maintained above a concentration four-
times the MIC of the pathogen throughout the dosing interval.
Secondary endpoints Definition and description
Clinical response
Clinical cure Completion of treatment course without change or addition of
antibiotic therapy, and with no additional antibiotics
commenced with 48 hours of cessation.
Clinical failure Any clinical outcome other than clinical cure.
30-day survival Survival at Day 30 following entry to the study.
Abbreviation: PK/PD, pharmacokinetic/pharmacodynamic; MIC, minimum inhibitory
concentration.
Legend:
aThe PK/PD exposure targets have all been identified in clinical studies recruiting critically ill
patients in which achieving these targets would increase the probability of clinical efficacy.
bActual MIC values, provided by the local microbiology laboratory, were used when available.
Where a pathogen was isolated but MIC was unavailable, the “surrogate” MIC was defined by the
EUCAST MIC90 data. Where no pathogen was formally identified, the MIC breakpoints for P.
aeruginosa (16 mg/L for piperacillin/tazobactam and 2 mg/L for meropenem) were inferred as the
“surrogate” MIC, which reflects the least susceptible pathogen that could be encountered during
beta-lactam therapy.
77
4.2.3.4 Statistical analysis
Data are presented as median values with interquartile range (IQR) for continuous variables and
number and percentage for categorical variables. A multivariate logistic regression model (manual
entry and stepwise, backward elimination) was constructed to identify significant predictors
associated with the primary and secondary end-points with OR and 95% confidence interval
reported. Biologically-plausible variables with a p-value of ≤0.15 on univariate analysis were
considered for model building. However, the administered beta-lactam and the method of
administration were forced into the regression models regardless of the univariate analysis results.
Goodness-of-fit was assessed by the Hosmer-Lemeshow statistic. A two-sided p-value of <0.05 was
considered statistically significant in all analyses. Statistical analysis was performed using IBM
SPSS statistic 22 (IBM Corporation, Armonk, New York).
4.2.4 Results
A total of 211 patients received either piperacillin/tazobactam or meropenem and were considered
for study inclusion. Twenty-nine patients were further excluded as they received extracorporeal
renal support during ICU stay. The patient inclusion and exclusion process is depicted in Figure 4-1
and the baseline characteristics for the 182 included patients are presented in Table 4-2. For clinical
outcome assessment, 37 patients who were only receiving antibiotic prophylaxis were further
excluded.
Of the 182 included patients, 110 (60.4%) received piperacillin/tazobactam. Additionally, 60.4%
(110/182) of patients also received concomitant antibiotic therapy as part of their treatment. The
most common administration method was IB where 63.2% (115/182) of the patients received beta-
lactams via this approach. Among the 67 PI patients, 23 (34.3%) and 44 (65.7%) were CI and EI
patients, respectively. Figure 4-2 illustrates the preferred method of dosing by participating country.
Although most countries favoured IB dosing, two countries, Belgium and France, had more than
half of the patients receiving the beta-lactams by PI dosing.
Of 182 patients who received beta-lactams, 70 (38.5%) were prescribed for either presumed or
confirmed respiratory infection. Of the patients treated for infection (n = 145), 114 (78.6%) had at
least one causative pathogen isolated with 40.4% (46/114) of them had actual MIC values for the
causative pathogens identified. The number of patients with actual MIC data were similar between
PI and IB treatment arms (37.5% [18/48] versus 42.4% [28/66], respectively; p = 0.769). The
distribution of the isolated pathogens was similar between the treatment arms and most of the
78
isolates were Gram-negative bacteria (PI 79.2% [38/48] versus IB 80.3% [53/66]; p = 0.881). Of the
114 isolated pathogens, the most prevalent Gram-negative and -positive pathogens were P.
aeruginosa (24/91; 26.4%) and S. aureus (6/23; 26.1%), respectively.
Figure 4-1: Study flowchart demonstrating the number of patients who were included and
excluded in each stage of the planned analysis
79
Table 4-2: Baseline demographics and characteristics
Characteristic All patients
(n = 182)
PI
(n = 67)
IB
(n = 115)
Significance p-
valuea,b
Age (years) 61 (47-74) 56 (47-75) 64 (48-74) 0.417
Male, n (%) 113 (62.1) 44 (65.7) 69 (60.0) 0.447
Weight (kg) 73 (65-84) 73 (64-88) 74 (65-80) 0.646
APACHE II 18 (13-25) 20 (13-26) 18 (14-24) 0.215
SOFA 5 (3-8) 5 (3-8) 5 (3-8) 0.797
Serum creatinine concentration (µmol/L) 71 (52-125) 64 (48-140) 73 (53-119) 0.726
Cockcroft-Gault creatinine clearance (mL/min) 85 (46-131) 95 (42-141) 82 (48-130) 0.510
Pre-ICU hospital stay (days) 2 (1-9) 1 (1-9) 2 (1-9) 0.260
Duration of antibiotic therapy (days) 9 (4-14) 8 (4-13) 9 (4-14) 0.371
Concomitant antibiotics usage, n (%) 110 (60.4) 39 (58.2) 71 (61.7) 0.733
Surgery within 24 hours of antibiotic sampling, n (%) 33 (18.1) 14 (20.9) 19 (16.5) 0.460
Organisms identified, n (%) 121 (66.5) 50 (74.6) 71 (61.7) 0.103
Polymicrobial infection, n (%) 29 (15.9) 11 (16.4) 18 (15.7) 0.577
Primary infection site, n (%)
Respiratory 70 (38.5) 33 (49.3) 37 (32.2) 0.041
Abdominal 50 (27.5) 16 (23.9) 34 (29.6) 0.593
Blood 23 (12.6) 6 (9.0) 17 (14.8) 0.664
Urinary 21 (11.5) 6 (9.0) 15 (13.0) 0.231
Central nervous system 8 (4.4) 4 (6.0) 4 (3.5) 0.639
Others 10 (5.5) 2 (3.0) 8 (7.0) 0.082
Abbreviation: APACHE, Acute Physiology and Chronic Health Evaluation; IB, intermittent bolus; PI, prolonged infusion; SOFA, Sequential Organ
Failure Assessment.
80
*Data are presented as median (interquartile range) or number (percentage).
Legend:
aRepresents the p-value between prolonged infusion versus intermittent bolus dosing and values in bold indicate significant difference between the
two dosing groups (p <0.05).
bLinear variables were compared using Mann-Whitney U test as data were non-normally distributed as were indicated by Kolmogorov-Smirnov test.
Dichotomous variables were compared using Pearson chi-square test or Fisher’s exact test as appropriate.
81
Figure 4-2: Method of piperacillin/tazobactam and meropenem administration according to
participating countries
Abbreviation: IB, intermittent bolus; PI, prolonged infusion.
4.2.4.1 Pharmacokinetic/pharmacodynamic and clinical outcome measures
Overall, 89.0% (162/182) of patients achieved the lower PK/PD target of 50% fT>MIC. For higher
thresholds such as 100% fT>MIC and 100% fT>4xMIC, 63.2% (115/182) and 27.5% (50/182) of
patients, respectively, achieved these PK/PD targets. Although PI patients generally demonstrated
numerically higher target attainment rates as opposed to IB patients across all PK/PD indices, a
statistically significant difference was only observed at 100% fT>MIC; 50% fT>MIC (PI 91.0% [61/67]
versus IB 87.8% [101/115]; p = 0.532; 50% fT>4xMIC (PI 62.7% [42/67] versus IB 49.6% [57/115]; p
= 0.106; 100% fT>MIC (PI 73.1% [49/67] versus IB 57.4% [66/115]; p = 0.045; and 100% fT>4xMIC
(PI 31.3% [21/67] versus IB 25.2% [29/115]; p = 0.357. When only patients with actual MIC data
were analysed, those who received beta-lactams via PI dosing also demonstrated numerically higher
target attainment rates, albeit not statistically significant, compared to IB patients across all PK/PD
indices.
The clinical cure and 30-day survival rate of patients who received antibiotics for treatment of
infection (n = 145) was 73.1% (106/145) and 73.1% (106/145), respectively. Table 4-3 presents the
82
differences in patient characteristics between those who demonstrated positive and negative clinical
outcomes in this study. The clinical outcomes were mostly similar between PI and IB patients
receiving antibiotics for treatment of infection (Figures 4-3 and 4-4). However, in sub-group of
patients who had respiratory infection (n = 59), patients receiving beta-lactams via PI dosing
demonstrated significantly better 30-day survival when compared to IB patients (86.2% [25/29]
versus 56.7% [17/30], respectively; p = 0.012).
Patients who had a SOFA score ≥9 were identified by CART analysis to have the greatest risk for
clinical failure (clinical cure rates were 80.0% [88/110] in patients with a SOFA score <9 versus
51.4% [18/35] in patients with a SOFA score ≥9; p = 0.004) and 30-day mortality (mortality rates
were 18.2% [20/110] in patients with a SOFA score <9 versus 54.3% [19/35] in patients with a
SOFA score ≥9; p = 0.001). In patients with a SOFA score ≥9 (n = 35), patients receiving beta-
lactams via PI dosing demonstrated significantly higher clinical cure (PI 73.3% [11/15] versus IB
35.0% [7/20]; p = 0.035) and 30-day survival rates (PI 73.3% [11/15] versus IB 25.0% [5/20]; p =
0.025).
4.2.4.2 Outcome measures predictors
Based on the most parsimonious model, decreasing CLCR values significantly increased the target
attainment for all PK/PD targets; 50% fT>MIC (OR 0.97; 95% confidence interval 0.98-0.99; p =
0.007); 50% fT>4xMIC (OR 0.97; 95% confidence interval 0.98-0.99; p = 0.014); 100% fT>MIC (OR
0.97; 95% confidence interval 0.98-0.99; p <0.001); and 100% fT>4xMIC (OR 0.97; 95% confidence
interval 0.96-0.98; p <0.001). The use of PI dosing, as opposed to IB dosing, significantly increased
the PTA for 100% fT>MIC (OR 2.78; 95% confidence interval 1.24-6.24; p = 0.013).
The results of all multivariate logistic regression models for clinical cure and 30-day survival are
available in Table 4-4. Based on the most parsimonious logistic regression model, SOFA score (OR
0.89; 95% confidence interval 0.80-0.99; p = 0.029) and concomitant antibiotic use (OR 0.31; 95%
confidence interval 0.10-0.96; p = 0.043) were identified as significant factors associated with
clinical cure whilst only SOFA score (OR 0.82; 95% confidence interval 0.73-0.92; p = 0.001) was
identified as the factor associated with 30-day survival.
83
Table 4-3: Differences in patient characteristics and treatment-related variables between those who demonstrated positive and negative
clinical outcome
Variable Clinical cure Significance
p-valuea,b
30-day survival Significance
p-valuea,b Yes
(n = 106)
No
(n = 39)
Alive
(n = 106)
Deceased
(n = 39)
Age (years) 65 (50-75) 64 (51-79) 0.297 59 (47-74) 65 (56-77) 0.048c
Male, n (%) 67 (63.2) 24 (61.5) 0.929 66 (62.3) 25 (64.1) 0.890
Weight (kg) 73 (63-86) 75 (65-81) 0.927 75 (65-88) 71 (60-76) 0.074c
APACHE II score 19 (15-25) 18 (15-24) 0.643 18 (14-25) 21 (16-24) 0.499
SOFA score 5 (2-7) 7 (4-9) 0.029c 4 (2-7) 7 (4-10) 0.001c
Serum creatinine (µmol/L) 65 (51-144) 87 (53-130) 0.457 64 (48-130) 92 (64-143) 0.101
Cockcroft-Gault CLCR (mL/min) 86 (41-130) 78 (39-131) 0.445 93 (45-147) 59 (36-93) 0.014c
Duration of treatment (days) 9 (5-13) 7 (4-10) 0.030c 10 (5-14) 8 (4-12) 0.217
Pre-ICU hospital stay (days) 2 (1-8) 6 (2-12) 0.005c 2 (1-9) 3 (1-12) 0.046c
Surgery within 24 hours, n (%) 12 (11.3) 6 (15.4) 0.420 14 (13.2) 4 (10.3) 1.000
Culture positive, n (%) 83 (78.3) 31 (79.5) 0.759 85 (80.2) 29 (74.4) 0.387
Gram-negative pathogen, n (%) 61 (73.5) 30 (96.8) 0.036c 64 (75.3) 27 (93.1) 0.039c
Polymicrobial infection, n (%) 16 (19.3) 7 (22.6) 0.536 20 (23.5) 7 (24.1) 0.824
Primary infection site, n (%)
Respiratory 40 (37.7) 19 (48.7) 0.303 42 (39.6) 17 (43.6) 0.591
Abdominal 30 (28.3) 12 (30.8) 0.695 31 (29.2) 11 (28.2) 0.639
Blood 14 (13.2) 5 (12.8) 1.000 13 (12.3) 6 (15.4) 0.542
Urinary 14 (13.2) 0 (0.0) 0.035 11 (10.4) 3 (7.7) 0.515
Central nervous system 4 (3.8) 1 (2.6) 1.000 4 (3.8) 1 (2.6) 1.000
Others 4 (3.8) 2 (5.1) 1.000 5 (4.7) 1 (2.6) 1.000
Beta-lactam antibiotics, n (%)
84
Piperacillin 60 (56.6) 26 (66.7) 0.295c 62 (58.5) 24 (61.5) 0.787
Meropenem 46 (43.4) 13 (33.3) 44 (41.5) 15 (38.5)
Concomitant antibiotics, n (%) 58 (54.7) 32 (82.1) 0.020c 60 (56.6) 30 (76.9) 0.023c
Dosing method, n (%)
Prolonged infusion 44 (41.5) 14 (35.9) 0.641c 47 (44.3) 12 (30.8) 0.156c
Intermittent bolus 62 (58.5) 25 (64.1) 59 (55.7) 27 (69.2)
PK/PD ratiod
50% fT>MIC 7.1 (2.2-13.0) 3.5 (2.1-10.0) 0.097c 5.3 (1.9-11.7) 8.1 (2.9-15.0) 0.383
100% fT>MIC 2.2 (0.6-7.1) 1.7 (0.5-3.1) 0.280 1.7 (0.5-5.3) 3.2 (1.1-7.2) 0.060c
Abbreviation: APACHE, Acute Physiology and Chronic Health Evaluation; CLCR = creatinine clearance; ICU, intensive care unit; MIC, minimum
inhibitory concentration; PK/PD, pharmacokinetic/pharmacodynamic; SOFA, Sequential Organ Failure Assessment.
Legend:
aLinear variables were compared using Mann-Whitney U test as data were non-normally distributed as were indicated by Kolmogorov-Smirnov test.
Dichotomous variables were compared using Pearson chi-square test or Fisher’s exact test as appropriate.
bBold values indicate statistical significance (p <0.05).
cRepresents variable that was included in the multivariate logistic regression model.
dThe pharmacokinetic/pharmacodynamic (PK/PD) ratios observed at 50% and 100% of the dosing interval. These indices were defined as the ratio
between the unbound plasma concentration (either piperacillin/tazobactam or meropenem) at 50% or 100% of the dosing interval and the causative
pathogens MIC. Actual MIC values were used when available. Where MIC was unavailable or no pathogen was formally identified, “surrogate” MIC
values were assumed.
85
Figure 4-3: Clinical cure rates comparison between prolonged infusion and intermittent bolus
dosing for patients who received antibiotics for treatment of infections, stratified according to
sub-groups
Abbreviation: IB, intermittent bolus; n, number; PI, prolonged infusion; SOFA, Sequential Organ
Failure Assessment.
Legend:
An asterisk indicates significant difference between prolonged infusion versus intermittent bolus
dosing (p <0.05).
86
Figure 4-4: Comparison of 30-day survival between prolonged infusion and intermittent bolus
dosing for patients who received antibiotics for treatment of infections, stratified according to
sub-groups.
Abbreviation: IB, intermittent bolus; n, number; PI, prolonged infusion; SOFA, Sequential Organ
Failure Assessment.
Legend:
An asterisk indicates significant difference between prolonged infusion versus intermittent bolus
dosing (p <0.05).
87
Table 4-4: Factors predicting clinical cure and 30-day survival for all patients who received antibiotics for treatment of infections (n =145)
Variable All factors included in the model Final model
Odds ratio
(95% CI)
Significance
(p-value)
Odds ratio
(95% CI)
Significance
(p-value)
Factors predicting clinical cure
SOFA score (per 1-point increase) 0.90 (0.80-1.01) 0.071 0.89 (0.80-0.99) 0.029
Concomitant antibiotic therapya 0.24 (0.07-0.84) 0.025 0.31 (0.10-0.96) 0.043
Duration of antibiotic therapy (per 1-day increase) 1.08 (0.98-1.18) 0.115 - -
Gram-negative pathogenb 0.35 (0.06-1.87) 0.218 - -
50% fT>MICc (per 1-point increase) 1.02 (0.97-1.08) 0.405 - -
Piperacillind 0.84 (0.28-2.46) 0.746 - -
Prolonged infusione 0.86 (0.31-2.43) 0.782 - -
Pre-ICU hospital stay (per 1-day increase) 1.00 (0.97-1.03) 0.966 - -
Goodness-of-fit
Hosmer-Lemeshow test X2 = 6.00, df = 8 0.647 X2 = 8.41, df = 8 0.394
Factors predicting 30-day survival
SOFA score (per 1-point increase) 0.83 (0.73-0.96) 0.009 0.82 (0.73-0.92) 0.001
Concomitant antibiotic therapya 0.24 (0.05-1.04) 0.056 - -
Piperacillind 2.70 (0.86-8.49) 0.090 - -
Age (per 1-year increase) 0.96 (0.92-1.01) 0.099 - -
Weight (per 1-kg increase) 1.03 (0.99-1.07) 0.119 - -
Gram-negative pathogenb 0.32 (0.05-2.05) 0.228 - -
Pre-ICU hospital stay (per 1-day increase) 0.98 (0.95-1.01) 0.232 - -
Estimated Cockcroft-Gault CLCR (per mL/min) 1.00 (0.99-1.01) 0.675 - -
88
Prolonged infusione 1.10 (0.33-3.67) 0.878 - -
100% fT>MICf (per 1-point increase) 1.00 (0.92-1.08) 0.960 - -
Goodness-of-fit
Hosmer-Lemeshow test X2 = 6.57, df = 8 0.584 X2 = 5.05, df = 8 0.751
Abbreviation: CI, confidence interval; CLCR, creatinine clearance; df, degree of freedom; MIC, minimum inhibitory concentration; SOFA, Sequential
Organ Failure Assessment; X2 = chi-square.
*When available, actual MIC values were used.
**Dashes indicate there was no variable output in the model.
Legend:
aOdds ratio compares concomitant antibiotic therapy relative to antibiotic monotherapy.
bOdds ratio compares Gram-negative relative to Gram-positive pathogens.
cThe ratio between the unbound plasma concentration (either piperacillin or meropenem) at 50% of the dosing interval and the causative pathogens
MIC (actual or assumed values).
dOdds ratio compares piperacillin relative to meropenem.
eOdds ratio compares prolonged infusion relative to intermittent bolus dosing.
fThe ratio between the unbound plasma concentration (either piperacillin or meropenem) at 100% of the dosing interval and the causative pathogens
MIC (actual or assumed values).
89
4.2.5 Discussion
Altered beta-lactam PK is widely reported among ICU patients, potentially leading to suboptimal
antibiotic exposures when “standard” beta-lactam dosing is applied in the cohort [6, 7, 56]. In this
study, the majority of patients achieved a lower PK/PD target of 50% fT>MIC and the attainment
rates were similarly high across the two administration methods and antibiotics. However, clinical
data from critically ill patients have suggested that such exposure should be regarded as the
minimum, with larger exposures associated with improved outcomes [5, 20, 21, 28]. A more
prudent target of 100% fT>MIC should be considered and this was not achieved by one-third of the
study patients. Nonetheless, the patients in this cohort were three-times more likely to achieve
100% fT>MIC when receiving beta-lactams via PI dosing (OR 2.78; 95% confidence interval 1.24-
6.24; p = 0.013). Although such an observation was anticipated, our current work remains unique
given that the data were derived from a broad range of ICU environment across 10 countries and the
strength of association was established and supported by multivariate regression analyses.
As the beta-lactams are predominantly cleared by the kidney, elevated renal function as observed in
ARC may likely lead to suboptimal PK/PD target attainment [117, 120, 121]. In our cohort,
increasing values of the estimated CLCR significantly reduced the probability of target attainment
for all PK/PD indices. Moreover, the observed relationship between CLCR and sub-optimal PK/PD
exposure was relatively strong in both univariate and multivariate analysis for all PK/PD indices.
The probability of attaining 100% fT>MIC would be reduced by 3% with every 1 mL/min increase in
the estimated CLCR (OR 0.97; 95% confidence interval 0.98-0.99; p <0.001). The median CLCR of
patients who did not attain 100% fT>MIC was 132 mL/min and only 28.2% (11/39) of those with a
CLCR ≥132 mL/min achieved the target. Such patients who are at-risk, usually in those with
apparently “normal” renal function, need to be identified early so that appropriate dose modification
can occur. Young trauma patients (<60 years), without significant organ dysfunction (SOFA ≤4)
[109, 353], were more likely to develop ARC and these factors were also evident in our patients
who manifested elevated CLCR; median age was 45 (IQR: 35-57) and median SOFA was 4 (IQR: 2-
7).
The significance of illness severity for clinical outcome is also highlighted in this study. In this
context, higher SOFA scores were independently associated with greater likelihood of developing
clinical failure and death at 30-days post antibiotic sampling. An increase in SOFA score by 1-point
reduced the probability of clinical cure and survival by 11.0% and 18.0%, respectively (Table 4-4).
Accordingly, we also observed that patients with a SOFA score ≥9 were more likely to demonstrate
90
negative clinical outcomes and when only these patients were tested, those receiving beta-lactams
via PI dosing demonstrated significantly better outcomes as opposed to IB dosing (Figures 4-3 and
4-4). Higher survival rates favouring PI dosing were also seen in sub-group of patients with
respiratory infection and our finding further substantiate similar claims of earlier studies which
suggested potential benefits of PI administration in severely-ill patients with pneumonia [274, 275,
290]. As inappropriate antibiotic treatment has been associated with reduced survival in patients
with severe pneumonia [20, 21, 31, 380], prompt antibiotic administration, with an optimal dosing
schedule, is therefore an essential intervention in this population. In this respect, the application of
PI dosing could be meritorious by enhancing beta-lactam penetration into the interstitial fluid of the
infected lung tissues [85, 141, 211], where the antibiotic-bacteria interactions occur [77].
Furthermore, optimal antibiotic dosing is crucial in this population as it may be directly linked with
patient outcomes [381, 382], whilst for other infection sites such as intra-abdominal and surgical-
site infections, effective source control and the role of the surgeons are probably more crucial in
predicting positive outcomes.
However, it is also important to mention that the sample size of patients in these two sub-groups
was relatively small compared to the clinically evaluable patients (<60 versus 145, respectively)
and thus, the observed statistical significance could have been the result of random chance, although
they do agree with previous published data [298]. Furthermore, due to the relatively small number
of patients in the two sub-groups, logistic regression analyses could not be performed and therefore,
the clinical benefits of PI were concluded based on unadjusted analyses which does not consider the
influence of potential confounders. Hence, it is important to highlight the median pre-ICU days for
PI patients in the two sub-groups were significantly shorter compared to IB patients (PI 2; IQR: 1-8
versus IB 7; IQR: 2-12; p = 0.039), and the large difference might skew the results in favour of PI.
Indeed, our clinical findings provide further evidence that PI dosing of beta-lactam antibiotics may
not be beneficial for all but rather a specific subset of critically ill patients with severe infections.
Interestingly, no sub-group has worse outcomes with PI dosing, suggesting that widespread use of
such an intervention is not likely to have an inferior effect compared with the current standard
practice. We believe that this study generates an interesting “therapeutic” signal, signifying
potential clinical superiority of PI dosing in patients with higher SOFA scores and in patients with
respiratory infections. Accordingly, future clinical studies should focus and test the hypotheses
specifically in these patient groups. As what has been demonstrated by a recent RCT, Dulhunty et
al., [166] showed that CI demonstrated better PK/PD and clinical outcomes when compared to IB
dosing and these findings may stem from the strategic approach of only recruiting patients with a
higher acuity of illness and in patients not receiving RRT.
91
In this study, concomitant antibiotic therapy also reduced the probability of clinical cure by 69.0%
(Table 4-4). Although the reasons were unclear, we hypothesize that the more severely-ill the
patient was, the more likely for the patient to receive multiple antibiotics in an attempt to “reverse”
the impending poor prognosis associated with such patients. Our notion was corroborated by the
higher median SOFA score observed in patients who received concomitant antibiotics compared to
those who did not (6; IQR: 3-9 versus 4; IQR: 1-7, respectively; p = 0.048). Whilst data on
concomitant antibiotics were available, we did not specifically evaluate their duration of therapy
and also assess the PK/PD of those antibiotics, all of which could have confounded the findings in
this study.
This study has several limitations we would like to declare. It is imperative to clarify that in 60% of
the patients, “surrogate” MIC values were assumed from population estimates and such approach
could markedly inflate, or even deflate, the magnitudes of PK/PD target non-attainment observed in
this study. In addition, this approach would adversely affect the target attainment rates of IB
patients more than the PI patients if the “surrogate” MIC values were indeed higher than the actual
MIC values. However, when we employed actual MIC data in our analysis, the findings were
consistent with our main approach where PI patients demonstrated numerically higher target
attainment rates, albeit not statistically significant, compared to IB patients across all PK/PD
indices. Actual MIC values would have been preferable although we believe that our present
approach closely “mimics” the real-life clinical approach where the MIC of a pathogen is rarely
available upon antibiotic treatment initiation. We also acknowledge the limitation of Cockcroft-
Gault formula in estimating the measures of renal function in this cohort and measured CLCR would
be more appropriate, particularly in patients with ARC. The post hoc nature of this analysis also
limits our ability to establish a causal relationship between the methods of beta-lactam
administration and clinical outcomes. As the antibiotic dosing regimen and all subsequent patient
management was at the discretion of the treating physician, this might have introduced potential
bias towards a better patient management among PI patients in this study.
4.2.6 Conclusion
This study provides additional PK/PD and clinical outcome data to support the practice of
administration of piperacillin/tazobactam and meropenem by PI in critically ill patients, particularly
for patients with respiratory infections. However, future clinical studies should focus and test the
potential clinical superiority of the altered beta-lactam dosing approaches in a specific subset of
critically ill patients with severe infections and that are not receiving RRT.
92
4.2.7 Acknowledgements
4.2.7.1 Authors’ Contribution
MHAA drafted the manuscript, had full access to the data and took responsibility for the integrity of
the data and the accuracy of the data analysis. JAR and JL designed the study and wrote the initial
protocol. MHAA and JD performed the statistical analysis. JL, MA, MB, JDW, GD, KMK, DK,
CM, PM, JR, AR, TS and JAR helped conduct the trial. All authors provided input into the
interpretation of the data and critical revision of the manuscript for important intellectual content.
4.2.7.2 Members of the DALI Study group
Author name Affiliation
Jason A Roberts Burns Trauma and Critical Care Research Centre, The University of
Queensland, Brisbane, Australia;
Royal Brisbane and Women’s Hospital, Brisbane, Australia
Jeffrey Lipman Burns Trauma and Critical Care Research Centre, The University of
Queensland, Brisbane, Australia;
Royal Brisbane and Women’s Hospital, Brisbane, Australia
Therese Starr Royal Brisbane and Women’s Hospital, Brisbane, Australia
Steven C Wallis Burns Trauma and Critical Care Research Centre, The University of
Queensland, Brisbane, Australia
Sanjoy Paul Queensland Clinical Trials & Biostatistics Centre, School of
Population Health, The University of Queensland,
Brisbane, Australia
Antonio Margarit Ribas Hospital Nostra Senyora de Meritxell, Escaldes-Engordany, Andorra
Jan J. De Waele Ghent University Hospital, Ghent, Belgium
Luc De Crop Ghent University Hospital, Ghent, Belgium
Herbert Spapen Universitair Ziekenhuis Brussels, Brussels, Belgium
Joost Wauters Universitair Ziekenhuis Gasthuisberg, Leuven, Brussels
Thierry Dugernier Clinique Saint Pierre, Ottignies, Belgium
Philippe Jorens Universitair Ziekenhuis Antwerpen, Edegem, Belgium
Ilse Dapper Algemeen Ziekenhuis Monica, Deurne, Belgium
Daniel De Backer Erasme University Hospital, Brussels, Belgium
93
Fabio S. Taccone Erasme University Hospital, Brussels, Belgium
Jordi Rello Vall d'Hebron Institut of Research. Universitat Autonoma de
Barcelona, Spain Centro de Investigación
Biomedica En Red- Enfermedades Respiratorias (CibeRes)
Laura Ruano Vall d'Hebron Institut of Research. Universitat Autonoma de
Barcelona, Spain Centro de Investigación
Biomedica En Red- Enfermedades Respiratorias (CibeRes)
Elsa Afonso Hospital Universitari Vall d'Hebron. Vall d'Hebron Institut of
Research. Universitat Autonoma de
Barcelona, Spain Centro de Investigación Biomedica En Red-
Enfermedades Respiratorias (CibeRes)
Francisco Alvarez-Lerma Hospital Del Mar, Parc Salut Mar. Barcelona, Spain
Maria Pilar Gracia-
Arnillas
Hospital Del Mar, Parc Salut Mar. Barcelona, Spain
Francisco Fernández Centro Médico Delfos, Barcelona
Neus Feijoo Hospital General de L’Hospitalet, Barcelona, Spain
Neus Bardolet Hospital General de L’Hospitalet, Barcelona, Spain
Assumpta Rovira Hospital General de L’Hospitalet, Barcelona, Spain
Pau Garro Hospital General de Granollers, Barcelona, Spain
Diana Colon Hospital General de Granollers, Barcelona, Spain
Carlos Castillo Hospital Txagorritxu, Vitoria, Spain
Juan Fernado Hospital Txagorritxu, Vitoria, Spain
Maria Jesus Lopez Hospital Universitario de Burgos. Burgos, Spain
Jose Luis Fernandez Hospital Universitario de Burgos. Burgos, Spain
Ana Maria Arribas Hospital Universitario de Burgos. Burgos, Spain
Jose Luis Teja Hospital Universitario Marques de Valdecilla, Santander, Spain
Elsa Ots Hospital Universitario Marques de Valdecilla, Santander, Spain
Juan Carlos Montejo Hospital Universitario 12 de Octubre, Madrid, Spain
Mercedes Catalan Hospital Universitario 12 de Octubre, Madrid, Spain
Isidro Prieto Hospital Ramon y Cajal, Madrid, Spain
Gloria Gonzalo Hospital Ramon y Cajal, Madrid, Spain
Beatriz Galvan Hospital Universitario La Paz, Madrid, Spain
94
Miguel Angel Blasco Hospital Universitario Severo Ochoa, Madrid, Spain
Estibaliz Meyer Hospital Universitario Severo Ochoa, Madrid, Spain
Frutos Del Nogal Hospital Universitario Severo Ochoa, Madrid, Spain
Loreto Vidaur Hospital Universitario de Donostia, Donostia, Spain
Rosa Sebastian Hospital Universitario de Donostia, Donostia, Spain
Pila Marco Garde Hospital Universitario de Donostia, Donostia, Spain
Maria del Mar Martin
Velasco
Hospital Universitario Nuestra Señora de Candelaria, Spain
Rafael Zaragoza Crespo Hospital Universitario Dr. Peset, Spain
Mariano Esperatti Institut Clínic del Tòrax, Hospital Clinic, IDIBAPS, Barcelona,
Spain; Centro de Investigación Biomedica En
Red- Enfermedades Respiratorias (CibeRes).
Antoni Torres Institut Clínic del Tòrax, Hospital Clinic, IDIBAPS, Barcelona,
Spain; Centro de Investigación Biomedica En
Red- Enfermedades Respiratorias (CibeRes).
Philippe Montravers Centre Hospitalier Universitaire Bichat-Claude Bernard, AP-HP,
Université Paris VII, Paris, France
Olivier Baldesi Centre Hospitalier Pays D Aix, Aix en Provence, France and AzuRea
Group
Herve Dupont Centre Hospitalier Universitaire d'Amiens, Amiens, France
Yazine Mahjoub Centre Hospitalier-Universitaire d'Amiens, Amiens, France and
AzuRea Group
Sigismond Lasocki Centre Hospitalier-Universitaire d'Angers, Angers, France
Jean Michel Constantin Centre Hospitalier Universitaire de Clermont-Ferrand, Clermont-
Ferrand, France and AzuRea Group
Jean François Payen Centre Hospitalier-Universitaire Grenoble, Grenoble France and
AzuRea Group
Claude Martin Hopital Nord, Marseille, France; AzuRea Group, France
Jacques Albanese Hopital Nord, Marseille, France and AzuRea Group
Yannick Malledant Hôpital Pontchaillou, Rennes, France
Julien Pottecher University Hospital, Strasbourg, France and AzuRea Group
Jean-Yves Lefrant Centre Hospitalier-Universitaire Nimes, Nimes France and AzuRea
95
Group
Samir Jaber Hospitalier-Universitaire Montpellier, Montpellier, France and
AzuRea Group
Olivier Joannes-Boyau Centre Hospitalier-Universitaire Bordeaux, Bordeaux, France and
AzuRea Group
Christophe Orban Centre Hospitalier-Universitaire Nice, Nice, France and AzuRea
Group
Marlies Ostermann St Thomas' Hospital, London, United Kingdom
Catherine McKenzie St Thomas' Hospital, London, United Kingdom
Willaim Berry St Thomas' Hospital, London, United Kingdom
John Smith St Thomas' Hospital, London, United Kingdom
Katie Lei St Thomas' Hospital, London, United Kingdom
Francesca Rubulotta Charing Cross Hospital, Imperial Healthcare NHS Trust, London,
United Kingdom
Anthony Gordon Charing Cross Hospital, Imperial Healthcare NHS Trust, London,
United Kingdom
Stephen Brett Hammersmith Hospital, Imperial Healthcare NHS Trust, London,
United Kingdom
Martin Stotz St Mary's Hospital, Imperial Healthcare NHS Trust, London, United
Kingdom
Maie Templeton St Mary's Hospital, Imperial Healthcare NHS Trust, London, United
Kingdom
Andrew Rhodes St George's Hospital, St George's Healthcare NHS Trust, London,
United Kingdom
Claudia Ebm St George's Hospital, St George's Healthcare NHS Trust, London,
United Kingdom
Carl Moran St George's Hospital, St George's Healthcare NHS Trust, London,
United Kingdom
Kirsi-Maija Kaukonen Helsinki University Central Hospital, Helsinki, Finland
Ville Pettilä Helsinki University Central Hospital, Helsinki, Finland
George Dimopoulos Attikon University Hospital, Athens, Greece
Despoina Koulenti Attikon University Hospital, Athens, Greece
96
Aglaia Xristodoulou Attikon University Hospital, Athens, Greece
Vassiliki Theodorou University Hospital of Alexandroupolis, Alexandroupolis, Greece
Georgios Kouliatsis University Hospital of Alexandroupolis, Alexandroupolis, Greece
Eleni Sertaridou University Hospital of Alexandroupolis, Alexandroupolis, Greece
Georgios Anthopoulos 251 Air Force General Hospital of Athens, Athens, Greece
George Choutas 251 Air Force General Hospital of Athens, Athens, Greece
Thanos Rantis 251 Air Force General Hospital of Athens, Athens, Greece
Stylianos Karatzas General Hospital of Athens ‘Hippokrateion’, Athens, Greece
Margarita Balla General Hospital of Athens ‘Hippokrateion’, Athens, Greece
Metaxia Papanikolaou General Hospital of Athens ‘Hippokrateion’, Athens, Greece
Pavlos Myrianthefs ‘Aghioi Anargyroi’ Hospita, Athens, Greece
Alexandra Gavala ‘Aghioi Anargyroi’ Hospita, Athens, Greece
Georgios Fildisis ‘Aghioi Anargyroi’ Hospita, Athens, Greece
Antonia Koutsoukou Sotiria General Hospital, Athens, Greece
Magdalini
Kyriakopoulou
Sotiria General Hospital, Athens, Greece
Kalomoira Petrochilou Sotiria General Hospital, Athens, Greece
Maria Kompoti ‘Thriassio’ General Hospital of Eleusi, Athen, Greece
Martha Michalia ‘Thriassio’ General Hospital of Eleusi, Athen, Greece
Fillis-Maria Clouva-
Molyvdas
‘Thriassio’ General Hospital of Eleusi, Athen, Greece
Georgios Gkiokas Aretaieion University Hospital, Athens, Greece
Fotios Nikolakopoulos Aretaieion University Hospital, Athens, Greece
Vasiliki Psychogiou Aretaieion University Hospital, Athens, Greece
Polychronis Malliotakis University Hospital Herakleion, Crete, Greece
Evangelia Akoumianaki University Hospital Herakleion, Crete, Greece
Emmanouil Lilitsis University Hospital Herakleion, Crete, Greece
Vassilios Koulouras University Hospital of Ioannina, Ioannina, Greece
George Nakos University Hospital of Ioannina, Ioannina, Greece
Mihalis Kalogirou University Hospital of Ioannina, Ioannina, Greece
Apostolos Komnos General Hospital of Larisa, Larisa, Greece
97
Tilemachos Zafeiridis General Hospital of Larisa, Larisa, Greece
Christos Chaintoutis General Hospital of Larisa, Larisa, Greece
Kostoula Arvaniti General Hospital of Thessaloniki ‘G. Papageorgiou’, Thessaloniki,
Greece
Dimitrios Matamis General Hospital of Thessaloniki ‘G. Papageorgiou’, Thessaloniki,
Greece
Christos Chaintoutis General Hospital of Thessaloniki ‘G. Papageorgiou’, Thessaloniki,
Greece
Christina Kydona General Hospital of Thessaloniki ‘Hippokrateion’, Thessaloniki,
Greece
Nikoleta Gritsi-
Gerogianni
General Hospital of Thessaloniki ‘Hippokrateion’, Thessaloniki,
Greece
Tatiana Giasnetsova General Hospital of Thessaloniki ‘Hippokrateion’, Thessaloniki,
Greece
Maria Giannakou Ahepa University Hospital, Thessaloniki, Greece
Ioanna Soultati Ahepa University Hospital, Thessaloniki, Greece
Ilias chytas Ahepa University Hospital, Thessaloniki, Greece
Eleni Antoniadou General Hospital ‘G. Gennimatas’, Thessaloniki, Greece
Elli Antipa General Hospital ‘G. Gennimatas’, Thessaloniki, Greece
Dimitrios Lathyris General Hospital ‘G. Gennimatas’, Thessaloniki, Greece
Triantafyllia Koukoubani General Hospital of Trikala, Trikala, Greece
Theoniki Paraforou General Hospital of Trikala, Trikala, Greece
Kyriaki Spiropoulou General Hospital of Trikala, Trikala, Greece
Vasileios Bekos Naval Hospital of Athens, Athens, Greece
Anna Spring Naval Hospital of Athens, Athens, Greece
Theodora Kalatzi Naval Hospital of Athens, Athens, Greece
Hara Nikolaou ‘Aghia Olga-Konstantopouleion’ General Hospital, Athens, Greece
Maria Laskou ‘Aghia Olga-Konstantopouleion’ General Hospital, Athens, Greece
Ioannis Strouvalis ‘Aghia Olga-Konstantopouleion’ General Hospital, Athens, Greece
Stavros Aloizos General Hospital of Athens ‘NIMITS’, Athens, Greece
Spyridon Kapogiannis General Hospital of Athens ‘NIMITS’, Athens, Greece
Ourania Soldatou General Hospital of Athens ‘NIMITS’, Athens, Greece
98
Matteo Bassetti Azienda Ospedaliera Universitaria Santa Maria della Misericordia,
Udine, Italy
Chiara Adembri Azienda Ospedaliero Universitaria Careggi, Florence, Italy
Gianluca Villa Azienda Ospedaliero Universitaria Careggi, Florence, Italy
Antonio Giarratano Università degli Studi di Palermo, Palermo, Italy
Santi Maurizio Raineri Università degli Studi di Palermo, Palermo, Italy
Andrea Cortegiani Università degli Studi di Palermo, Palermo, Italy
Francesca Montalto Università degli Studi di Palermo, Palermo, Italy
Maria Teresa Strano Università degli Studi di Palermo, Palermo, Italy
V. Marco Ranieri San Giovanni-Battista Molinette, Turin, Italy
Claudio Sandroni Catholic University School of Medicine, Rome, Italy
Gennaro De Pascale Catholic University School of Medicine, Rome, Italy
Alexandre Molin University of Genoa, Genoa, Italy
Paolo Pelosi University of Genoa, Genoa, Italy
Luca Montagnani Universitaria San Martino, Genova, Italy
Rosario Urbino Universitaria S.Giovanni Battista della Città di Torino, Torino, Italy
Ilaria Mastromauro Universitaria S.Giovanni Battista della Città di Torino, Torino, Italy
Francesco G. De Rosa Universitaria S.Giovanni Battista della Città di Torino, Torino, Italy
V. Marco Ranieri Universitaria S.Giovanni Battista della Città di Torino, Torino, Italy
Teresa Cardoso Hospital de Santo António, Porto, Portugal
Susana Afonso Hospital de St António dos Capuchos, Lisbon, Portgual
João Gonçalves-Pereira Hospital de São Francisco Xavier, Lisbon, Portugal
João Pedro Baptista Hospital de Universidade de Coimbra, Coimbra, Portugal
Murat Akova Hacettepe University School of Medicine, Ankara, Turkey
Arife Özveren Hacettepe University School of Medicine, Ankara, Turkey
4.2.7.3 Funding information
This project has received funding from the European Society of Intensive Care Medicine's
European Critical Care Research Network (ESICM ECCRN), and the Royal Brisbane and Women's
Hospital Research Foundation. Neither organization had a role in study design, analysis or drafting
of the manuscript.
99
4.2.7.4 Transparency declarations
Prof. Roberts is funded by a Career Development Fellowship from the National Health and Medical
Research Council of Australia (APP1048652). All other authors: none to declare.
100
4.3 Conclusion
This chapter supports the notion that altered beta-lactam dosing strategies may not be meritorious to
all critically ill patients but rather in a specific subset of patients with severe infections. Similar to
other previous small-scale studies, data from this chapter suggest that the critically ill patients who
are most likely to benefit from altered dosing strategies are those with severe pneumonia and not
receiving RRT. The information on patient groups which are more likely to benefit from altered
dosing approaches is vital to determine if PI is truly more advantageous than IB dosing. With this
data, future clinical studies should focus and test the potential clinical superiority of PI
administration in this specific subset of critically ill patients.
101
Chapter 5: The ideal characteristics of a clinical trial investigating
continuous infusion versus intermittent bolus dosing of beta-lactam
antibiotics
5.1 Synopsis
Superior bacterial killing of beta-lactam antibiotics via CI compared with traditional IB dosing has
been demonstrated in pre-clinical studies. Superior PK/PD profiles favouring CI administration
have also been reported in studies involving critically ill septic patients. Despite all the theoretical
advantages, to date, no study has conclusively shown any superiority of CI compared to IB dosing
in terms of patient clinical outcomes. Furthermore, recent meta-analyses of published literature
found no significant difference between CI and IB dosing with regards to clinical cure or patient
survival. However, a particularly noteworthy feature in these studies has been the inclusion of non-
critically ill patients, which may mask any potential benefits of either dosing approaches in
critically ill patients with severe sepsis. This chapter describes the methodological shortcomings
that are associated with current clinical studies in the comparison of CI and IB administration of
beta-lactam antibiotics. Several intriguing issues and problems surrounding the interpretation of
results obtained from these clinical studies are also discussed in the chapter. Based on these
discussions, a description of a methodologically robust, definitive clinical trial is proposed.
102
5.2 Manuscript entitled “Continuous beta-lactam infusion in critically ill
patients: the clinical evidence”
The manuscript entitled “Continuous beta-lactam infusion in critically ill patients: the clinical
evidence” has been accepted for publication in the Annals of Intensive Care (2012; 16(2): 37).
The co-authors contributed to the manuscript as follows: Conception and development of the study
design was performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz, under the guidance of Prof.
Jason A. Roberts and Prof. Jeffrey Lipman. Literature review was performed by the PhD candidate,
Mohd-Hafiz Abdul-Aziz, under the guidance and supervision of Prof. Jason A. Roberts and Prof.
Rinaldo Bellomo. The PhD candidate, Mohd-Hafiz Abdul-Aziz took the leading role in manuscript
preparation and writing with the supervision and guidance of Prof. Jason A. Roberts, Prof. Jeffrey
Lipman, Prof. Rinaldo Bellomo and Dr. Joel M. Dulhunty. All co-authors reviewed and contributed
to the final draft of the manuscript.
The accepted version of this manuscript is presented and incorporated in this chapter. However,
some text, tables and figures may have been inserted at slightly different positions to fit the overall
style of the thesis. Numbering of pages, tables and figures may also change to fit the thesis
requirements. Manuscript references have been collated with all other references in the thesis.
Permission has been granted by the publisher and copyright owner, BioMed Central Ltd., to
reproduce the manuscript in this Thesis.
103
CONTINUOUS BETA-LACTAM INFUSION IN CRITICALLY ILL PATIENTS: THE
CLINICAL EVIDENCE
Mohd H. Abdul-Aziz (1), Joel M. Dulhunty (1, 2), Rinaldo Bellomo (3), Jeffrey Lipman (1, 2),
Jason A. Roberts (1, 2, 4)
Affiliation:
(1) Burns, Trauma & Critical Care Research Centre, University of Queensland, Brisbane, Australia.
(2) Department of Intensive Care Medicine, Royal Brisbane and Woman’s Hospital, Brisbane,
Australia.
(3) Department of Intensive Care, Austin Hospital, Melbourne.
(4) Pharmacy Department, Royal Brisbane and Woman’s Hospital, Brisbane, Australia.
Keywords:
Beta-lactam antibiotic; continuous infusion; critically ill; pharmacokinetic; pharmacodynamic;
treatment outcome.
Address for correspondence:
Dr. Joel Dulhunty,
Department of Intensive Care Medicine,
Royal Brisbane and Women’s Hospital,
Herston, QLD 4029, Australia.
Ph: +6 1 7 3636 8111 Fax: +6 1 7 3636 3542
104
5.2.1 Abstract
Beta-lactam antibiotics display time-dependant PD whereby constant antibiotic concentrations
rather than high peak concentrations are most likely to result in effective treatment of infections
caused by susceptible bacteria. CI has been suggested as an alternative strategy, to conventional IB
dosing, to optimize beta-lactam PK/PD properties. With the availability of emerging data, we
elected to systematically investigate the published literature describing the comparative PK/PD and
clinical outcomes of beta-lactam antibiotics administered by CI or IB dosing. We found that the
studies have been performed in various patient populations including critically ill, cancer and cystic
fibrosis patients. Available in vitro PK/PD data conclusively support the administration of beta-
lactams via CI administration for maximizing bacterial killing from consistent attainment of PD
end-points. In addition, clinical outcome data supports equivalence, even with the use of a lower
dose by CI. However, the present clinical data is limited with small sample sizes common with
insufficient power to detect advantages in favour of either dosing strategy. With abundant positive
pre-clinical data as well as document in vivo PK/PD advantages, large multicentre RCTs are needed
to describe whether CI administration of beta-lactams is truly more effective than IB dosing.
105
5.2.2 Introduction
The mortality rate of severe sepsis and septic shock in critically ill patients remains high despite
recent therapeutic advances. Swift and judicious antibiotic use in these patients is vital and any
delays are associated with increases in mortality [4, 357]. Beta-lactam antibiotics are used
commonly and are regarded as a cornerstone in the management of critically ill patients with severe
sepsis in ICUs around the world [357, 383, 384]. However, the occurrence of severe
pathophysiological changes, namely the fluid shift phenomenon [64] and ARC [385], in critically ill
patients may alter the PK of the antibiotics. Thus, appropriate dosing modifications should be
applied to prevent inadequate antibiotic concentrations and therapeutic failure [8, 56, 64].
Antibiotic PD is the discipline that attempts to relate PK parameters to the ability of an antibiotic to
kill or inhibit the growth of bacterial pathogens [11]. Antibiotics can be classified based on these
PD characteristics. Generally, antibiotics are classified into three categories based on their mode of
bacterial killing: (a) concentration-dependent; (b) time-dependent; or (c) both (Figure 5-1). The first
category includes antibiotics, such as aminoglycosides, where the best predictor of efficacy is
Cmax/MIC [386, 387]. Some antibiotics, such as fluoroquinolones and glycopeptides, are more
complex and exhibit both a concentration and time-dependent kill characteristics where the best
predictor of efficacy is AUC0-24/MIC. Therefore, increasing the dose or/and concentration for these
antibiotics can be logically expected to enhance the rate and extent of bacterial killing [388, 389]. In
contrast, higher beta-lactam concentrations do not significantly influence their efficacy. Based on
numerous in-vitro and in-vivo experimental data, it is the duration of effective antibiotic exposure
that is more important for these time-dependent antibiotics [12, 24, 390, 391].
The debate persists about whether traditional IB dosing or CI administration is clinically preferable
for administration of beta-lactam antibiotics. This is despite the fact that beta-lactam PD data
suggest advantages for CI compared with IB [79, 85, 247, 253, 330, 362, 363], showing time-
dependent activity and demonstrating that the fT>MIC best describes its bacterial kill characteristics
[12] (Figure 5-1). Thus, administration via CI should be advantageous, because it inevitably
produces higher and sustained antibiotic concentrations above the MIC. It also is noteworthy that IB
yields unnecessary high peak and low trough concentrations below MIC for much of the dosing
interval [67, 174, 175, 250] (Figure 5-2 and Figure 5-3). The constant and sustainable antibiotic
concentrations provided by CI are particularly important for pathogens with high MIC values. Such
pathogens are relatively common in the ICU [14, 86, 264].
106
Figure 5-1: Study flowchart demonstrating the number of patients who were included and
excluded in each stage of the planned analysis
Abbreviation: AUC0-24, area under the concentration-time curve during a 24-hour time period; Cmax,
maximum plasma antibiotic concentration; T>MIC, time that a drug’s plasma concentration remains
above the minimum inhibitory concentration (MIC) for a dosing period.
Figure 5-2: The simulated concentration-time profile of a beta-lactam when administered by
intermittent bolus dosing or continuous infusion (Vd = 0.22 L/kg; T½ = 2.45 hr)
Legend: Continuous infusion (dotted lines); intermittent bolus dosing (solid lines).
107
Figure 5-3: Observed steady state plasma and tissue concentrations for meropenem
administered to critically ill patients with sepsis by intermittent bolus dosing and continuous
infusion (adapted from Roberts et al., 2009, J Antimicrob Chemother)
Abbreviation: CI, continuous infusion; ISF, interstitial fluid.
Legend:
Continuous infusion (CI) meropenem plasma concentration (solid dark lines); IB meropenem
plasma concentration (dotted grey lines); IB meropenem interstitial fluid (ISF) concentration (solid
grey lines); CI meropenem ISF concentration (dotted dark lines).
Despite these theoretical advantages, a global practice shift towards CI of beta-lactam antibiotics
has not taken place. Although CI has been shown to be superior to IB dosing during in in vitro [152,
219] and in vivo [231, 233, 235, 392] experimental studies, comparative clinical studies have so far
failed to demonstrate significant differences in patient outcome. Furthermore, three recent meta-
analyses of these clinical trials have found similar outcomes between CI and IB, in heterogeneous
hospitalized patient populations [217, 267, 377]. This dissociation between pre-clinical data and
clinical reports raises uncertainty for the treating clinician. Additionally, most trials have important
methodological flaws and have used inconsistent methods and therapeutic end-points [14]. There
also is a lack of general consensus about which patient groups should be investigated and the
appropriate methodology that should be employed to identify whether clinical outcome differences
between these two dosing approaches exist in all hospitalized patients. The possible advantages and
disadvantages from the two dosing methods are further summarized in Table 5-1.
108
Table 5-1: Possible advantages and disadvantages of employing continuous or intermittent
administration of beta-lactam antibiotics
Administration method Advantages Disadvantages
Continuous infusion More predictable antibiotic
pharmacokinetic profiles
Relatively new antibiotic
administration method thus
requiring intensive educational
effort to update clinical staff on
the administration method prior to
implementation
Lower antibiotic daily dose
may be appropriate with
continuous infusion
May increase the cost of treatment
Reduced drug acquisition
costs when lower antibiotic
doses are used
Some beta-lactams
(e.g., meropenem) are not stable
under prolonged exposure at room
temperature and may produce and
enhance degradation products that
cause hypersensitivity reactions
Effective resource
consumption
(e.g., reduce the time
required for pharmacists or
nurses to prepare and
administer antibiotic)
Risk of drug wastage is high with
this approach (e.g., when
treatment ceased before infusion
bag completed)
Intermittent bolus Simple. Pharmacokinetic and
pharmacodynamic targets may not
be achieved (especially in
critically ill patients)
Does not require dedicated
line access for drug
administration
(incompatibility issues
unlikely)
Neurological adverse effects are
theoretically more possible with
high Cmax
Less likely to have
unexpected device failures
and dosing delivery rate
errors
109
The purpose of this review is to describe the published clinical trials and their associated
methodological shortcomings in their comparison of CI and IB administration in hospitalized
patients. Several intriguing issues or problems involved in the interpretation of results obtained
from the available studies also will be highlighted. Finally, based on these discussions, description
of a methodologically robust, definitive clinical trial will be proposed.
5.2.3 PK/PD considerations
The % fT>MIC during a dosing interval is regarded as the optimal PD index for beta-lactam
antibiotics and as such, maintaining effective drug concentration above the MIC should be the
priority when this antibiotic class is used. Specifically, the % fT>MIC needed for bacteriostasis and
bactericidal is 35-40% and 60-70% for cephalosporins, 30% and 50% for penicillins, 20% and 40%
for carbapenems, respectively [10, 11, 152, 393]. However, it is imperative to note that these
indices should be regarded as the minimum PD end-points and that they may not be adequate to
treat severe infections and to prevent the development of antibiotic resistance [394]. Furthermore,
emerging retrospective clinical data for critically ill patients suggest patients’ benefits with higher
and longer antibiotic exposures than those described for the in vitro and in vivo experimental studies
[28, 298]. Thus, it has been suggested that maintaining concentrations above the MIC for 90-100%
of the dosing interval is a rational PD end-point to ensure that the above minimum targets are
achieved [153]. Combining the above data, beta-lactams should be more effective when delivered
continuously to achieve a concentration above the MIC throughout treatment.
Alternatively, prolonging the infusion time via EI dosing, also has been suggested to maximize the
fT>MIC for this antibiotic class without some of the CI-associated drawbacks outlined in Table 5-1
[190, 242]. Both CI and EI may be particularly advantageous in the treatment of severe infections.
5.2.3.1 Inconsistent PD end-points for comparison
Different PD end-points have been used in published studies which make comparison between CI
and IB difficult. However, several reviews have suggested that prolonged antibiotic exposures will
achieve better PD profile [56, 395, 396]. Apparent benefits with regards to maximum bacterial
killing also were reported in several studies when antibiotic concentrations were maintained above
the MIC for extended periods, ideally four- to five-times the MIC especially when less susceptible
microorganisms were involved [25, 28, 82, 152, 221, 397]. In combination with other PK/PD data,
it is suggested that therapeutic targets for CI therapy should be a Css that is at least 4 x MIC [152].
Thus, future comparative PK/PD studies should evaluate the relative ability of IB to achieve a Cmin
110
greater than the 4 x MIC of the offending pathogen for 40-70% of a dosing interval and for CI, a Css
greater than 4 x MIC to prevent biased comparisons. It follows that the real challenge for IB is to
obtain a Cmin greater than 4 x MIC in a severely ill patient who is infected with a pathogen with
high MIC.
5.2.3.2 The role of post-antibiotic effect
Another consideration for optimizing antibiotic pharmacokinetic exposure is the PAE i.e., the
suppression of bacterial growth even with antibiotic concentrations below the MIC [12, 154, 157,
158]. Although all antibiotics demonstrate PAE against susceptible Gram-positive pathogens (i.e.,
staphylococci and streptococci), only some antibiotics, such as the aminoglycosides and
fluoroquinolones produce prolonged PAE for Gram-negative pathogens [12]. In contrast, beta-
lactams except for the carbapenems, produce minimal or no PAE against Gram-negative pathogens.
It follows that the reduced % fT>MIC required for carbapenems bacteriostatic (20%) and bactericidal
(40%) activity may relate to the antibiotics PAE [154, 158, 160-162, 398]. Therefore, the need for
frequent dosing and continuous administration is deemed supplemental when antibiotics such as
carbapenems display significant PAE.
5.2.3.3 Revision in antibiotic breakpoints
The recent revision in antibiotic breakpoints to indicate if an organism is susceptible or resistant to
different antibiotics, as classified by EUCAST and CLSI, have had an impact on how clinicians
view and manage infections worldwide [14]. These new rules also are applicable for interpretation
of antibiotic PK/PD studies. Due to these changes, future studies need to be interpreted in light of
the new susceptibility breakpoints [361]. These new rules may mean that the present dosing
approaches are more, or less likely to achieve PK/PD targets.
5.2.3.4 The role of optimal PK/PD targets in the prevention of antibiotic resistance
Antibiotic resistance patterns have significantly changed during the past 15 years with increasing
resistance currently regarded as a major health crisis [399, 400]. Furthermore, the rate at which the
pathogens are currently developing antibiotic resistance is likely to far outpace the rate of
development of new antibiotics. Thus, optimizing the use of new or existing antibiotics via PK/PD
principles may prolong their life span in clinical practice [10, 398]. Although numerous studies
have been performed to determine the optimal PK/PD targets for clinical and bacteriological
success, very little data exist that describe their roles in the prevention of bacterial resistance.
111
However, extensive research in this area has been conducted with fluoroquinolones and more
importantly, the corresponding optimal PD targets (i.e., AUC/MIC breakpoints) for resistance
prevention has been described for this antibiotic class [349, 401, 402]. The success with
fluoroquinolones further emphasizes that PK/PD principles are not only relevant in bacterial
eradication but also should be considered to minimize the development of bacterial resistance. For
the beta-lactams, however, limited data are currently available, with the exception of several in vitro
[365, 403] and in vivo experimental studies [404], which suggest the optimal PD targets for the
prevention of resistance. Thus, appropriate targets are initially needed for this antibiotic class before
a dosing regimen that minimizes resistance development can be recommended. Until convincing
evidence becomes available, antibiotic dosing that targets concentrations greater than 4-6 x MIC for
an extended interval should be aimed at to prevent resistance [149, 152, 405]. It also follows that
once the targets are defined, it will then be possible to evaluate the relative ability of CI versus IB in
reducing the emergence of resistance associated with the use of beta-lactam antibiotics. However,
several reviews have suggested that the currently proposed PK/PD target is probably best achieved
by using CI or EI [14, 153].
5.2.4 Controversies surrounding data interpretation
Since the initial availability of antibiotics, methods to optimize antibiotic dosing have been explored
[391, 406]. Numerous trials have been conducted with beta-lactams testing various dosing strategies
in various patient populations [82, 151, 171-173, 243, 248, 254-258, 261, 262, 266, 305, 407]. The
characteristics and findings of these relevant clinical trials are described in Tables 5-2 and 5-3,
respectively. However, these studies have not defined whether altered dosing approaches are
advantageous and which patient groups may benefit. Most of these trials were conducted in North
America and Europe between 1979 and 2008 with all but two studies published after the year 2000
[255, 262]. A number of articles also have discussed the potential advantages and disadvantages of
CI [14, 15, 17, 153, 264]. Yet, the limitations of the existing studies have not been analysed in
detail and require further elaboration. Figure 5-4 briefly summarizes the current limitations
associated with the available clinical trials.
112
Table 5-2: Characteristics of previously published studies of continuous versus bolus dosing of beta-lactam antibiotics
Study Setting
(Country)
Antibiotic Critically ill Population Sample
size
Agea Allocation
sequence
generator
Allocation
concealment
Masking Concomitant
antibiotic CI IB
Angus et al.,
[151]
Not specified
(Thailand)
Ceftazidime Yes Septicaemic
melioidosis
21 48
(29-58)
43
(27-73)
Not specified Not specified Not specified Various
Bodey et al.,
[255]
Non-ICU
(USA)
Cefamandole No Malignant diseases
with neutropenia
204 Not specified Adequate Adequate Not specified Carbenicillin
Buck et al.,
[173]
Non-ICU
(Germany)
Piperacillin/tazobactam No Hospitalized
infections
24 60-88b 32-76b Not specified Adequate No Nil stated
Georges et al.,
[172]
ICU
(France)
Cefepime Yes Critically ill with
Gram-negative
infections
50 50±17 46±24 Not specified Not specified No Amikacin
Hanes et al.,
[254]
ICU
(USA)
Ceftazidime Yes Critically ill trauma 32 33.5±12.5 36.1±12.8 Not specified Not specified No Nil stated
Lagast et al.,
[262]
Not specified
(Belgium)
Cefoperazone No Gram-negative
septicaemia
45 37-77b Not specified Not specified No Nil stated
Lau et al.,
[256]
ICU
(USA)
Piperacillin/tazobactam No Complicated intra-
abdominal infections
262 50.4±16.6 49.3±17.8 Not specified Not specified No Nil stated
Lubasch et al.,
[258]
Not specified
(Germany)
Ceftazidime No Hospitalized patients
with COPD
exacerbation
81 65.3±10.1 Not specified Not specified No Nil stated
Nicolau et al.,
[266]
ICU
(USA)
Ceftazidime Yes Critically ill patients
with sepsis
41 46±16 56±20 Adequate Not specified No Tobramycin
Pedeboscq et al.,
[261]
ICU
(France)
Piperacillin/tazobactam Yes Severe sepsis 7 58±12 Not specified Not specified No Ofloxacin
Rafati et al.,
[248]
ICU
(Iran)
Piperacillin Yes Critically ill patients
with sepsis
40 50.1±22.2 48.0±20.7 Not specified Not specified No Amikacin
Roberts et al.,
[243]
ICU
(Australia)
Ceftriaxone Yes Critically ill patients
with sepsis
57 43±19 52±16 Adequate Adequate Adequatec Multiple
depending on
indication
Sakka et al.,
[171]
ICU
(Germany)
Imipenem/cilastatin Yes Critically ill patients
with sepsis
20 62±16 59±16 Not specified Adequate No Nil stated
Van Zanten et al.,
[257]
Not specified
(Netherlands)
Cefotaxime No Hospitalized patients
with COPD
exacerbation
93 65.3±8.4 68.6±5.3 Not specified Not specified No Nil stated
Abbreviation: CAP, community-acquired pneumonia; CI, continuous infusion; COPD, chronic obstructive pulmonary disease; CVVH, continuous venovenous haemofiltration; IB, intermittent bolus; ICU, intensive care unit.
Legend:
aValues are reported according to published results as mean (±SD) or median (interquartile range).
bValues are reported as range.
cOnly outcome assessment was blinded.
113
Table 5-3: Antibiotics dosage and outcome data of previously published studies for CI versus IB dosing of beta-lactam antibiotics
Study Types of infection Number of patients
(APACHE II scorea)
Antibiotic dosage regimen Concurrent
PK/PD analysis
Clinical outcome
measures
CI IB p-valueb
CI IB CI IB
Angus et al.,
[151]
Septicaemic
melioidosis
10 (15) 11 (21) 12 mg/kg LD, then 4
mg/kg every 1 hr
40 mg/kg every 8 hrs Yes Mortality 20% 36.4% 0.89
Bodey et al.,
[255]
Pneumonia, UTI &
neutropenic fever
167 (ND) 162 (ND) 3 g LD, then 12 g/24
hrs
3 g every 6 hrs No Clinical cure 64% 57% ND
Buck et al.,
[173]
Pneumonia, IAI & fever
of unknown origin
12 (ND) 12 (ND) 2 g LD, then 8 g/24 hrs 4 g every 8 hrs Yes Clinical response 67% 67% ND
Georges et al.,
[172]
Pneumonia & blood
stream infection
24 (45)c 23 (44)c 2 g/12 hrs twice daily 2 g every 12 hrs No Clinical cure 85% 67% ND
Mortality 12% 13% ND
Duration of MV 24 days 25 days ND
ICU LOS 34 days 40 days ND
Hanes et al.,
[254]
Pneumonia 17 (13) 14 (11) 2 g LD, then 60 mg/kg
every 24 hrs
2 g every 8 hrs Yes Duration of leukocytosis 8 days 11 days 0.35
Duration of pyrexia 8 days 4 days 0.06
Duration of MV 23 days 12 days 0.16
ICU LOS 27 days 16 days 0.11
Hospital LOS 41 days 29 days 0.37
Lagast et al.,
[262]
Blood stream infection 20 (ND) 25 (ND) Day 1: 1 g LD, then 3
g/24 hrs
Day 2 +: 4 g/24 hrs
2 g every 12 hrs No Clinical cure 25% 16% ND
ICU mortality 70% 80% ND
Lau et al.,
[256]
IAI 81 (8) 86 (8) 2 g LD, then 12 g /24
hrsg
3 g every 6 hrsg No Clinical cure 86% 88% 0.817
Bacteriological cure 77% 88% 0.628
Lubasch et al.,
[258]
Pneumonia 41 (ND) 40 (ND) 2 g LD, then 2 g/7 hrs
twice daily
2 g every 8 hrs Yes Clinical cure 90% 90% ND
Bacteriological cure 90% 88% ND
Nicolau et al.,
[266]
Pneumonia 17 (14) 18 (16) 1 g LD, then 3 g/24 hrsh 2 g every 8 hrsh No Clinical cure 41% 33% 0.592
Duration of MV 8 days 8 days 0.97
Days to defervescence 3 days 5 days 0.015
Days to WCC
normalization
7 days 6 days 0.259
LOS ICU 9 days 9 days 0.691
Pedeboscq et al.,
[261]
IAI 3 (ND) 4 (ND) 12 g/24 hrs 4 g every 8 hrs Yes Mortality 0% 0% ND
Rafati et al.,
[248]
Pneumonia, IAI, UTI,
CNS infection, SSTI &
blood stream infection
20 (16) 20 (14) 2 g LD, then 8 g/24 hrs 3 g every 6 hrs Yes Mortality 30% 25% 0.72
Decrease in illness
severity
CI>ITd
Duration of pyrexia 2 days 1 day 0.08
WCC normalization 75% 83% ND
114
Roberts et al.,
[243]
Pneumonia, IAI, UTI,
CNS infection, SSTI &
blood stream infection
29 (19) 28 (16) 0.5 g LD, then 2 g/24
hrs
Day 1: 2.5 g/24 hrs
Day 2: 2 g/24 hrs
No Clinical curee 52% 20% 0.04
Mortality 10% 0% 0.25
Duration of MV 4 days 3 days 0.33
ICU LOS 11 days 6 days 0.29
Hospital LOS 42 days 24 days 0.34
Sakka et al.,
[171]
Pneumonia 10 (26) 10 (28) 1 g LD, then 2 g /24 hrs 1 g every 8 hrs Yes Mortality 10% 20% ND
Van Zanten et al.,
[257]
COPD exacerbation 40 (ND) 43 (ND) 1 g LD, then 2 g/24 hrs 1 g every 8 hrs Yes Clinical cure 93% 93% 0.93
Abbreviation: APACHE, Acute Physiology and Chronic Health Evaluation; CI, continuous infusion; CNS, central nervous system; CRP, C-reactive protein; IAI, intra-abdominal infection; IB, intermittent bolus; ICU,
intensive care unit; LD, loading dose; LOS, length of stay; MV, mechanical ventilation; ND, not described; PK/PD, pharmacokinetic/pharmacodynamic; SOFA, Sequential Organ Failure Assessment; SSTI, skin and skin-
structure infection; UTI, urinary tract infection; WCC, white cell counts.
Legend:
aValues are reported as mean or median.
bBold values indicate statistical significance at p <0.05.
cValues are SAPS scores.
dStatistically significant difference in APACHE II scores on Days 2, 3 and 4.
eA priori analysis.
115
Figure 5-4: The summary of the current limitations and flaws associated with the available
clinical trial
5.2.4.1 Heterogeneous patient populations
Most of the relevant trials recruited hospitalized patients from different populations, especially the
non-critically ill patient groups (Table 5-2). The diverse range of patient groups include critically ill
patients with sepsis [151, 172, 243, 248, 261, 262, 266], trauma patients (86), patients with
abdominal infections [256, 407], COPD patients [257, 258], cancer [255] and non-specific
hospitalized infections [173]. Thus, meta-analyses have evaluated heterogeneous patient groups and
any potential benefits of CI or IB that may exist in a particular patient group were not assessed. This
issue was previously discussed by Roberts et al., in their meta-analysis, where large CI were
observed suggesting clinical differences may exist between CI and IB administration if more
stringent and rigorous inclusion criteria were used in clinical studies [217].
5.2.4.2 Inclusion of patients with a low level of illness severity
Detecting significant difference between CI and IB is difficult because the potential benefits may be
masked by the inclusion of low-risk patients who have much lower mortality rates than reported in
epidemiological studies. This selection bias was further described in two recent meta-analyses [217,
116
377]. For example, two of the nine ICU studies that were meta-analysed by Roberts et al., reported
a mortality rate ≤10% when the mortality rate for severe sepsis is usually reported between 40% and
50% [33, 408, 409] (Table 6-3). Other studies also recruited patients with low illness severity
whereby more than 70% of the cohort presented with an APACHE II score of only 10 [256]. This is
a problem because any differences between CI and IB are more likely emerge in more severely ill
patients [151, 298]. Critically ill patients with severe sepsis are more likely to benefit from CI,
because they commonly develop severe pathophysiological changes which may reduce effective
antibiotic exposure [129]. Furthermore, these patients are usually infected with pathogens that are
less susceptible to antibiotic therapy. Thus, in combination, the two important factors may reduce
PK/PD target attainment in severely ill patients. In contrast, it has been shown that IB dosing of
beta-lactam antibiotics achieves adequate PK/PD target for bacterial eradication in patients with low
level of illness severity.
5.2.4.3 Inconsistent antibiotic dosing regimen
Most of the studies included in the three meta-analyses utilized higher IB doses than the CI
treatment arm, potentially favouring the former [151, 171, 173, 248, 254, 256, 257, 266] (Table 5-
3). This treatment bias might have skewed the results of these meta-analyses towards the null
hypothesis. Another logical conclusion is that a lower dose in the CI group was able to achieve
equivalent outcomes to a higher dose in the IB group. A significant difference in clinical outcomes
might emerge if the two approaches utilized the same daily dose. This notion has been supported by
a meta-analysis, whereby clinical failures were less frequent in the CI group, when separate
analyses were performed in trials which used the same total daily dose in the two treatment arms
[267]. Furthermore, dosing inconsistency with regards to initial bolus administration of antibiotic
was reported in several studies [172, 261, 407] (Table 5-3). An initial loading dose was not
provided to the CI protocol in these studies. This approach delays attainment of target antibiotic
concentrations compared with the IB group. To make the two dosing protocols comparable, an
initial and equal loading dose of beta-lactam antibiotic should be provided to both groups.
5.2.4.4 Pathogens with low MIC values
The offending pathogens isolated in most of the clinical trials have MIC values that make them
highly susceptible. Simulation data suggests that there will be little difference in the achievement of
PK/PD targets for IB and CI if the pathogens involved are in the susceptible range. When less
susceptible pathogens are present, the true potential benefits of CI may be seen because treatment
failures are more likely with IB [28, 151, 174, 398]. This limitation has been highlighted in the two
117
most recent meta-analyses and has been proposed as one of the contributing reasons why clinical
differences between CI and IB of beta-lactams have not been found. This notion is supported by one
RCT [151] and two retrospective, observational studies [274, 298] which were conducted in
critically ill patients infected with Gram-negative organisms. These studies reported clinical cure
and mortality benefits favouring CI for pathogens with high MIC values.
5.2.4.5 Concomitant administration of other antibiotics
Another noteworthy limitation is that patients included in the available clinical trials were
frequently prescribed concomitant antibiotics that, unrelated to the method of beta-lactam
administration, may influence clinical outcome [267, 377]. Such additional antibiotics
(aminoglycosides and fluoroquinolones) provide adequate antimicrobial coverage for most Gram-
negative pathogens. Therefore, the exclusive contribution of beta-lactam antibiotics to patient
outcomes will be poorly defined in these trials. However, in reality, beta-lactam antibiotics are
usually administered in conjunction with an aminoglycosides especially when treating patients with
severe infections. It follows that regardless of the beta-lactam administration method, the
aminoglycosides or fluoroquinolones may be “protecting” patients from Gram-negative pathogens
during periods of inadequate beta-lactams concentration. A plausible explanation could be that the
method of administering beta-lactams is not that important when additional Gram-negative
coverage (i.e., aminoglycosides or fluoroquinolones) is used.
5.2.4.6 Insufficient sample sizes
The lack of significance in the published results also may be attributed to the consistently small
sample sizes that have been used to explore the effect of CI versus IB. The typical study cohort size
has varied from 10 to 531 patients but the majority of these trials studied less than 60 patients [82,
171-173, 243, 248, 254, 262, 266, 407] (Table 5-2). The small sample sizes and heterogeneous
patient background in the clinical studies contribute to insufficient power to investigate the value of
both dosing methods. Further to this, if the population of interest is critically ill patients, a single
intervention in this setting is unlikely to influence mortality and clinical cure [264] and, as a
consequence, a much larger sample size is needed to show significance [172, 267, 330]. For
instance, Roberts et al., calculated that a sample size of 560 patients in each dosing protocol would
be needed to detect difference in bacteriological outcomes [243]. Considering the difficulties in
achieving these numbers in critically ill patients, perhaps it is time for clinicians to fully
acknowledge the importance of surrogate end-points in the setting of a study. Clinical cure and
118
ICU-free days are suitable surrogate end-points and may be used as primary outcomes in a phase II
study of this intervention.
5.2.5 Other relevant concerns
Apart from the discussion above, there are several other plausible reasons why clinical differences
have not been established between CI and IB in previous trials. It is important to note that some
patients, especially in the ICU, may have some degree of renal impairment on admission or during
their hospital stay [136, 410, 411]. Whereas a commonly prescribed beta-lactam dose may not be
sufficient in patients with mild or no renal impairment, target antibiotic concentrations are more
easily achieved in patients with moderate to advanced renal impairment [211]. Similarly, beta-
lactam exposure will still be adequate in patients with significant renal impairment as antibiotic CL
is reduced, regardless of the drug administration method [253]. Finally, one of the strongest bodies
of evidence suggesting the superiority of CI has been derived from animal studies. However, the
metabolic pathways and tissue distribution patterns of an antibiotic in animals may differ from
humans. In addition, more often than not, these animal models fail to mimic human sepsis [412,
413].
Based on the discussion above, clearer insights regarding CI and IB administration in patients
receiving beta-lactam antibiotics are emerging. Importantly, the results from previous clinical
studies suggest that CI of beta-lactam antibiotics is unlikely to be advantageous for all hospitalized
patients but may be important in specific patient cohorts. Thus, in an attempt to elucidate the true
benefits, we contend that the patient population most likely to adequately test the putative benefits
of CI of beta-lactam antibiotics must involve: (a) critically ill patients; (b) patients with higher level
of illness severity (i.e., APACHE II score ≥15); (c) patients infected with less susceptible
microorganisms; and (d) patients with Gram-negative infections.
5.2.6 Methodology concerns and the proposed characteristics of an “ideal” trial
Several reviews have suggested the importance of designing and conducting a methodologically
sound clinical trial in the investigation of CI versus IB antibiotic administration benefits in critically
ill patients [14, 217, 267, 377]. These recommendations cannot be overemphasized due to frequent
reports of low methodological quality clinical studies. It also is noteworthy that a previous study,
which utilized the most rigorous and stringent methods was the only study to demonstrate a clinical
cure advantage in favour of CI administration of beta-lactams [243]. The characteristics of an
119
“ideal,” randomized, clinical trial to compare CI versus IB administration of beta-lactam antibiotics
in critically ill patients are described in Table 5-4.
Table 5-4: Description of a randomized clinical trial that should be performed to investigate
CI versus IB of beta-lactam antibiotics
Criteria Comments
Population Should only include patients with sepsis or severe sepsis
Intervention Antibiotic dosing regimen should be similar between CI and IB group
a. A loading dose should be given to continuous infusion group to
ensure rapid attainment of target antibiotic concentration
b. An equal daily antibiotic dose should be given to continuous and
bolus administration group
c. Antibiotic doses should be specified according to the patient’s body
weight
d. Concomitant administration of other non-beta-lactam antibiotics
should be allowed
PK/PD analysis Concurrent PK/PD analysis should be performed to support any findings
a. Measurements of antibiotic concentrations should be performed as
long as contributing sites have necessary infrastructure to ensure apt
sampling
b. PK/PD analysis should evaluate the relative ability of IB to achieve a
Cmin greater than 4 x MIC of the offending pathogen for 40-70% of
the dosing interval while for CI, a Css greater than 4 x MIC
Methods Design
Preferably multicenter in nature and recruits participants from different
regions to improve generalizability of results
Patients
Define eligibility criteria for participants to be included into trial
a. Definition of sepsis and severe sepsis should be described in detail
b. Inclusion and exclusion criteria used should be explained
Randomization
Detailed explanation on allocation sequence generation development
Detailed allocation concealment mechanism
Blinding/masking
Outcome evaluators for the trial should be blinded to treatment allocation
End-points
a. End-points selection should include primary (clinical outcome) and
secondary (PK/PD; adverse event) end-points
b. Data collection on the observed bacterial resistance in the two
treatment arms should occur
120
Most studies did not address the methods for allocation sequence generation and concealment
further increasing the chance for selection bias [172, 173, 248, 254, 256-258, 261, 262, 266, 305,
407] (Table 5-2). In many studies, masking or blinded assessment of the study end-points were not
adequately addressed causing detection bias [151, 171-173, 248, 254-258, 262, 266, 305, 407]
(Table 5-2). In addition, most of the available studies have failed to have blinded clinicians to assess
the clinical and bacteriological outcomes. Each of these issues increases the possibility of
systematic errors in these studies.
Ideally, the antibiotic dosing regimen in each treatment arm (i.e., CI and IB) should be comparable
in terms of the provision of an initial loading dose with an equal daily antibiotic dose. Alternatively,
a suitable surrogate end-point, such as a cost-effective analysis, may be used to compare these two
dosing approaches when unequal antibiotic doses are used between them. Concomitant
administration of other non-beta-lactam antibiotics, such as the aminoglycosides or
fluoroquinolones, in the setting of a study is appropriate considering that a single empirical therapy
is unlikely to occur during antibiotic initiation in ICU patients [357, 384]. Furthermore, the
concomitant administration of other antibiotics should be regarded as a limitation rather than a
major flaw in future trials, because it reflects real clinical practice. However, the number of
concomitant antibiotics that are used and their administration sequences in relation to the main
study antibiotic should at least be described in the trials.
Only a number of studies measured antibiotic concentrations and included a concurrent PK/PD
evaluation to confirm whether the dosing approaches were actually meeting their respective PK/PD
end-points (Table 5-3) [82, 171, 248, 254, 256, 257]. Hence, it is difficult to relate clinical
outcomes to the respective antibiotic exposure obtained via the two approaches. It is imperative to
note the difference in PK/PD end-points with regards to CI and IB. In a comparison that reflects
current practice, CI has to achieve a Css greater than 4 x MIC to be microbiologically more effective
than IB. On the other hand, IB has to achieve an antibiotic Cmin greater than 4 x MIC during the
typical 40-70% of the dosing interval [14, 151, 152, 358]. Therefore, concentration measurement
and concurrent PK/PD analysis needs to be done in light of this information or the extent of
antibiotic exposure may not occur as predicted and therefore the influence on clinical cure and
mortality will remain unclear. Concurrent analysis should be considered “compelling” in future
trials as long as contributing clinical sites have the necessary infrastructure to ensure appropriate PK
sampling.
121
Considering the rampant development of bacterial resistance, the exact role of altered dosing
approaches to reduce the problem should be addressed. To date, studies investigating the impact of
various beta-lactams dosing approaches and their associated risk of bacterial resistance are scarce
[149]. However, it is interesting to note the findings of a recent prospective, multicenter,
randomized study that compared the clinical benefits of EI doripenem versus IB imipenem patients
with VAP [305]. The authors reported that only 18% of patients treated with EI developed
resistance of P. aeruginosa compared with 50% who received the conventional imipenem dosing.
This is one of the few recent studies to evaluate the relative ability of the two dosing approaches in
the prevention of resistance; similar studies, particularly involving critically ill patients, should
ensue. Although there are not enough prior clinical data to power a study in the ICU and describe
the appropriate methodology, data collection on the observed resistance should be performed in
future clinical trials investigating the two dosing approaches.
Previously published studies have mostly been single-center in design. To our knowledge, only
three studies were conducted as a multicenter study, and only two of the three studies were able to
include more than 200 patients [256, 258, 305]. The need for more multicenter studies should be
emphasized, because these studies will provide a stronger basis for subsequent generalization of any
findings. Participation from different regions and countries in such studies also should be
encouraged to facilitate generalization even more to an extent of a possible global practice change.
Because of the cost of large-scale trials, a step-wise approach to consider potential problems and
feasibility is desirable. An initial pilot study before proceeding with a larger multicenter trial is
beneficial. In this regard, the BLING I feasibility study has now led to the design of large clinical
outcome study, BLING II. BLING I was a prospective, multicenter, double-blind, double dummy,
pilot RCT enrolling 60 critically ill patients from 5 ICUs across Australia and Hong Kong [166].
The primary end-point of the study was to establish the PK separation between CI and IB in terms
of achieving plasma antibiotic concentrations above the MIC of causative pathogens. The PK
findings in BLING I demonstrated significant differences in plasma antibiotic concentrations above
MIC favouring the CI group (CI; 81.8 % versus IB; 28.6 %, p = 0.001) thus supporting the notion of
PK/PD superiority associated with CI administration. Clinical cure also was superior in the CI
group (CI; 70.0 % versus IB; 43.3 %, p = 0.037). Other relevant findings include the feasibility of
the proposed randomization and blinding process used by the BLING I investigators and the
suggestion of appropriate surrogate end-points for survival to be utilized in a multicenter study.
Thus, based on the findings from BLING I, BLING II was designed with rigorous and stringent
methods to answer the ultimate question of whether administration of beta-lactam antibiotics by CI
122
will result in improved outcomes for patients with severe sepsis. BLING II is a phase II,
multicenter, double-blinded, RCT that will recruit critically ill patients with severe sepsis in several
ICUs in New Zealand as well as Australia and Hong Kong. The Australian National Health and
Medical Research Council (NHMRC)-funded clinical trial aims to compare the effects of two
approaches to the administration of beta-lactam antibiotics (i.e., CI versus IB) on ICU-free days up
to day 28.
5.2.7 Conclusion
Although numerous PK/PD data from various in vitro and in vivo experimental studies favour the
use of CI dosing, the current clinical data are less convincing and insufficient to instigate a global
shift from conventional bolus dosing. However, this lack of convincing data may be due to several
methodological flaws and inconsistencies among the available studies, thus contributing towards
insufficient power to detect any significant differences between CI and IB, if they exist. Based on
the published literature, it can be concluded that CI of beta-lactams will not be beneficial to all
patients, but may potentially be beneficial in specific subsets of patients. If any patient group is
likely to benefit from CI, it may be critically ill patients with severe infections. If benefits from CI
do exist in critically ill patients, a large-scale, prospective, multinational trial with a robust design is
required. A step-wise approach to conduct such clinical trials has begun and already shows promise.
A phase II study involving 420 patients is about to start and will provide high quality information to
confirm or refute the need for a pivotal phase III double-blinded RCT of CI versus IB dosing of
beta-lactam antibiotics in critically ill patients with sepsis.
123
5.3 Conclusion
This chapter describes numerous limitations associated with previous studies in this area, which has
reduced the quality of any findings related to whether CI or IB administration of beta-lactam
antibiotics should be preferred in critically ill patients with severe sepsis. The data presented in this
chapter also highlighted that previous studies lacked a design that was sufficient to explore the
effect of both dosing approaches with regards to clinical outcomes, and some involved small patient
numbers. Other methodological flaws associated with previously published studies include an
absence of allocation sequence generation and allocation concealment, possibly leading to selection
bias. Masking or blinding of health care providers was also not adequately addressed making
detection bias a possibility in most of these studies. Thus, it is critical for future clinical studies to
address these limitations in order to conduct a methodologically sound and robust RCT. In addition
to these methodological flaws, most previous studies recruited participants with low burden of
disease and with highly susceptible microorganisms. Such subject selection may mask the potential
advantages of CI of beta-lactams in critically ill patients with severe sepsis where PK alterations
will be more pronounced. There are no apparent benefits of one approach over the other in the
management of highly susceptible pathogens. If many patients with highly susceptible pathogens
are included in a study, the sample size required to show a clinical difference between CI and IB
dosing will rise dramatically. Hence, future studies should focus on recruiting critically ill patients
with severe sepsis that are at risk of infection by less-susceptible pathogens to determine if true
differences exist between the two dosing approaches.
124
Chapter 6: Continuous beta-lactam infusion in critically ill patients with
severe sepsis: A prospective, two-centre, open-labelled, randomized
controlled trial
6.1 Synopsis
Although CI has been suggested as one of the methods to optimize beta-lactams dosing in critically
ill patients, most clinical outcome studies have failed to demonstrate a clinical advantage over
conventional IB dosing in terms of clinical cure and patient survival. Meta-analyses of these
outcome studies have also not found any significant clinical benefits favouring CI over IB dosing.
However, the efficacy of CI administration in critically ill patients has not been investigated in
high-quality RCTs. Most of the available studies recruited heterogeneous patient groups and have
important methodological inconsistencies that may mask any possible merits of CI dosing, if they
exists in critically ill patients. However, three recent RCTs which utilized a more rigorous and
stringent methodology have reported some clinical outcome advantages favouring CI administration
of beta-lactam antibiotics. Hence, this chapter aims to address all the methodological limitations of
previous studies by performing a methodologically sound and robust prospective RCT to
investigate the clinical and PK/PD outcomes associated with CI and IB dosing of beta-lactam
antibiotics in a cohort of critically ill patients with severe sepsis.
125
6.2 Manuscript entitled “BLISS: Beta-Lactam Infusion in Severe Sepsis: a
prospective, two-centre, open-labelled, randomized controlled trial of
continuous versus intermittent beta-lactam infusion in critically ill patients with
sepsis”
The manuscript entitled “BLISS: Beta-Lactam Infusion in Severe Sepsis: a prospective, two-centre,
open-labelled, randomized controlled trial of continuous versus intermittent beta-lactam infusion in
critically ill patients with sepsis” has been accepted for publication in the Intensive Care Medicine
(2016).
The co-authors contributed to the manuscript as follows: Conception and development of the study
design was performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz, Dr. Helmi Sulaiman, Dr.
Mohd-Basri Mat-Nor, under the guidance of Prof. Jason A. Roberts. Literature review was
performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz, under the guidance of Prof. Jason A.
Roberts. Data collection was performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz, Dr. Helmi
Sulaiman, Dr. Vineya Rai, Dr. Kang K. Wong, Dr. Mohd. S. Hasan and Azrin N. Abd Rahman.
Sample bioanalysis was performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz, and Janattul-
Ain Jamal, under the supervision of Dr. Steven C. Wallis. Data analysis was performed by the PhD
candidate, Mohd-Hafiz Abdul-Aziz, under the supervision of Prof. Jason A. Roberts. The PhD
candidate took the leading role in manuscript preparation and all co-authors reviewed and
contributed to the final draft of the manuscript.
The accepted version of this manuscript is presented and incorporated in this chapter. However,
some text, tables and figures may have been inserted at slightly different positions to fit the overall
style of the thesis. Numbering of pages, tables and figures may also change to fit the thesis
requirements. Manuscript references have been collated with all other references in the thesis.
Permission has been granted by the publisher and copyright owner, Springer Science + Business
Media (License no: 3886900914112), to reproduce the manuscript in this Thesis.
126
BLISS: Beta-Lactam Infusion in Severe Sepsis: a prospective, two-centre, open-labelled,
randomized controlled trial of continuous versus intermittent beta-lactam infusion in
critically ill patients with severe sepsis
Authors
Mohd H. Abdul-Aziz (1, 2), Helmi Sulaiman (3), Mohd-Basri Mat-Nor (4), Vineya Rai (5), Kang K.
Wong (5), Mohd S. Hasan (5), Azrin N. Abd Rahman (2, 6), Janattul A. Jamal (7), Steven C. Wallis
(1), Jeffrey Lipman (1, 8), Christine E. Staatz (6, 9), Jason A. Roberts (1, 6, 8)
Affiliation
(1) Burns, Trauma & Critical Care Research Centre, The University of Queensland, Brisbane,
Australia.
(2) School of Pharmacy, International Islamic University of Malaysia, Kuantan, Pahang, Malaysia.
(3) Infectious Diseases Unit, Department of Medicine, Faculty of Medicine, University of Malaya,
Kuala Lumpur, Malaysia.
(4) Department of Anaesthesiology and Intensive Care, School of Medicine, International Islamic
University of Malaysia, Kuantan, Pahang, Malaysia.
(5) Department of Anaesthesiology, Faculty of Medicine, University of Malaya, Kuala Lumpur,
Malaysia.
(6) School of Pharmacy, The University of Queensland, Brisbane, Australia.
(7) Department of Pharmacy, Hospital Tengku Ampuan Afzan, Kuantan, Malaysia.
(8) Department of Intensive Care Medicine, Royal Brisbane and Women’s Hospital, Brisbane,
Australia.
(9) Australian Centre of Pharmacometrics, Brisbane, Australia.
Running title: Continuous beta-lactam infusion.
Keywords: antibiotics, critically ill, intermittent bolus, pharmacokinetics, pharmacodynamics,
prolonged infusion.
Corresponding author:
Prof. Jason A. Roberts,
Burns, Trauma & Critical Care Research Centre, The University of Queensland,
Level 3, Ned Hanlon Building, Royal Brisbane & Women’s Hospital,
Herston, Queensland, 4029 Australia
127
Ph +61736361847; Fax +61736463524
Email: [email protected]
Alternate corresponding author:
Mohd H. Abdul-Aziz
Burns, Trauma and Critical Care Research Centre, The University of Queensland,
Level 3, Ned Hanlon Building, Royal Brisbane & Women’s Hospital,
Herston, Queensland, 4029 Australia
Ph +61736361847; Fax +61736463524
Email: [email protected]
128
6.2.1 Abstract
6.2.1.1 Purpose
This study aims to determine if CI is associated with better clinical and PK/PD outcomes compared
to IB dosing in critically ill patients with severe sepsis.
6.2.1.2 Methods
This was a two-centre, RCT of CI versus IB dosing of beta-lactam antibiotics, which enrolled
critically ill participants with severe sepsis who were not on RRT. The primary outcome was
clinical cure at 14 days after antibiotic cessation. Secondary outcomes were PK/PD target
attainment, ICU-free days and ventilator-free days at day 28 post-randomization, 14- and 30-day
survival, and time to WCC normalization.
6.2.1.3 Results
One-hundred and forty (140) participants were enrolled with 70 participants each allocated to CI
and IB dosing. CI participants had higher clinical cure rates (56% versus 34%, p = 0.011) and
higher median ventilator-free days (22 days versus 14 days, p <0.043) than IB participants. PK/PD
target attainment rates were higher in the CI arm at 100% fT>MIC than the IB arm on Day 1 (97%
versus 70%, p <0.001) and Day 3 (97% versus 68%, p <0.001) post-randomization. There was no
difference in 14-day or 30-day survival between the treatment arms.
6.2.1.4 Conclusions
In critically ill patients with severe sepsis not receiving RRT, CI demonstrated higher clinical cure
rates and had better PK/PD target attainment compared to IB dosing of beta-lactam antibiotics.
Continuous beta-lactam infusion may be mostly advantageous for critically ill patients with high
levels of illness severity and not receiving RRT.
Malaysian National Medical Research Register ID: NMRR-12-1013-14017.
129
6.2.2 Introduction
Mortality due to severe infections remains persistently high worldwide, ranging from 30-50% in
patients with severe sepsis and 40-80% in those with septic shock [1]. Optimized antibiotic therapy
is an intervention likely to improve treatment outcomes in severe sepsis [7].
Beta-lactam antibiotics display time-dependent activity where bacterial killing and treatment
efficacy correlates with fT>MIC [12]. Based on this characteristic, maximal beta-lactam effects are
considered more likely with CI rather than traditional IB dosing. IB dosing may produce beta-
lactam concentrations below the MIC for much of the dosing interval [13], particularly in the ICU
where pathogens with higher MIC values are relatively common [5].
Although CI has been shown to be superior to IB dosing in numerous pre-clinical and PK/PD
simulation studies [13], most clinical comparative trials have failed to demonstrate a clinical
advantage of CI dosing in terms of clinical cure and/or patient survival [151, 172, 248, 254, 256-
258, 266]. Meta-analyses of prospective studies have also not found any significant clinical benefits
favouring CI over IB dosing [217, 240, 267]. However, most of the studies recruited heterogeneous
patient groups and have important methodological flaws, potentially masking any possible benefits
of CI dosing in critically ill patients [217, 240]. Three recent RCTs have demonstrated some clinical
outcome advantages favouring CI administration of beta-lactam antibiotics when only critically ill
patients were recruited [166, 242, 243]. As most of the current evidence was derived from Western
countries, the wider applicability of CI dosing remains largely unexplored in some regions which
are plagued by more resistant pathogens and patients with higher levels of sickness severity [332].
Data from such areas, particularly from the South East Asian countries, are vital in order to support
a global practice change if subsequent studies identify CI benefits in critically ill patients. The
primary aim of the Beta-Lactam Infusion in Severe Sepsis (BLISS) study was to determine if CI of
beta-lactam antibiotics is associated with improved clinical outcomes compared to IB dosing in a
large cohort of critically ill patients with severe sepsis in a Malaysian ICU setting.
Findings of the BLISS study were presented, in part, at the 55th Interscience Conference on
Antimicrobial Agents and Chemotherapy (ICAAC), San Diego, CA, September 18-21, 2015 [414].
130
6.2.3 Methods
6.2.3.1 Study design
The BLISS study was a prospective, two-centre, open-labelled, RCT of CI versus IB dosing of beta-
lactam antibiotics in critically ill patients with severe sepsis from the two following Malaysian
ICUs: (1) Tengku Ampuan Afzan Hospital (HTAA), Kuantan; and (2) University Malaya Medical
Centre (UMMC), Kuala Lumpur. Institutional ethics approval was obtained at each participating
site. Written informed consent to participate in the study was obtained from each participant or their
legally-authorized representative prior to study enrolment. The study was registered with the
Malaysian National Medical Research Register (ID: NMRR-12-1013-14017).
6.2.3.2 Participants and randomization
ICU patients were eligible for inclusion if they met all of the following criteria: (a) adult (≥18
years); (b) developed severe sepsis (defined as presumed or confirmed infection with new organ
dysfunction) [24] in the previous 48 hours; (c) indication for cefepime, meropenem or
piperacillin/tazobactam with <24 hours therapy at time of assessment; (d) and expected ICU stay
greater than 48 hours. Patients were excluded if they: (a) were receiving RRT; (b) had impaired
hepatic function (defined as total bilirubin >100 µmol/mL); (c) were receiving palliative treatment;
(d) had inadequate central venous catheter access; (e) or death was deemed imminent.
Participants currently receiving, or about to receive, cefepime, meropenem or
piperacillin/tazobactam were randomly allocated to either a CI (intervention arm) or IB (control
arm) treatment arm. Randomization was performed using a computer program
(http://www.randomization.com) based on blocks of four with an allocation ratio of 1:1 stratified by
participating sites. Following study enrolment, an unblinded pharmacist on-duty who was
responsible for preparing medications, determined treatment allocation by opening sequentially-
numbered opaque, sealed and stapled envelopes. The tamper-evident envelopes were prepared by an
unblinded investigator and were provided to each participating site.
6.2.3.3 Intervention
Each antibiotic dose was prepared by an unblinded ICU pharmacist on-duty in accordance with
standard pharmacy practice. The dosing regimen was determined by the treating intensivist, with
guidance from a local dosing protocol (Table 6-1). To ensure early achievement of therapeutic beta-
131
lactam exposures in the intervention arm, a single loading dose infused over 30 minutes was given
at initiation of antibiotic therapy meaning that the CI group received a larger antibiotic dose on Day
1 post-randomization compared to those in the IB arm (Table 6-1). The study antibiotic was
administered until, (a) the treating intensivist decided to cease the drug; (b) the participant withdrew
from the study; (c) ICU discharge; or (d) ICU death. All subsequent patient management including
addition of other antibiotics and non-study drugs was at the treating intensivist’s discretion.
Table 6-1: Antibiotic dosing protocol according to treatment arm in the BLISS study
Antibiotic and treatment arm Dosing regimen
Cefepime
Intervention arm
(continuous infusion)
Day 1: 2 g IV loading dose (infused over 30 minutes)
followed by 2 g IV (infused over 480 minutes) every 8
hours
Day 2 onwards: 2 g IV (infused over 480 minutes)
every 8 hours
Control arm
(intermittent bolus dosing)
2 g IV (infused over 30 minutes) every 8 hours
Meropenem
Intervention arm
(continuous infusion)
Day 1: 1 g IV loading dose (infused over 30 minutes)
followed by 1 g IV (infused over 480 minutes) every 8
hours
Day 2 onwards: 1 g IV (infused over 480 minutes)
every 8 hours
Control arm
(intermittent bolus dosing)
1 g IV (infused over 30 minutes) every 8 hours
Piperacillin/tazobactam
Intervention arm
(continuous infusion)
Day 1: 4 g/0.5 g IV loading dose (infused over 30
minutes) followed by 4 g/0.5 g IV (infused over 360
minutes) every 6 hours
Day 2 onwards: 4 g/0.5 g IV (infused over 360 minutes)
every 6 hours
Control arm
(intermittent bolus dosing)
4 g/0.5 g IV (infused over 30 minutes) every 6 hours
Abbreviation: IV, intravenous.
132
6.2.3.4 Outcomes and measurements
The primary end-point investigated in this study was clinical cure at 14 days after antibiotic
cessation. Clinical cure was rated as either: (a) Resolution: complete disappearance of all signs and
symptoms related to infection; (b) Improvement: a marked or moderate reduction in disease severity
and/or number of signs and symptoms related to infection; or (c) Failure: insufficient lessening of
the signs and symptoms of infection to qualify as improvement, death or indeterminate for any
reason. Clinical cure was scored as a “Yes” for resolution and a “No” for all other findings (i.e.,
sum of 2 and 3 above). Secondary end-points investigated in this study include: (a) PK/PD target
attainment; (b) ICU-free days at day 28; (c) ventilator-free days at day 28; (d) survival at day 14; (e)
survival at day 30; and (f) time to WCC normalization. The definitions used to assess these end-
points are described in Table 6-2.
Table 6-2: Definitions used for primary and secondary clinical end-points
Primary end-pointa Definition and description
Clinical cure Clinical cure was evaluated at 14 days after cessation of study
antibiotic and was rated as:
1. Resolution: complete disappearance of all signs and
symptoms related to infection.
2. Improvement: a marked or moderate reduction in
disease severity and/or number of signs and symptoms
related to infection.
3. Failure: insufficient lessening of the signs and
symptoms of infection to qualify as improvement,
including death or indeterminate (i.e. no evaluation
possible, for any reason).
Clinical cure was scored as a “Yes” for resolution and a “No”
for all other findings (i.e., sum of 2 and 3 above).
Secondary end-pointsb,c,d Definition and description
PK/PD – 50% fT>MIC Free (unbound) drug concentration maintained above the MIC
of the causative pathogen for at least 50% of dosing interval
(i.e., mid-interval drug concentration). For CI participants, this
was the first sample taken over a 24-hour interval.
133
PK/PD – 100% fT>MIC Free (unbound) drug concentration maintained above the MIC
of the causative pathogen for at least 100% of dosing interval
(i.e., trough drug concentration or steady-state drug
concentration). For CI participants, this was the second sample
taken over a 24-hour interval.
ICU-free days at day 28 The number of days the participant was ICU-free after
successful transfer to a general ward in the first 28 days post-
randomization. ICU-free days were 0 if a patient died or stayed
in the ICU for ≥28 days.
Ventilator-free days at day 28 The number of days the participant was ventilator-free (for at
least 48 consecutive hours) in the first 28 days post-
randomization. Ventilator-free days were 0 if a patient died or
required mechanical ventilation for ≥28 days.
14-day survival Survival at day 14 post-randomization.
30-day survival Survival at day 30 post-randomization
Time to WCC normalization The number of days from randomization to the first identified
date when WCC was ≥4.0x109/L and ≤10.0x109/L (for at least
48 consecutive hours) in participants who had values outside
this range.
Abbreviation: CI, continuous infusion; ICU, intensive care unit; MIC, minimum inhibitory
concentration; PK/PD, pharmacokinetic/pharmacodynamic; WCC, white cell count.
Legend:
aClinical cure was evaluated by a blinded clinician if the participant was still in the ICU or by
blinded review of the medical records if the participant was discharged from the ICU.
bPharmacokinetic/pharmacodynamic (PK/PD) analysis only included participants with complete
pharmacokinetic data (i.e., those who had both trough and mid-interval concentrations collected on
both sampling days).
cPK/PD analysis was performed on Days 1 and 3 post-randomization.
dWhere a pathogen was isolated, the “surrogate MIC” was defined by the European Committee on
Antimicrobial Susceptibility Testing (EUCAST) MIC90 data. Where no pathogen was formally
identified, the MIC breakpoints for P. aeruginosa (8 mg/L for cefepime, 2 mg/L for meropenem
and 16 mg/L for piperacillin/tazobactam) were inferred as the “surrogate MIC”. Participants who
were infected with beta-lactam resistant pathogens were excluded from PK/PD analysis.
134
For the secondary end-point of PK/PD target attainment, assessment was made by comparing the
unbound (free) beta-lactam concentrations against the “surrogate MIC” of the pathogen. This MIC
was inferred from EUCAST database. PK/PD target attainment was evaluated as a dichotomous
variable and scored as a “Yes” if measured drug concentration exceeded pathogens “surrogate
MIC”. Only participants with complete PK data were included in the analysis (i.e., those who had
both trough and mid-interval drug concentrations collected on Days 1 and 3 post-randomization).
Participants who were infected with beta-lactam resistant pathogens were excluded from the PK/PD
analysis.
Independent investigators who were blinded to treatment allocation, patient care and management
assessed the end-points of interest. These investigators were not working in the participating ICUs
during this study.
Demographic, clinical and treatment-related variables were collected. Microbiological cultures were
collected from the most likely infection site immediately before or during antibiotic treatment. CLCR
was estimated using the Cockcroft-Gault formula [341]. APACHE II [340] and SOFA [52] scores
were calculated and recorded within 24 hours of ICU admission. Comorbidity was scored using the
Charlson comorbidity index [415]. Adverse events during the study period were recorded and
evaluated as “almost certainly”, “probably”, “possibly”, or “unlikely” to be caused by study
antibiotics [416]. Data were collected until participants were discharged from hospital or death.
6.2.3.5 Pharmacokinetic sampling and bioanalysis
PK sampling was coordinated by unblinded investigators and was performed on Days 1 and 3 post-
randomization. Blood (5 mL) was collected into lithium-heparinised tubes. For participants in the
IB arm, mid-dosing interval and trough concentrations were collected. For participants in the CI
arm, two blood samples were taken at least 12 hours apart. All blood samples were immediately
refrigerated at 4°C and within 1 hour, centrifuged at 3000 rpm for 10 minutes to separate plasma.
Plasma samples were frozen at -80°C within 24 hours of collection. Frozen plasma samples were
shipped on dry ice by a commercial courier and assayed at the BTCCRC, the University of
Queensland, Australia.
Beta-lactam concentration in plasma was measured, after protein precipitation, by a validated HPLC
method with ultraviolet detection [417], on a Shimadzu Prominence (Shimadzu Corporation, Kyoto,
Japan) instrument. Samples were assayed in batches, alongside calibration standards and quality
135
control replicates at high, medium and low concentrations. All bioanalysis techniques were
conducted in accordance with regulatory standards [342]. Observed concentrations were corrected
for protein binding using published protein binding values (20% for cefepime, 2% for meropenem
and 30% for piperacillin) [99].
6.2.3.6 Sample size calculations
A sample size of 120 participants (60 in each treatment arm) was estimated to demonstrate a
statistical significant difference in the primary end-point (power 0.8, alpha 0.05). For clinical cure,
75% of patients in the intervention arm versus 45% in the control arm were estimated to achieve
clinical cure [166]. The final study sample size was increased to 140 participants (70 in each arm)
factoring in a 15-20% drop-out rate.
6.2.3.7 Statistical analysis
Statistical analyses were primarily performed on the ITT population. A mITT analysis was also
performed in all participants who received at least one dose of study antibiotic. A per-protocol (PP)
analysis was performed in all participants who received study antibiotic for ≥4 days.
Data are presented as median values with IQR for continuous variables and number and percentage
for categorical variables. Differences in free plasma antibiotic concentration and free plasma
antibiotic concentration to MIC ratio in the ITT population were analysed using a Mann-Whitney U
test and are graphically presented as box (median and IQR) and whisker (10-99 percentile) plots.
Primary and secondary end-points were compared between the two treatment arms using a
Pearson’s chi-square test or a Mann-Whitney U test as appropriate. For the primary end-point, sub-
group analyses (determined a priori) were performed according to the study beta-lactams used,
concomitant antibiotic treatment, infection sites and A. baumannii or P. aeruginosa infection. For
ICU-free days and ventilator-free days, results are presented for ICU survivors. A Kaplan-Meier
survival curve was constructed to compare survival trends at Day 14 and Day 30 in the ITT
population. Comparison of survival between the two treatment arms was performed using a log-
rank test with the hazard ratio (HR) and 95% confidence interval reported. A multivariate logistic
regression was constructed to identify significant predictors associated with cure, with OR and 95%
confidence interval reported. Biologically-plausible variables with a p-value ≤0.15 on univariate
analysis were considered for model building. A two-sided p-value of <0.05 was considered
statistically significant in all analyses. Statistical analysis was performed using IBM SPSS Statistics
22 (IBM Corporation, Armonk, New York).
136
6.2.4 Results
6.2.4.1 Baseline demographics and clinical characteristics
Participants were recruited from April, 2013 to July, 2014. The sites enrolled 55 and 85
participants, respectively. Two hundred and twenty patients were assessed for eligibility of whom
140 were randomized and 134 received at least one dose of the study antibiotic. One hundred and
twenty-six participants received ≥4 days of randomized treatment. The BLISS study CONSORT
flow diagram is presented in Figure 6-1 and details that the most common reason for patient
exclusion was presence of RRT on assessment (n = 32). The baseline characteristics of the ITT
population are presented in Table 6-3.
Figure 6-1: The BLISS study CONSORT flow diagram
137
Table 6-3: Baseline demographic and clinical characteristics of the intention-to-treat
population
Characteristic Intervention
(n = 70)
Control
(n = 70)
Age (years) 54 (42-63) 56 (41-68)
Male, n (%) 46 (66) 50 (71)
Body weight (kg) 70 (59-80) 65 (59-75)
Body mass index (kg/m2) 27 (23-30) 24 (22-29)
APACHE II 21 (17-26) 21 (15-26)
SOFA 8 (6-10) 7 (5-9)
Charlson comorbidity index 3 (1-5) 4 (2-6)
Serum creatinine concentration (µmol/L) 111 (73-118) 92 (59-158)
Cockcroft-Gault creatinine clearance (mL/min) 64 (43-98) 72 (41-122)
Pre-randomization ICU stay (days) 2 (2-5) 3 (2-6)
Pre-randomization antibiotic therapy, n (%) 52 (74) 56 (80)
Pre-randomization appropriate antibiotic therapy, n (%)a 38 (79) 41 (73)
Post-randomization ICU stay (days) 8 (5-10) 6 (4-13)
Duration of randomized treatment (days) 7 (5-9) 7 (5-9)
Mechanically-ventilated, n (%) 66 (52) 61 (48)
Post-randomization renal replacement therapy, n (%) 15 (21) 12 (17)
White cell count (x 109/L) 17 (13-25) 15 (13-20)
Study antibiotic, n (%)
Piperacillin/tazobactam 38 (54) 47 (67)
Meropenem 21 (30) 21 (30)
Cefepime 11 (16) 2 (3.0)
Pharmacokinetic sampling, n (%)b
Piperacillin/tazobactam 35 (92) 37 (79)
Meropenem 19 (91) 17 (81)
Cefepime 9 (82) 2 (100)
Concomitant antibiotic, n (%) 33 (47) 33 (47)
Azithromycin 13 (19) 12 (17)
Vancomycin 6 (9) 12 (17)
Metronidazole 6 (9) 10 (6)
Clindamycin 2 (3) 4 (6)
Aminoglycosides 3 (4) 3 (4)
Colistin 1 (1) 1 (1)
Otherc 7 (10) 5 (7)
Primary infection site, n (%)
Lung 46 (66) 36 (51)
138
Intra-abdominal 11 (16) 15 (21)
Blood 4 (6) 6 (9)
Urinary tract 2 (3) 3 (4)
Skin or skin structure 6 (9) 7 (10)
Central nervous system 1 (1) 3 (4)
Organ dysfunction, n (%)
Respiratory 46 (66) 44 (63)
Cardiovascular 40 (57) 37 (53)
Hematologic 18 (26) 12 (17)
Renal 17 (24) 10 (14)
Metabolic acidosis 4 (6) 3 (4)
Abbreviation: APACHE, Acute Physiology and Chronic Health Evaluation; ICU, intensive care
unit; SOFA, Sequential Organ Failure Assessment.
*Data are presented as median (interquartile range) or number (percentage).
Legend:
aAppropriate antibiotic therapy was assumed if a participant received at least one antibiotic (24
hours before study inclusion) which was effective against the isolated pathogen(s). Only
participants who had at least one organism identified was assessed (n = 104; intervention = 48,
control = 56).
bParticipants who had complete pharmacokinetic data i.e., those who had mid-dose and trough
concentrations on both sampling occasions.
cIncludes cloxacillin (n = 7), doxycycline (n = 2), co-trimoxazole (n = 2) and ciprofloxacin (n = 1).
139
The allocation of beta-lactam antibiotics was comparable between the treatment arms except for
cefepime where 11 participants were allocated to the intervention arm and only 2 to the control arm.
The median 24-hour antibiotic dose was not different between the intervention and control arms:
cefepime 6 g (IQR: 6-6) versus 6 g (2 participants), meropenem 3 g (IQR: 3-3) versus 3 g (IQR: 3-
3) and piperacillin/tazobactam 18 g (IQR: 18-18) versus 18 g (IQR: 9-18), respectively. The median
antibiotic treatment course was 7 days (IQR: 5-9) in both treatment arms. Thirty-three participants
(47%) in both treatment arms received concomitant antibiotic therapy as part of their treatment. The
median ICU stay was 8 days (IQR: 5-10) for participants in the intervention arm and 6 days (IQR:
4-13) in the control arm (p = 0.544). The median ventilator days were 6 (IQR: 3-7) and 5 (IQR: 3-
11) for participants in the intervention and control arms (p = 0.662), respectively. There was no
difference between the groups of proportion of patients with appropriate initial therapy.
Microbiological characteristics of the ITT population are shown in Table 6-4. Forty-eight
participants (69%) in the CI arm and 56 participants (80%) in the IB arm had at least one causative
pathogen identified before or during the course of treatment. Eighteen participants (34%) in the CI
arm and 26 participants (46%) in the IB arm had polymicrobial infections during the course of
treatment. The most prevalent Gram-negative pathogens in the intervention arm were P. aeruginosa
(37%) and A. baumannii (25%) and for the control arm, A. baumannii (31%) and Klebsiella
pneumoniae (23%). There were 9 participants (6%) who had a non-susceptible pathogen identified
as the primary causative organism: intervention arm 6 participants (9%) versus control arm 3
participants (4%). The median “surrogate MIC” values were similar in both treatment arms: 8 mg/L
(IQR: 4-8) for cefepime, 2 mg/L (IQR: 2-2) for meropenem, and 16 mg/L (IQR: 8-16) for
piperacillin/tazobactam.
140
Table 6-4: Microbiological characteristics of the intention-to-treat population
Characteristic Intervention
(n = 70)
Control
(n = 70)
Participants who had organisms identified, n (%) 48 (69) 56 (80)
Gram-positive, n (%) 12 (20) 25 (33)
Staphylococcus aureus 5 (42) 11 (44)
Staphylococcus epidermidis 4 (33) 6 (24)
Enterococcus faecalis 0 (0) 3 (12)
Streptococcus intermedius 1 (8) 2 (8)
Streptococcus pneumoniae 2 (17) 1 (4)
Mycoplasma pneumoniae 0 (0) 2 (8)
Enterococcus faecium 0 (0) 1 (4)
Streptococcus anginosus 0 (0) 1 (4)
Streptococcus constellatus 0 (0) 1 (4)
Gram-negative, n (%) 49 (80) 52 (68)
Acinetobacter baumannii 12 (25)a 16 (31)b
Pseudomonas aeruginosa 18 (37) 10 (19)
Klebsiella pneumoniae 9 (18)c 12 (23)
Escherichia coli 5 (10)d 5 (10)
Proteus mirabilis 2 (4) 2 (4)
Bulkholderia cepacia 1 (2) 1 (2)
Chlamydophila pneumoniae 0 (0) 2 (4)
Stenotrophomonas maltophilia 1 (2) 1 (2)
Bulkholderia pseudomallei 1 (2) 0 (0)
Enterobacter aerogenes 0 (0) 1 (2)
Morganella morganii 0 (0) 1 (2)
Serratia marcescens 0 (0) 1 (2)
Polymicrobial infection, n (%) 18 (38) 26 (46)
Legend:
aFour isolates were multi-drug resistant A. baumannii.
bThree isolates were multi-drug resistant A. baumannii.
cOne isolate was extended-spectrum beta-lactamase (ESBL) K. pneumoniae.
6.2.4.2 Outcome measures
Primary and secondary end-points in the ITT population and the clinical outcome for the sub-groups
of interest are presented in Table 6-5. Participants in the intervention arm had higher clinical cure
rates and shorter median time to WCC normalization. The number needed to treat with CI to
improve the likelihood of clinical cure is three patients. Additionally, CI administration
141
demonstrated higher clinical cure rates than IB dosing in participants who had respiratory infection,
participants who received piperacillin/tazobactam and in those without concomitant antibiotic
treatment (Table 6-5). Differences in PK/PD target attainment rates were significantly higher in the
intervention group at 100% fT>MIC on Day 1 and Day 3 post-randomization. At 28 days, there was
no difference in median ICU-free days but median ventilator-free days were significantly higher in
the participants of the intervention arm. There was no difference in survival at 14 days or 30 days
between the treatment arms (Figure 6-2).
Findings in the mITT and PP population were similar to those reported in the ITT population and
the primary and secondary end-points for these groups are presented in Tables 6-6 and 6-7.
6.2.4.3 Outcome measures predictors
Significant predictors associated with clinical cure in the ITT population are presented in Tables 6-8
and 6-9. Based on the most parsimonious logistic regression model, CI administration of beta-
lactam antibiotics (OR 3.21, 95% confidence interval 1.48-6.94; p = 0.003), pre-randomization
antibiotic therapy (OR 2.85, 95% confidence interval 1.12-7.23; p = 0.028), non-bacteraemia
related infection (OR 11.73, 95% confidence interval 1.30-105.94; p = 0.028), lower APACHE II
score (OR 0.95, 95% confidence interval 0.90-0.99; p = 0.036), and meropenem (OR 6.54, 95%
confidence interval 1.48-28.90; p = 0.013) or piperacillin/tazobactam administration (OR 4.21, 95%
confidence interval 1.06-16.64; p = 0.041) (as opposed to cefepime administration) were all
statistically significant predictors for clinical cure.
142
Table 6-5: Primary and secondary end-points by treatment arm in the intention-to-treat population and the sub-groups of interest
Primary end-point Intervention
(n = 70)
Control
(n = 70)
Absolute difference
(95% CI)
Significance
(p-value)a,b
Clinical cure for ITT population, n (%) 39 (56) 24 (34) 22 (-0.4 to -0.1) 0.011
Clinical cure by antibiotic, n (%)c
Piperacillin/tazobactam 22 (58) 15 (32) 26 (-0.4 to -0.1) 0.016
Meropenem 14 (67) 8 (38) 29 (-0.5 to 0.1) 0.064
Cefepime 3 (27) 1 (50) 23 (-0.3 to 0.7) 1.000
Clinical cure by concomitant antibiotic treatment, n (%)d
Yes 14 (42) 13 (39) 3 (-0.3 to 0.2) 0.802
No 25 (68) 11 (30) 38 (-0.6 to -0.2) 0.001
Clinical cure by site of infection, n (%)e
Lung 27 (59) 12 (33) 25 (-0.4 to -0.1) 0.022
Clinical cure by A. baumannii or P. aeruginosa infection, n
(%)f
Yes 13 (52) 6 (25) 27 (-0.5 to 0.1) 0.052
No 10 (44) 12 (38) 6 (-0.3 to 0.2) 0.655
Secondary end-points Intervention
(n = 70)
Control
(n = 70)
Absolute difference
(95% CI)
Significance
(p-value)a,b
PK/PD target attainment, n (%)g
50% fT>MIC on day 1 56 (98) 49 (93) 5 (-0.2 to 0.1) 0.194
100% fT>MIC on day 1 55 (97) 37 (70) 27 (-0.4 to -0.1) <0.001
50% fT>MIC on day 3 56 (98) 49 (93) 5 (-0.2 to 0.1) 0.194
100% fT>MIC on day 3 55 (97) 36 (68) 29 (-0.4 to -0.1) <0.001
143
ICU-free days 20 (12-23) 17 (0-24) 3 (-4 to 1) 0.378
ICU survivorsh 21 (19-23) 21 (14-24) (-2 to 2) 0.824
Ventilator-free days 22 (0-24) 14 (0-24) 8 (-7 to 0) 0.043
ICU survivorsi 23 (21-25) 21 (0-25) 2 (-6 to 0) 0.076
14-day survival, n (%) 56 (80) 50 (71) 9 (-0.2 to 0.1) 0.237
30-day survival, n (%) 52 (74) 44 (63) 11 (-0.3 to 0.1) 0.145
WCC normalization days 3 (2-7) 8 (4-15) 5 (1 to 5) <0.001
Abbreviation: CI, confidence interval; ICU, intensive care unit; ITT, intention-to-treat; PK/PD, pharmacokinetic/pharmacodynamic; WCC, white cell
count; 50% fT>MIC, unbound (free) plasma concentration at 50% of the dosing interval (mid-interval concentration) was above the causative pathogens
MIC; 100% fT>MIC, unbound (free) plasma concentration at 100% of the dosing interval (trough concentration) was above the causative pathogens
MIC.
Legend:
aRepresents the p-value between the intervention arm versus the control arm and values in bold indicate significant difference between the two
treatment arms (p <0.05).
bContinuous variables were compared using Mann-Whitney U test as data were non-normally distributed as indicated by Kolmogorov-Smirnov test.
Dichotomous variables were compared using Pearson chi-square test or Fisher’s exact test as appropriate.
cNumber of participants analysed: (1) piperacillin/tazobactam (n = 85; intervention = 38, control = 47), (2) meropenem ( n = 42; intervention = 21,
control = 21), and (3) cefepime (n = 13; intervention = 11, control = 2).
dNumber of participants analysed: (1) patients who received concomitant antibiotics ( n = 66; intervention = 33, control = 33) and (2) patients who did
not receive concomitant antibiotics (n = 74; intervention = 37, control = 37).
eNumber of participants analysed: lung (n = 82; intervention = 46, control = 36).
fNumber of participants analysed: (1) A. baumannii or P. aeruginosa infection (n = 49; intervention = 25, control = 24) and (2) other infections (n =
55; intervention =23, control = 32).
144
gOnly participants with complete pharmacokinetic data (n = 119; intervention = 63, control = 56) and those who were infected with beta-lactam
susceptible pathogens (n = 110; intervention = 57, control = 53) were included in the analysis.
hOnly participants who survived at ICU discharge was included in this sub-analysis (57 and 53 participants in the intervention and control arm,
respectively).
iOnly mechanically-ventilated participants who survived at ICU discharge was included in this sub-analysis (53 and 46 participants in the intervention
and control arm, respectively).
145
Table 6-6: Primary and secondary end-points by treatment arm in the modified intention-to-treat population
Primary end-point Intervention
(n = 68)
Control
(n = 66)
Absolute difference
(95% CI)
Significance
(p-value)a,b
Clinical cure for mITT population, n (%)
Clinical cure, n (%) 39 (57.4) 23 (34.8) 22.5 (-0.4 to -0.1) 0.009
Secondary end-points Intervention
(n = 68)
Control
(n = 66)
Absolute difference
(95% CI)
Significance
(p-value)a,b
PK/PD target attainment, n (%)c
50% fT>MIC on day 1 54 (98.2) 48 (94.1) 4.1 (-0.1 to 0.1) 0.350
100% fT>MIC on day 1 53 (96.4) 37 (72.5) 23.9 (-0.4 to -0.1) 0.001
50% fT>MIC on day 3 54 (98.2) 48 (94.1) 4.1 (-0.1 to 0.1) 0.350
100% fT>MIC on day 3 53 (96.4) 36 (70.6) 25.8 (-0.4 to -0.1) <0.001
ICU-free days 20 (11-23) 16 (0-23) 4 (-4 to 0) 0.287
ICU survivorsd 21 (19-23) 21 (12-24) 0 (-3 to 1) 0.565
Ventilator-free days 22 (0-24) 14 (0-24) 8 (-7 to 1) 0.045
ICU survivorse 23 (21-25) 20 (0-25) 3 (-6 to 0) 0.050
14-day survival, n (%) 54 (79.4) 47 (71.2) 8.2 (-0.2 to 0.1) 0.271
30-day survival, n (%) 50 (73.5) 42 (63.6) 9.9 (-0.2 to 0.1) 0.217
WCC normalization days 3 (2-7) 8 (4-15) 5 (1-5) <0.001
Abbreviation: CI, confidence interval; ICU, intensive care unit; mITT, modified intention-to-treat population; PK/PD,
pharmacokinetic/pharmacodynamic; WCC, white cell count; 50% fT>MIC, unbound (free) plasma concentration at 50% of the dosing interval (mid-
interval concentration) was above the causative pathogens MIC; 100% fT>MIC, unbound (free) plasma concentration at 100% of the dosing interval
(trough concentration) was above the causative pathogens MIC.
146
Legend:
aRepresents the p-value between the intervention arm versus the control arm and values in bold indicate significant difference between the two
treatment arms (p <0.05).
bContinuous variables were compared using Mann-Whitney U test as data were non-normally distributed as indicated by Kolmogorov-Smirnov test.
Dichotomous variables were compared using Pearson chi-square test or Fisher’s exact test as appropriate.
cOnly participants with complete pharmacokinetic data (n = 115; intervention = 61, control = 54) and those who were infected with beta-lactam
susceptible pathogens (n = 106; intervention = 55, control = 51) were included in the analysis.
dOnly participants who survived at ICU discharge was included in this sub-analysis (55 and 50 participants in the intervention and control arm,
respectively).
eOnly mechanically-ventilated participants who survived at ICU discharge was included in this sub-analysis (52 and 43 participants in the intervention
and control arm, respectively).
147
Table 6-7: Primary and secondary end-points by treatment arm in the per-protocol population
Primary end-point Intervention
(n = 66)
Control
(n = 60)
Absolute difference
(95% CI)
Significance
(p-value)a,b
Clinical cure for PP population, n (%)
Clinical cure, n (%) 39 (59.1) 20 (33.3) 25.8 (-0.4 to -0.1) 0.004
Secondary end-points Intervention
(n = 66)
Control
(n = 60)
Absolute difference
(95% CI)
Significance
(p-value)a,b
PK/PD target attainment, n (%)
50% fT>MIC on day 1 54 (98.2) 42 (93.6) 4.6 (-0.2 to 0.1) 0.332
100% fT>MIC on day 1 53 (96.4) 34 (72.3) 24.1 (-0.4 to -0.1) 0.001
50% fT>MIC on day 3 54 (98.2) 42 (93.6) 4.6 (-0.2 to 0.1) 0.332
100% fT>MIC on day 3 53 (96.4) 34 (72.3) 24.1 (-0.4 to -0.1) 0.001
ICU-free days 20 (12-23) 17 (0-23) 3 (-4 to 0) 0.276
ICU survivorsd 21 (19-23) 21 (14-24) 0 (-3 to 1) 0.662
Ventilator-free days 22 (0-24) 14 (0-24) 8 (-7 to 0) 0.025
ICU survivorse 23 (21-25) 19 (1-25) 4 (-7 to 0) 0.027
14-day survival, n (%) 53 (80.3) 42 (70.0) 10.3 (-0.3 to 0.1) 0.180
30-day survival, n (%) 49 (74.2) 38 (63.3) 10.9 (-0.3 to 0.1) 0.186
WCC normalization days 3 (2-6) 8 (5-15) 5 (2 to 5) <0.001
Abbreviation: CI, confidence interval; ICU, intensive care unit; PK/PD, pharmacokinetic/pharmacodynamic; PP, per-protocol; WCC, white cell
count; 50% fT>MIC, unbound (free) plasma concentration at 50% of the dosing interval (mid-interval concentration) was above the causative pathogens
MIC; 100% fT>MIC, unbound (free) plasma concentration at 100% of the dosing interval (trough concentration) was above the causative pathogens
MIC.
148
aRepresents the p-value between the intervention arm versus the control arm and values in bold indicate significant difference between the two
treatment arms (p <0.05).
bContinuous variables were compared using Mann-Whitney U test as data were non-normally distributed as indicated by Kolmogorov-Smirnov test.
Dichotomous variables were compared using Pearson chi-square test or Fisher’s exact test as appropriate.
cOnly participants with complete pharmacokinetic data (n = 110; intervention = 60, control = 50) and those who were infected with beta-lactam
susceptible pathogens (n = 102; intervention = 55, control = 47) were included in the analysis.
dOnly participants who survived at ICU discharge was included in this sub-analysis (54 and 45 participants in the intervention and control arm,
respectively).
eOnly mechanically-ventilated participants who survived at ICU discharge was included in this sub-analysis (51 and 40 participants in the intervention
and control arm, respectively).
149
Table 6-8: Differences in clinical characteristics and treatment-related variables between participants who demonstrated clinical cure
and clinical failure in the ITT population
Variable Cure (n = 63) Failure (n = 77) p-valuea,b
Age (years) 55 (45-63) 53 (40-68) 0.774
Male, n (%) 46 (73.0) 50 (64.9) 0.306
Body weight (kg) 70 (56-80) 68 (60-75) 0.875
Body mass index (kg/m2) 25 (22-30) 25 (22-29) 0.793
APACHE II 19 (16-22) 23 (17-28) 0.009*
SOFA 7 (6-9) 8 (5-10) 0.695
Charlson comorbidity index 3 (2-5) 4 (2-6) 0.126*
Serum albumin (g/dL) 26 (21-30) 22 (17-28) 0.037*
Serum creatinine concentration (µmol/L) 94 (63-176) 120 (66-165) 0.697
Cockcroft-Gault creatinine clearance (mL/min) 68 (50-115) 59 (38-97) 0.268
Pre-randomization ICU stay (days) 2 (2-5) 3 (2-6) 0.580
Pre-randomization antibiotic therapy, n (%) 24 (28.1) 34 (44.2) 0.469
Pre-randomization appropriate antibiotic therapy, n (%) 34 (82.9) 45 (71.4) 0.180
Duration of randomized treatment (days) 7 (6-9) 6 (4-8) 0.040*
Mechanically-ventilated, n (%) 57 (90.5) 70 (90.9) 0.930
Post-randomization renal replacement therapy, n (%) 7 (11.1) 20 (26.0) 0.027*
Surgery within 24 hours of study inclusion, n (%) 24 (38.1) 34 (44.2) 0.469
White cell count (x 109/L) 16 (13-21) 16 (14-21) 0.769
Pre-randomization antibiotic therapy, n (%) 44 (69.8) 64 (83.1) 0.063*
Study antibiotic, n (%)
Piperacillin/tazobactam 37 (58.7) 48 (62.3) 0.357
Meropenem 22 (34.9) 20 (26.0)
Cefepime 4 (6.3) 9 (11.7)
150
Concomitant antibiotic use, n (%) 27 (42.9) 39 (50.6) 0.358
Treatment
Continuous infusion 39 (61.9) 31 (40.3) 0.011*
Intermittent bolus 24 (38.1) 46 (59.7)
Primary infection site, n (%)
Lung 39 (61.9) 43 (55.8) 0.469
Intra-abdominal 13 (20.6) 13 (16.9) 0.570
Blood 1 (1.6) 9 (11.7) 0.023*
Urinary tract 3 (4.8) 2 (2.6) 0.657
Skin or skin structure 6 (9.5) 7 (9.1) 0.930
Central nervous system 1 (1.6) 3 (3.9) 0.627
Organ dysfunction, n (%)
Respiratory 40 (63.5) 50 (64.9) 0.859
Cardiovascular 37 (58.7) 40 (51.9) 0.422
Hematologic 13 (20.6) 17 (22.1) 0.836
Renal 13 (20.6) 14 (18.2) 0.714
Metabolic acidosis 4 (6.3) 3 (3.9) 0.701
Participants who had organisms identified, n (%) 41 (65.1) 63 (81.8) 0.024*
Gram-negative infections, n (%) 35 (85.4) 45 (71.4) 0.099*
PK/PD ratio
Concentration at 50% of the dosing interval to MIC D1 5.8 (3.4-15.0) 6.5 (3.6-16) 0.547
151
Concentration at 100% of the dosing interval to MIC D1 4.5 (2.1-12.4) 4.7 (2.1-10.1) 0.823
Concentration at 50% of the dosing interval to MIC D3 7.9 (3.8-17.0) 6.9 (13.2-16.1) 0.583
Concentration at 100% of the dosing interval to MIC D3 6.3 (2.2-13.8) 4.2 (1.7-12.8) 0.282
Abbreviation: APACHE, Acute Physiology and Chronic Health Evaluation; ICU, intensive care unit; MIC, minimum inhibitory concentration;
PK/PD, pharmacokinetic/pharmacodynamic; SOFA, Sequential Organ Failure Assessment.
*Data are presented as median (interquartile range) or number (percentage).
Legend:
aBold values indicate statistical significance (p <0.05).
bRepresents variable that was included in the multivariate logistic regression model.
152
Table 6-9: Factors predicting clinical cure in the ITT population
Variable All factors included in the model Final model
Odds ratio
(95% CI)
Significance
(p-value)
Odds ratio
(95% CI)
Significance
(p-value)
Factors predicting clinical cure
Continuous infusiona 3.08 (1.38-6.94) 0.007 3.21 (1.48-6.94) 0.003
Bacteremiab 0.10 (0.01-0.92) 0.042 0.09 (0.09-0.770) 0.028
Pre-randomization antibiotic therapyc 2.74 (1.02-7.32) 0.045 2.85 (1.12-7.23) 0.028
APACHE II score (per 1-point increase) 0.95 (0.90-1.00) 0.060 0.95 (0.90-0.99) 0.036
Study drugd 0.075 0.047
Piperacillin/tazobactam 4.15 (1.01-17.01) 0.049 4.21 (1.06-16.64) 0.041
Meropenem 6.04 (1.28-28.47) 0.023 6.54 (1.48-28.90) 0.013
Cefepime 1.0 - 1.0 -
Causative organism identifiede 0.54 (0.22-1.33) 0.180 - -
Duration of randomized treatment (per 1-day increase) 1.04 (0.98-1.09) 0.208 - -
Albumin (per 1 g/dL increase) 1.02 (0.96-1.08) 0.597 - -
Charlson comorbidity index (per 1-point increase) 0.98 (0.85-1.13) 0.781 - -
Goodness-of-fit
Hosmer-Lemeshow test X2 = 6.96, df = 8 0.541 X2 = 3.843, df = 8 0.871
Abbreviation: APACHE, Acute Physiology and Chronic Health Evaluation; CI, confidence interval; df, degree of freedom; X2, chi-square.
*Bold values indicate statistical significance (p <0.05).
Legend:
aOR compares continuous infusion relative to IB dosing of beta-lactam antibiotics.
bOR compares bacteraemia relative to other sites of infections.
cOR compares those who received pre-randomization antibiotic therapy relative to those who did not.
153
dOR compares piperacillin/tazobactam and meropenem relative to cefepime.
eOR compares those who had at least one causative organism identified relative to those who did not.
154
6.2.4.4 Pharmacokinetic/pharmacodynamic data
The data describing free (unbound) plasma antibiotic concentration and free (unbound) plasma
antibiotic concentration to MIC ratio are presented in Figures 6-2 and 6-3, respectively. Plasma
antibiotic concentrations measured at 50% and 100% of the dosing interval were relatively higher in
the intervention group on Day 1 and Day 3 post-randomization (Figure 6-2). The ratio of plasma
antibiotic concentration to MIC was also relatively higher in the intervention group on both
sampling days for all study antibiotics (Figure 6-3).
Figure 6-2: Free plasma antibiotic concentration by beta-lactam antibiotics and treatment
groups measured at (a) 50% of the dosing interval on Day 1 (b) 100% of the dosing interval
on Day 1 (c) 50% of the dosing interval on Day 3 and (d) 100% of the dosing interval on Day 3
Abbreviation: CI, continuous infusion; IB, intermittent bolus.
*Median, interquartile range and range are presented.
**An asterisk indicates a significant difference between continuous infusion and intermittent bolus
dosing (p <0.05).
155
Figure 6-3: Free plasma antibiotic concentration to minimum inhibitory concentration (MIC)
ratio by beta-lactam antibiotics and treatment groups measured at (a) 50% of the dosing
interval on Day 1 (b) 100% of the dosing interval on Day 1 (c) 50% of the dosing interval on
Day 3 and (d) 100% of the dosing interval on Day 3
Abbreviation: CI, continuous infusion; IB, intermittent bolus.
*Median, interquartile range and range are presented.
**An asterisk indicates a significant difference between continuous infusion and intermittent bolus
dosing.
***PK/PD ratio is defined as the ratio between the measured plasma antibiotic concentration at
50% or 100% of the dosing interval and the causative pathogen’s “surrogate MIC” (i.e., not actual
MIC values), as defined in Table 6-2. Note that a ratio of 1 at 100% of the dosing interval is
generally considered to be a minimum PK/PD target during beta-lactam therapy.
6.2.4.5 Adverse events
No adverse events occurred during study participation. A total of 18 deaths occurred during receipt
of the study drug: CI arm 7 participants versus IB arm 11 participants.
156
6.2.5 Discussion
In this RCT, we found that continuous beta-lactam infusion demonstrated higher clinical cure rates
and better PK/PD target attainment compared to IB dosing in critically ill patients with severe
sepsis. Other significant benefits for CI participants in two other surrogate clinical end-points were
increased ventilator-free days and a reduced time to WCC normalization. Given that these results
were derived from a population of ICU patients with severe sepsis, who were not on extra-corporeal
renal support, our findings provide further evidence that CI of beta-lactam antibiotics are likely to
be beneficial for patients with a high level of illness severity not receiving RRT. Although three
recent RCTs have also reported similar findings [166, 242, 243], our current work remains unique
considering that we recruited patients from a different geographical region, one which is rarely
investigated but commonly associated with higher illness severity, than those commonly reported.
Clinical evidence supporting improved patient outcome with CI of beta-lactams has been mixed,
varying from no significant effect [151, 172, 241, 256-258] to significant patient benefits [166, 242,
243, 248, 254, 266]. We would note that there is yet to be a report suggesting inferior patient
outcomes when CI is used. Meta-analyses of the above prospective clinical studies have failed to
comprehensively demonstrate the superiority of CI over IB dosing in terms of clinical cure and
patient survival [217, 240, 267]. However, a particularly noteworthy feature in most of these studies
has been the inclusion of non-critically ill patients, whereas the patients who may be most likely to
benefit from CI dosing are critically ill patients with high illness severity [166, 242]. Critically ill
patients, particularly those with severe sepsis, commonly develop extreme physiological
derangements, which may severely reduce antibiotic exposure, particularly when IB dosing is
employed [7, 291]. Patients that received beta-lactams via CI dosing in our study were ten-times
more likely to achieve 100% fT>MIC on Day 1 (p <0.001) and nine-times more likely to achieve
100% fT>MIC on Day 3 (p <0.001). As maintaining 100% fT>MIC in critically ill patients is associated
with improved patient outcomes [28], we believe that the observed clinical cure difference in the
ITT analysis (absolute difference of 22%) favouring CI dosing may be partly explained by the
relative ability of CI dosing to achieve the target PK/PD exposure more consistently than IB dosing
in patients with severe sepsis [164, 291]. Importantly, CI participants in this study were three-times
more likely to achieve clinical cure when compared with IB participants, even after controlling for
confounding variables (OR 3.21, 95% confidence interval 1.48-6.94; p = 0.003).
Significant advantages of CI over IB for beta-lactam antibiotics were also observed in two recent
RCTs of critically ill patients with severe sepsis. In a prospective, multicentre, double-blind, RCT
157
(BLING I; n = 60), Dulhunty et al., [166] showed that participants in the CI treatment arm
demonstrated greater fT>MIC (82% versus 29%; p = 0.001) and higher clinical cure rates (77%
versus 50%; p = 0.032) compared to the IB arm. In a single-centre RCT which recruited 240
critically ill Czech participants, Chytra et al., [242] reported higher microbiological cure rates in the
CI treatment arm as opposed to the IB arm (91% versus 78%; p = 0.020). Neither study
demonstrated significant mortality advantages.
Despite these results, disease severity is only one of the many variables which can influence the
outcome of CI versus IB dosing in critically ill patients. This was recently highlighted in a
multicentre, double-blind, RCT (BLING II; n = 420) [241]. Despite recruiting only patients with
severe sepsis, Dulhunty et al., found no significant difference between participants in both treatment
arms, in all five clinical end-points evaluated. In their study, the absolute difference in clinical cure
between CI and IB participants was 3% in favour of CI dosing compared with the 22% in the
present BLISS study. In contrast to BLISS, the BLING II trial included patients receiving RRT
(~25% of participants) and this inclusion criterion may reduce PK/PD exposure differences between
CI and IB dosing because patients with reduced drug clearances are less likely to manifest sub-
therapeutic antibiotic exposures [244, 245] and consequently, are less likely to benefit from altered
dosing approaches such as CI administration. Interestingly, all five clinical studies which
demonstrated patient benefits with CI dosing only recruited critically ill patients with conserved
renal function [166, 242, 243, 248, 254].
Other than recruiting participants with a low burden of disease, most clinical studies have also
isolated pathogens which are highly susceptible to the study antibiotics [166, 172, 241-243, 248,
254, 256-258, 266]. PK/PD principles states that IB dosing will be just as likely as CI to achieve
target exposures when MICs are low [13] with treatment failures more likely with IB dosing when
less susceptible pathogens are present [151, 290, 293]. In the present study, although actual MIC
values were not available, 41% of the causative pathogens were either A. baumannii or P.
aeruginosa which mostly have higher MICs to the study antibiotics [418], thereby reducing the
likelihood of achieving therapeutic concentrations with IB dosing. However, it should also be
highlighted that benefits of CI may not be apparent in some geographical regions with different
microbiology and antibiotic resistance patterns. Importantly, use of combination therapy to treat
infections caused by Gram-negative pathogens was infrequent in this study, which may differ from
practices in other centres.
158
This study has several limitations. Participants were only recruited from two centres in one country
which may limit the generalizability of the findings to other treatment settings. Despite the baseline
characteristics of the treatment arms being relatively well balanced, CI participants manifested
higher median SOFA scores on admission compared to IB participants. Even though this typically
translates into a reduced likelihood of survival, it is possible that CI participants may have been
selectively provided with additional monitoring in the ICU to account for their illness severity,
which may influence clinical outcomes. Furthermore, clinical outcomes were evaluated by an
independent investigator and unlike a specialized review committee, the former strategy may be
more likely to introduce biased observations towards one of the treatment allocations. However, the
possibility of bias in this study should be very low as the assessor had no knowledge of treatment
allocation now role in patient management and was not working in the participating centres during
the study period. We also acknowledge the limitation of the Cockcroft-Gault formula in estimating
renal function in this cohort, and that measured CLCR would be more accurate [419]. Neither
unbound plasma concentrations nor concentrations at the sites of infections were measured in this
study, although all drugs have relatively low protein binding [99]. As MIC reporting is rare in
Malaysia, we have used “surrogate MIC” values, using EUCAST MIC breakpoints, in our primary
end-point analyses. Accordingly, this approach will exaggerate the magnitudes of PK/PD target
non-attainment in the IB treatment arm relative to the CI arm if actual MIC values were used.
Although actual MIC values would have been preferable, we believe that our approach resembles
the real-life clinical approach where the MIC of a pathogen is rarely available upon antibiotic
commencement [27]. Although data on concomitant antibiotics were available, we did not evaluate
the PK/PD of those antibiotics. This study was not powered to test the effect of CI versus IB dosing
on survival but has provided useful information that can be used for sample size determination of a
larger multicentre RCT seeking to quantify any survival benefits of CI dosing.
6.2.6 Conclusion
In critically ill patients with severe sepsis not receiving RRT, CI administration was associated with
higher clinical cure rates and better PK/PD target attainment compared to IB dosing for three
common beta-lactam antibiotics. Our findings suggest that beta-lactam CI may be most beneficial
for critically ill patients with a high level of illness severity, who are infected with less susceptible
microorganisms and that are not receiving RRT. A large-scale, prospective, multinational clinical
study is required to ascertain whether the potential benefits of continuous beta-lactam infusion do
indeed translate into survival benefit in critically ill patients with severe sepsis.
159
6.3 Conclusion
The findings in this chapter showed that CI of beta-lactam antibiotics demonstrated higher clinical
cure rates and better PK/PD target attainment as opposed to IB dosing in a large cohort of critically
ill patients with severe sepsis. Furthermore, data from the BLISS study further corroborates data
from previous studies which suggest that CI may not improve outcomes for all critically ill patients,
but only certain sub-populations. Based on the findings presented in this chapter, CI of beta-lactam
antibiotics are likely to be advantageous for critically ill patients with a high level of illness severity
who are not receiving RRT. Additionally, this alternative dosing strategy may improve the
outcomes from severe infections which are more likely to be associated with less susceptible
pathogens. Although the BLISS study was not powered to investigate survival benefit between the
two dosing approaches, its data provides useful information that can be used for the design of a
large-scale, prospective, multinational RCT to ascertain whether the perceived benefits of CI do
indeed translate into mortality reduction in critically ill patients with severe sepsis.
160
Chapter 7: Optimizing antibiotic treatment in critically ill patients via
pharmacokinetic/pharmacodynamic principles
7.1 Synopsis
The patterns of antibiotic resistance have significantly changed over the last few decades with
increasing antibiotic resistance currently being regarded as one of the major health crises.
Organisms such as E.coli and K. pneumoniae, which were previously considered relatively
innocuous, are frequently becoming resistant to currently available antibiotics and therefore,
treating these infections has become a challenge for clinicians world-wide. Furthermore, it was
predicted that these worrying trends of increasing resistance will continue to progress with the
biggest threats arising from Gram-negative pathogens. The rate at which these pathogens develop
resistance is likely to far outpace the rate of development of new antibiotics. Abuse and overuse of
antibiotics in hospitals, particularly in the ICU, has caused a dramatic increase in antibiotic
resistance and this phenomenon currently threatens to shorten the clinical life-span of the existing
antibiotic armamentarium. Clinicians now are forced to find new methods that optimize the use of
presently available antibiotics. Although more commonly explored to maximize patient outcomes,
emerging data are suggesting that the PD-based dosing approach is equally crucial to prevent the
emergence of resistance by avoiding sub-optimal antibiotic dosing. The aims of this chapter are to
describe the relevance of PK/PD characteristics of different antibiotic classes on the development of
antibiotic resistance and to suggest alternative treatment strategies that can be employed not only to
maximize patient outcomes but also to minimize the emergence of resistance.
161
7.2 Manuscript entitled “Applying pharmacokinetic/pharmacodynamic
principles in critically ill patients: optimizing efficacy and reducing resistance
development”
The manuscript entitled “Applying pharmacokinetic/pharmacodynamic principles in critically ill
patients: optimizing efficacy and reducing resistance development” has been accepted for
publication in the Seminars in Respiratory and Critical Care Medicine (2015; 36(1): 136-153).
The co-authors contributed to the manuscript as follows: Conception and development of the study
design was performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz, under the guidance of Prof.
Jason A. Roberts, Prof. Jeffrey Lipman and Prof. Johan W. Mouton. Literature review was
performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz, under the guidance of Prof. Jason A.
Roberts, Prof. Johan W. Mouton and Prof. William W. Hope. The PhD candidate took the leading
role in manuscript preparation and all co-authors reviewed and contributed to the final draft of the
manuscript.
The accepted version of this manuscript is presented and incorporated in this chapter. However,
some text, tables and figures may have been inserted at slightly different positions to fit the overall
style of the thesis. Numbering of pages, tables and figures may also change to fit the thesis
requirements. Manuscript references have been collated with all other references in the thesis.
Permission has been granted by the publisher and copyright owner, Thieme, to reproduce the
manuscript in this Thesis.
162
Applying pharmacokinetic/pharmacodynamic principles in critically ill patients: optimizing
efficacy and reducing resistance development
Authors
Mohd H. Abdul-Aziz (1), Jeffrey Lipman (1, 2), Johan W. Mouton (3, 4), William W. Hope (5),
Jason A. Roberts (1, 2, 5).
Affiliation
(1) Burns, Trauma & Critical Care Research Centre, The University of Queensland, Brisbane,
Australia.
(2) Department of Intensive Care Medicine, Royal Brisbane & Women’s Hospital, Brisbane,
Australia.
(3) Department of Medical Microbiology, Radboud University, Nijmegen Medical Centre,
Nijmegen, The Netherlands.
(4) Department of Medical Microbiology and Infectious Diseases, Erasmus MC, Rotterdam, The
Netherlands.
(5) Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool,
United Kingdom.
Keywords: antibacterial; resistance; pharmacodynamics; pharmacokinetics.
Address for correspondence:
Prof. Jason A. Roberts,
Burns, Trauma & Critical Care Research Centre,
The University of Queensland,
Level 3, Ned Hanlon Building, Royal Brisbane & Women’s Hospital,
4029 Butterfield Street, Brisbane, Queensland,
Australia.
Ph: +61736464108; Fax: +61736463542
Email: [email protected]
163
7.2.1 Abstract
The recent surge in MDR pathogens combined with the diminishing antibiotic pipeline has created a
growing need to optimize the use of our existing antibiotic armamentarium, particularly in the
management of ICU patients. Optimal and timely PK/PD target attainment has been associated with
an increased likelihood of clinical and microbiological success in critically ill patients. Emerging
data, mostly from in vitro and in vivo studies, suggest that optimization of antibiotic therapy should
not only aim to maximize clinical outcomes but to also include the suppression of resistance. The
development of antibiotic dosing regimens that adheres to the PK/PD principles may prolong the
clinical lifespan of our existing antibiotics by minimizing the emergence of resistance. This present
article summarizes the relevance of PK/PD characteristics of different antibiotic classes on the
development of antibiotic resistance. Based on the available data, we propose dosing
recommendations that can be adopted in the clinical setting, in order to maximize therapeutic
success and limit the emergence of resistance in the ICU.
164
7.2.2 Introduction
Severe infections leading to severe sepsis and septic shock are prominent causes of morbidity and
mortality in critically ill patients. In a large multicentre point prevalence study involving 1265 ICUs
across 75 countries, 51% of ICU patients were classified as infected on the day of study with a
mortality rate of 25.3% [31]. Data from a large European ICU study has further corroborated the
diagnosis of severe sepsis as a global healthcare crisis, whereby the condition accounted for 26.7%
of ICU admissions [33]. In this study, the corresponding mortality in patients with severe sepsis and
septic shock were concerning with rates of 32.2% and 54.1%, respectively [33]. Despite an
emerging trend for improved survival over recent years [29, 30, 32], the mortality rate in this patient
cohort remains unacceptably high worldwide [1]. In the context of the financial burden incurred, the
United States itself is currently spending between $121 and $263 billion annually on critically ill
patients, which represents more than 8% of the country’s total healthcare expenditure [46].
To address these persisting poor patient outcomes, significant amounts of research have been
directed towards optimizing the provision of care for the critically ill patient. Indeed improving
antibiotic therapy is a core focus of treatment of infection-driven pathologies like sepsis. There is
strong evidence to suggest that optimal antibiotic therapy may have a greater impact on patients’
survival when compared to novel treatment strategies such as the use of activated protein C [408],
antithrombin III [420], and intensive insulin therapy in these patients [4, 421-423]. However, the
process of optimizing antibiotic therapy can be a daunting challenge in the ICU for a variety of
reasons. Extreme physiological derangements that can occur from either pharmacological
interventions or the natural course of critical illness may alter antibiotic concentrations and
consequently reduce antibiotic exposure in critically ill patients [6]. In addition, pathogens that are
usually isolated in the ICU differ from the general wards, as they are commonly less susceptible to
common antibiotics [334, 335]. Indeed, antibiotic dosing that does not account for these features is
likely to lead to sub-optimal antibiotic exposure and therapeutic failures. In addition, sub-optimal
antibiotic exposure is also highly implicated as a contributing factor to the escalation of antibiotic
resistance. Resistance to antibiotics certainly is considered a global healthcare crisis which currently
threatens the advances of modern medicine [148].
The recent surge in MDR pathogens combined with the diminishing antibiotic pipeline has created a
growing need to optimize the use of the existing antibiotic armamentarium, particularly in the ICU.
Although critically ill patients constitute fewer than 10% of all hospital admissions, their antibiotic
consumption is 10-times greater compared to patients in all other wards [383, 424, 425]. The
165
rampant antibiotic use (or misuse) has therefore, in part, contributed to the alarming increase in the
MDR pathogens such as the ESBL and carbapenemase-producing Gram-negative pathogens.
Notably, Gram-negative pathogens such as A. baumannii and P. aeruginosa, as well as members of
the Enterobacteriaceae family such as E. coli and K. pneumoniae, which were previously considered
relatively innocuous, have impressively out-manoeuvred our current antibiotics. Previously simple
infections have become increasingly difficult to treat over a short period of time [399]. Moreover,
infections caused by these pathogens frequently result in poor clinical outcomes, including higher
mortality and prolonged hospitalization [426-428]. The healthcare community concerns are
legitimate, as the emergence of resistance is likely to far outpace the rate of development of new
antibiotics. In light of these grim prospects, clinicians are currently forced to reintroduce older
antibiotics as treatment options (e.g., colistin and fosfomycin) and vigorously search for new
strategies that can optimize the use of our presently available antibiotics.
The aim of this review is to describe the relevance of PK exposure and PD characteristics of
different antibiotic classes on the development of antibiotic resistance. We will discuss the relevant
antibiotic resistance descriptors and review how target drug exposures differ between predicting
treatment success and suppressing resistance development. Based on the current data, we will also
suggest dosing strategies that ultimately exploit antibiotic PD, which increase the likelihood of
treatment success as well as minimizing the emergence of resistance.
7.2.3 Applied clinical pharmacology of antibiotics
Pharmacology is the science of drugs including the study of drug actions. Two principle areas of
pharmacology are PK and PD. Traditionally, antibiotic dosing and administration were only
optimized, in accordance to the PK/PD principles, for clinical efficacy (i.e., clinical and
microbiological cure) with an associated collateral damage being the selection of resistant
pathogens. Emerging data are suggesting that the PD-based dosing approach should not only aim to
maximize clinical outcomes but to also include the suppression of resistance. Indeed, the
application of PK/PD principles have been shown to minimize the risk of emergence of resistance
by avoiding ineffective antibiotic exposure, which consequently exerts a selective pressure to
pathogens, rather than to eradicate them [149]. This selective pressure causes the elimination of
highly susceptible, but not the more resistant phenotypes, leading to future colonization and
potential infection with poorly susceptible pathogens.
166
7.2.3.1 Pharmacokinetic considerations
PK refers to the study of concentration changes of a drug over a given time period. This branch of
pharmacology describes the rates and processes from absorption to distribution of drugs to
elimination mechanism via metabolism or excretion. Some of the examples of important PK
parameters are; (a) Vd, (b) CL, (c) Cmax, (d) Cmin and, (e) AUC0-24. Among these however,
alterations in the primary PK parameters, namely Vd and CL, are probably the most influential in
determining altered antibiotic dosing and exposure. Changes in antibiotic Vd and CL have been
commonly observed in critically ill patients and the relevance of the two phenomena in influencing
effective antibiotic exposure has been reviewed in detail elsewhere [7].
7.2.3.2 Pharmacodynamic considerations
PD describes the relationship between PK exposure and pharmacological effect. For antibiotics, PD
relates the antibiotic concentration to the ability of an antibiotic to kill or inhibit the growth of a
pathogen. Generally, this relationship is often described by linking the concentration of an antibiotic
with the corresponding MIC of the offending pathogen. For an antibiotic, it is the free or unbound
concentration that is responsible for the antibacterial activity [429]. Numerous studies have
demonstrated that different antibiotics have different PD properties and can be readily categorized
as the following; (a) fT>MIC, (b) Cmax/MIC and, (c) AUC0-24/MIC. These fundamental PK/PD indices
for antibiotics’ activity are further illustrated in Figure 7-1. It should be noted, that the AUC/MIC
was never considered in earlier studies, and that many data retrieved from older literature only
established the relationship between Cmax/MIC and effect parameter. From a theoretical point of
view most of the antibiotics should show a relationship with AUC and effect rather than Cmax.
Based on the PK/PD indices, antibiotics can be classified into three categories that by and large
reflect their modes of bacterial killing [12, 24, 430]. The first category includes antibiotics where
the difference between the maximum effect and minimum effect is relatively large, and increasing
concentrations result in progressively increased killing. These are therefore also sometimes called
concentration dependent antibiotics, and include aminoglycosides and quinolones. For these
antimicrobials AUC/MIC describes their antibiotic activity best, and, mainly because AUC/MIC is
closely correlated to Cmax/MIC, Cmax/MIC as well [386, 431]. On the other hand, time-dependent
antibiotics’ activity, such as the beta-lactams, is strongly correlated with fT>MIC and as such,
prolonging the duration of effective drug exposure should be the priority when this antibiotic class
is used [11, 28]. However, some antibiotics such as the glycopeptides are more complex where they
are found to display both concentration- and time-dependent kill characteristics [11]. For these
167
Figure 7-1: The graphical illustration of fundamental pharmacokinetic and pharmacodynamic parameters of antibiotics on a hypothetical
concentration-time curve
Abbreviation: AUC, area under the concentration-time curve; Cmax, maximum drug concentration; Cmin, minimum drug concentration; MIC,
minimum inhibitory concentration; T>MIC, duration of time that drug concentration remains above MIC.
168
antibiotics, the ratio of AUC0-24/MIC describes their antibiotic activity best and higher thresholds
are closely related with successful clinical outcome [432].
7.2.4 Pharmacokinetic/pharmacodynamic considerations and the resistance
descriptors
Most of the earlier research on optimizing antibiotic dosing was only focused on maximizing
clinical and microbiological cure and not minimization of the emergence of antibiotic resistance. To
date, most of the data describing PK/PD and its association with antibiotic resistance comes from
pre-clinical, albeit advanced, PK/PD infection models. However, the antibiotic exposure required
for clinical efficacy and resistance suppression is markedly different. For instance, the antibiotic
exposure-response relationship for clinical efficacy is monotonic or can also be described as a
sigmoidal relationship in which, no measurable antibiotic effect is expected at lower drug exposures
whilst larger exposures are expected to augment the bactericidal effect up to a certain threshold. In
contrast, the relationship between antibiotic exposure and the selection of resistant mutants is
markedly non-monotonic and has the shape of an inverted “U” where resistant mutants are
amplified with initial antibiotic exposure and then slowly decline with increasing exposure up to an
optimal threshold that ultimately prevents resistance amplifications [433-436]. The inverted U-
shape seems to follow a log normal distribution [437]. Additionally, Jumbe et al., found that an
AUC0-24/MIC of ≥110 for levofloxacin, which was twice that was necessary for optimal bactericidal
effect, was required to suppress drug-resistant population of P. aeruginosa in a mouse-thigh
infection model [401]. This information, among other similar observations, has indicated that the
magnitude of the PK/PD indices for resistance suppression is generally different and higher than the
thresholds required for clinical success [405, 434, 438, 439]. Therefore, antibiotic dosing that only
aims to optimize clinical efficacy may potentially amplify resistance formation by selecting mutant
bacterial strains with reduced drug susceptibility. With enhanced knowledge on antibiotic PK/PD
over recent years, important hypotheses and concepts, such as the mutant selection window (MSW)
and mutant prevention concentrations (MPC), have been proposed to provide potential explanations
as to how sub-optimal antibiotic exposure may amplify the selection of resistant bacterial strains.
Additionally, the dynamics of bacterial population under various dosing regimen can be described
using mixture models, where changes in susceptible and resistant sub-populations in relation to
drug concentrations are quantified [401, 435, 438, 440, 441].
169
7.2.4.1 Mutant selection window
The term “selective window” (SW) which was firstly coined by Baquero [442, 443] refers to a
critical range of antibiotic concentrations in which drug-resistant bacterial mutants could be
selectively enriched and amplified when exposed to concentrations in this zone. Subsequent in vitro
studies, utilizing mycobacteria treated with fluoroquinolones, were able to define the boundaries for
the critical zone of antibiotic concentrations and this concept was later renamed as the MSW [444-
446]. The studies that attempted to describe MSW further suggested that these concentration zones
are those between the MIC of the susceptible pathogens and that of the least susceptible mutants.
Figure 7-2 graphically illustrate the concept of MSW and its relevance in the development of
resistant mutants. The MSW describes the range of antibiotic concentrations where resistant
mutants may be selectively amplified and these concentration zones are those between the MIC of
the susceptible pathogens and that of the least susceptible mutants i.e., MPC. In area (A) of Figure
7-2, which is below the MIC, no resistant mutants are expected to grow, as there is no selective
pressure in this area. In area (C) of Figure 7-2, which is above the MPC, the growth of resistant
mutants is severely restricted and highly unlikely as the exposure in the area is able to suppress the
growth of the least susceptible pathogens. On the contrary, the selection of resistant mutants would
be most intense in area (B) of Figure 7-2, which is also known as MSW. Conversely, the longer the
time spent by an antibiotic in this concentration zone, the greater the opportunity for resistant
mutants to be selected and amplified. In addition to this, the formation of the resistant mutants was
observed to be most intense in the bottom portion as opposed to the upper portion of the selection
window [447]. The existence of such “dangerous” concentration zones was further corroborated by
several in vitro [436, 448-450] and in vivo experimental studies [451-454].
The MSW hypothesis is potentially important, as contemporary antibiotic dosing tends to produce
drug concentrations within the critical zone where they selectively amplify the growth of resistant
mutants. Essentially, the higher the percentage of time (t) spent by an antibiotic within the MSW
(tMSW), the greater the opportunity for resistant mutants to be selected and amplified. Furthermore,
the continuous and prolonged “careless” practice of “dosing to only cure” in the ICU eventually
leads to the resistant mutants being the dominant bacterial population and it is only at this point that
surveillance studies would be alerted to the emergent resistant isolates. The MSW has been defined
for many of the fluoroquinolones and some of the beta-lactams against various microorganisms
[455-457]. Nevertheless, this concept is currently considered as a relatively new idea and has not
been investigated in many infective pathologies, nor its relevance at the site of infection. Hence, its
170
clinical relevance in optimizing antibiotic dosing to avoid the MSW remains unclear and warrants
further investigation.
Figure 7-2: Graphical illustration of the mutant selection window and mutant prevention
concentration on a hypothetical concentration-time curve
Abbreviation: Cmax, maximum drug concentration; Cmin, minimum drug concentration; MIC,
minimum inhibitory concentration; MPC, mutant prevention concentration; MSW, mutant selection
window.
7.2.4.2 Mutant prevention concentration
The concept of MPC, which was derived from the MSW hypothesis, refers to the antibiotic
concentration that corresponds to the MIC of the least susceptible mutants in a colony [444, 446].
While MIC refers to the lower boundary, the MPC essentially represents the upper boundary of
concentrations in the MSW in which the enrichment of resistant mutants are expected to be severely
hindered. Conversely, antibiotic dosing that aims to achieve concentrations higher than the MPC, as
opposed to MIC, theoretically provides both an optimal bactericidal effect as well as resistance
suppression. Furthermore, the ratio of AUC0-24 to MPC (AUC0-24/MPC) as opposed to AUC0-24/MIC
is also suggested as a predictor of the development of resistance in several in vitro and in vivo
evaluations as MIC quantifications generally ignore mutant sub-populations [433, 455, 458, 459].
The argument has been mostly tested in in vitro studies for fluoroquinolones where the mutant-
171
restrictive thresholds of AUC0-24/MPC were approximately one-third of those AUC0-24/MIC values
[436, 460].
The MPC has been described mostly for fluoroquinolones, although data for other classes of
antibiotics are emerging [455, 461, 462]. Quantifying MPC thresholds for individual antibiotics
should be one of the priorities in the development of dosing guidelines especially earlier in the
process of evaluation and screening of new compounds. Although the concept seems appealing, the
application however is not straightforward as the doses needed to achieve the MPC are usually
higher than those for curing patients and exceed those that are registered for those antibiotics. There
are also examples where these concentrations are unattainable for some antibiotic-pathogen
combination [445, 462]. In addition, a trade-off between an increased risk of adverse effects with
minimizing antibiotic resistance is a difficult consideration in clinical practice. In such cases,
combining two or three antibiotics with overlapping PD properties may be warranted.
7.2.4.3 Application of experimental mixture models
A mixture models examine resistance development by describing the population dynamics of
antibiotic-susceptible and -resistant bacteria during the course of treatment. Susceptible and
resistant sub-populations respond differently to different antibiotic concentrations. In a murine-
thigh infection model, Jumbe et al., investigated the impact of bacterial inoculum on the required
levofloxacin exposure in the eradication of total P. aeruginosa population [401]. The mice were
inoculated with either 107 or 108 bacteria per thigh and levofloxacin was initiated after 2 hours. The
investigators demonstrated that the exposure intensity which is required for maximal levofloxacin
activity increases (by 2-5 fold) as the size of the inoculum increases by 1-log. This phenomenon
occurs as a larger bacterial challenge constitutes larger population of resistant mutants, which are
less susceptible to antibiotic therapy. The investigators also employed a complex mathematical
model to analyse their findings simultaneously in order to calculate an exposure that would amplify
resistant population and also, exposure that would restrict the enrichment of the population. A free
AUC/MIC ratio of 110 and 36 was predicted to prevent the emergence and amplify resistant P.
aeruginosa mutants in the study, respectively.
7.2.5 Specific antibiotic classes
This section discusses individual antibiotic classes and their pharmacodynamic characteristics,
which influence antibiotic activity and the prevention of resistance. The relevant PD indices that
have been shown to correlate with both outcomes are presented in Table 7-1.
172
7.2.5.1 Quinolones
Quinolones are mostly lipophilic antibiotics and display largely concentration-dependent kill
characteristics but with some time-dependent effects. Previous in vitro studies have shown that the
achievement of a Cmax/MIC ratio of at least 8-12 is important for its optimal bactericidal activity
[463, 464]. Given the half-life of most quinolones, this corresponds to AUC0-24/MIC values that
correlate to efficacy. More importantly however, is that the index has also been associated with the
reduction of resistant mutants in several experimental studies [389, 465, 466].
Several studies found that the ratio of AUC0-24/MIC is important for its bactericidal effect, as an
even more significant index as compared to the Cmax/MIC ratio, and a ratio of ≥125 and ≥30 has
been advocated for clinical success in the treatment of Gram-negative and -positive infections,
respectively [389, 467-471]. In the context of antibiotic resistance, an inverse relationship has been
described between this index and the probability of developing resistance [402]. Accordingly,
quinolone dosing regimens that ensure higher ratios of AUC0-24/MIC are currently recommended to
maximize bactericidal exposure as well as minimizing the development of resistance [401, 402,
435]. Several investigators have further elucidated the critical AUC0-24/MIC thresholds as being
between >100 to 200 in order to suppress the formation of resistant mutants when these antibiotics
are used for Gram-negative infections [401, 402, 472]. However, due to intrinsic differences
between various quinolones in selecting resistant strains, the suggested AUC0-24/MIC ratio for
resistance suppression may vary between individual agent [389, 473].
173
Table 7-1: Optimal pharmacokinetic/pharmacodynamic indices for antibiotic activity and the magnitudes associated with maximal therapeutic outcomes and resistance suppressiona
Antibiotic class Optimal PK/PD index PK/PD magnitude for bacterial killingb PK/PD magnitude for clinical efficacyc Optimal PK/PD index for
resistance suppression
PK/PD magnitude for
resistance suppressiond
Aminoglycosides AUC0-24/MIC AUC0-24/MIC: 80-160
[229, 474, 475]
AUC0-24/MIC: 50-100
[476]
Cmax/MIC Cmax/MIC ≥20
[477]
Cmax/MIC -
Cmax/MIC ≥8
[431, 461, 478]
Cmax/MIC ≥30
[477]
Penicillins T>MIC ≥40-50% T>MIC
[11, 12]
≥40-50% T>MIC T>MIC ≥40-50% T>MIC
[457]
Cephalosporins T>MIC ≥60-70% T>MIC
[11, 12]
≥45-100% T>MIC
[20, 21]
tMSW ≤40% tMSW
[479]
Carbapenems T>MIC ≥40% T>MIC
[11]
≥50-75% T>MIC
[25, 152]
T>MIC ≥40% T>MIC
[480]
tMSW ≤45% tMSW
[481]
Fluoroquinolones AUC0-24/MIC AUC0-24/MIC: 30-200
[430, 470, 471]
AUC0-24/MIC: 35-250
[389, 467-469]
AUC0-24/MIC AUC0-24/MIC: 100-200
[401, 435]
Cmax/MIC Cmax/MIC ≥8
[463, 464, 466]
Cmax/MIC ≥8
[474]
Cmax/MIC Cmax/MIC ≥4
[465]
AUC0-24/MPC AUC0-24/MPC ≥22
[455]
tMSW ≤30% tMSW
[448, 450, 454, 482]
Vancomycin AUC0-24/MIC AUC0-24/MIC: 86-460
[11]
AUC0-24/MIC: 400-600
[11, 483]
AUC0-24/MIC AUC0-24/MIC: 200
[448]
Linezolid AUC0-24/MIC AUC0-24/MIC: 50-80
[484]
AUC0-24/MIC ≥80
[485] - -
T>MIC ≥40% T>MIC
[484, 486]
≥85% T>MIC
[485] - -
Daptomycine AUC0-24/MIC AUC0-24/MIC: 388-537
[487] -
AUC0-24/MIC AUC0-24/MIC: 200
[448]
Cmax/MIC Cmax/MIC: 59-94
[487] - - -
Fosfomycin Unknown - - - -
Colistin AUC0-24/MIC AUC0-24/MIC: 50-65
[488, 489] - - -
Abbreviation: AUC0-24/MIC, ratio of area under the concentration-time curve during a 24-hour period to minimum inhibitory concentration; Cmax/MIC, ratio of maximum drug concentration to minimum inhibitory
concentration; T>MIC, duration of time that drug concentration remains above the minimum inhibitory concentration during a dosing interval; tMSW, percentage of time spent by an antibiotic within the mutant selection
window; AUC0-24/MPC, ratio of area under the concentration-time curve during a 24-hour period to the concentration that prevents mutation.
174
Legend:
aAll values refer to the non-protein bound, free fraction except when indicated otherwise.
bData have been summarized from in vivo animal studies and may utilize different infection models employing different bacteria. Where the index is reported as a range, specific data for the contributing indices, which may
have been derived from different studies, can be found in the associated references. The data also reflect the 2-log kill and in some cases 1-log kill which may or may not coincide with maximum kill.
cData have been summarized from clinical studies and may recruit different patient population. Where the index is reported as a range, specific data for the contributing indices, which may represent PK/PD thresholds for
clinical or microbiological cure, can be found in the associated references.
dData have been summarized from pre-clinical studies, which may include in vitro and in vivo experimental infection models employing different bacteria. Specific data for the contributing indices can be found in the
associated references.
eValues reported here refer to total drug concentration.
175
The AUC0-24/MPC index is also being investigated and the advantages over AUC0-24/MIC in the
prediction of resistance development have been documented in several in vitro studies [455, 458,
459]. To date, this remains a controversial argument as most authors found that both indices were
similar in their predictive potentials of resistance development [452, 490]. Nevertheless, higher
ratios of AUC0-24/MPC are associated with minimizing the emergence of resistance.
Recently, increasing interest and efforts have been focused on the application of MSW concept in
the evaluation of quinolones dosing regimens. Based on the current data, tMSW of ≤30% should
restrict mutant amplification and the index has been studied in several in vitro [450, 482] and in
vivo studies [452, 456]. Khachman et al., further extended this concept into clinical practice by
investigating the appropriateness of the currently recommended ciprofloxacin dosing in 102
critically ill patients [491]. Using Monte Carlo simulations, the PTA (i.e., ≤20% tMSW) for the
currently recommended ciprofloxacin dosing regimens (i.e., 800 mg or 1200 mg/daily) was less
than 50% and when higher doses such as 2400 mg/daily were used, only minor improvements were
observed i.e., PTA of 61%. More importantly, the risk of selecting resistant A. baumannii and P.
aeruginosa strains were extremely high with the recommended regimens thus challenging their
appropriateness in critically ill patients. As it stands, a quinolone-dosing regimen that maximizes
the AUC0-24/MIC ratio should be considered in critically ill patients and by citing ciprofloxacin as
an example; the objective may be achieved with a 400 mg 8-hourly or 600 mg 12-hourly regimen.
When treating pathogens with high MICs, dose escalation should be considered whilst being
observant of possible dose-related adverse effects occurrence.
7.2.5.2 Aminoglycosides
Aminoglycosides are hydrophilic in nature and they demonstrate concentration-dependent kill
characteristics [431, 492]. Although previous studies have mainly suggested that achieving a high
Cmax/MIC ratio predicts optimal outcome [229, 386, 474, 478, 493], Craig et al., argued that the
ratio of AUC0-24/MIC would be more appropriate in describing the antibiotic’s activity [11]. In the
1980s, Moore et al., [386] suggested that an aminoglycoside dose that provided a Cmax/MIC ratio of
8-10 was associated with a higher probability of clinical success against Gram-negative infections.
However, the investigators chose the index due to their sparse PK sampling times and consequently,
AUC0-24/MIC ratio was not considered in the study. Importantly, high collinearity existed between
Cmax and AUC. Several investigators have since suggested that the ratio of AUC0-24/MIC is more
likely to be a “better” PD descriptor for aminoglycosides activity [430, 476], in which an AUC0-
24/MIC ratio of 80-160 has been advocated for its efficacy [475, 476].
176
Although higher concentrations enhance aminoglycoside activity, prolonged exposure of such
concentrations may lead to drug toxicity as well as the development of bacterial resistance. This
type of resistance is known as adaptive resistance and is characterized by a slow but reversible,
concentration-independent killing [494-496]. Maximizing the Cmax/MIC ratio seems to reduce the
development of adaptive resistance and the objective is likely achieved with extended-daily dosing
(EDD) as opposed to the traditional dosing schemes (i.e., twice or thrice daily dosing) [496]. In a
PD model designed to predict aminoglycosides activity against A. baumannii and P. aeruginosa,
Tam et al., further quantified the required Cmax/MIC ratio to prevent the resistance development
[477]. In this study, a Cmax/MIC ratio of 20 for a once-daily amikacin dosing regimen and 30 for a
12-hourly gentamicin dosing regimen was required for suppressing A. baumannii and P. aeruginosa
regrowth, respectively. Based on these results, it could be then inferred that the Cmax/MIC ratio and
AUC0-24/MIC are the PD indices to consider in order to suppress A. baumannii and P. aeruginosa
resistant mutants, respectively.
Based on the available data, EDD rather than the traditional multiple daily dosing of
aminoglycosides is currently advocated in an attempt to maximize their therapeutic potential and
minimize resistance development. Furthermore, it has been shown in numerous clinical studies
[497, 498] and several meta-analyses [499, 500] that the dosing recommendation is indeed
appropriate and valid in reducing aminoglycosides toxicity and may increase the likelihood of
successful treatment outcomes. Clinical data on these dosing effects on development of resistance
remains sparse.
7.2.5.3 Beta-lactams
The beta-lactam antibiotics are made up of penicillins, cephalosporins and monobactams and
carbapenems but the latter will be considered separately in the section below because of their
different spectrum and PD properties. Beta-lactam antibiotics are generally hydrophilic in nature
and display time-dependent kill characteristics. The fT>MIC is regarded as the optimal PD index for
their activity and as such, maintaining effective drug exposure above the MIC should be the priority
when this antibiotic class is used [12]. It has been generally suggested that % fT>MIC required for
bactericidal effect is 50%, 60-70% and 40% for penicillins, cephalosporins and carbapenems,
respectively [22, 393, 501]. Additionally, relatively higher fT>MIC exposures are needed for maximal
activity against the Gram-negatives as opposed to the Gram-positive pathogens. However, clinical
data from critically ill patients have not consistently supported these targets. Some data suggest that
these in vitro exposures to be the minimum antibiotic exposures required, with patients potentially
177
benefitting from higher and longer antibiotic exposures than those previously described in in vitro
and in vivo studies [20, 21, 25, 27, 28, 152]. It has also been demonstrated that maximal bactericidal
activity occurs when drug concentrations are maintained at 4-5 x MIC, with higher concentrations
providing little added benefit [23, 26, 152]. Therefore, it has been suggested that beta-lactam
concentrations should be maintained at least 4-5 x MIC for extended periods during each dosing
interval to ensure clinical success, particularly in severely ill patients [13].
It is still inconclusive whether the fT>MIC index predicts beta-lactams resistance although the
potential link has been described in several in vitro [405] and in vivo experimental studies [404,
457]. Fantin et al., utilized an in vivo animal model to suggest that the development of resistance
against ceftazidime might arise should the drug concentration fall below the MIC for more than half
of the dosing interval [404]. The risk of developing resistance against a cephalosporin has also been
linked to a low AUC0-24/MIC ratio [502]. This was further demonstrated by Stearne et al., who
found that an AUC0-24/MIC of 1000 was required with ceftizoxime to prevent the emergence of
resistant Enterobacter cloacae strains [437]. In another murine lung infection model, Goessens et
al., found that the growth of resistant E. cloacae strains was correlated with prolonged ceftazidime’s
tMSW [479].
Based on the limited data on resistance suppression, beta-lactams dosing that targets concentrations
greater than 4 x MIC for extended periods would be most appropriate [503]. Importantly, research
has shown that the objective can be obtained via frequent dosing or by utilizing EI or CI. However,
the altered dosing schemes may potentially drive the emergence of resistance with sub-optimal
dosing, at least in theory, as these approaches tend to increase beta-lactams tMSW. In a recent in
vitro hollow-fibre infection model (HFIM) of P. aeruginosa, Felton et al., suggested that EI of
piperacillin/tazobactam was equivalent to IB dosing in terms of the bactericidal effect and the
prevention of resistance [504]. However, the target concentration for the two approaches should be
different in which the ratio of Cmin/MIC of 10.4 and 3.4 was required by EI and IB to suppress
resistant mutants, respectively.
7.2.5.4 Carbapenems
Generally, carbapenems have similar PK/PD characteristics when compared to other beta-lactam
antibiotics. Some studies have suggested that unlike other beta-lactams, carbapenems possess a
PAE against Gram-negative bacilli, including P. aeruginosa strains [157] although this could not be
confirmed in another study [505]. This PAE property of carbapenems may explain a shorter %
178
fT>MIC for optimal bactericidal activity. Li et al., further quantified the % fT>MIC as >54% in order to
achieve optimal microbiological outcome when meropenem is used in patients with lower
respiratory tract infections [23]. Additionally, only a ratio of Cmin/MIC of >5 was significantly
associated with clinical and microbiological cure in this cohort of patients. Further, Tam et al., used
an in vitro HFIM to demonstrate that a Cmin/MIC of >6.2 was required to suppress the development
of resistant P. aeruginosa mutants [405]. The finding was later corroborated by the same group of
investigators in a neutropenic mouse infection model and in this current analysis, % fT>MIC of >40%
was also associated with the selection of resistant mutants [480]. More recently in an in vitro
dynamic model simulating doripenem concentrations, Zinner et al., found that resistant P.
aeruginosa mutants were likely to be selected at drug concentrations that fell ≥45% within the
MSW (≥45% tMSW) [481].
Similar to the other beta-lactam antibiotics, maintaining carbapenem concentrations at 4-6 x MIC
for extended periods is currently advocated to suppress resistant mutants selection. To achieve this
objective, prolonging the duration of infusion is generally recommended when the antibiotic is
used. However, EI as opposed to CI is the currently preferred dosing method when carbapenems are
used considering the group’s inherent drug instability in aqueous solutions. With increasing
information and emerging data, clear distinction, in the context of stability problems, needs to be
emphasized between the different members of the carbapenem group. Whilst imipenem is indeed
less stable, there are currently no practical reasons to oppose continuous meropenem infusion as it
has been successfully administered up to 8 hours (under hospital environment) in numerous clinical
studies without drug instability or degradation reports [86, 276, 506]. In an in vitro HFIM
examining cell-kill and resistance suppression for three P. aeruginosa strains, Louie et al.,
demonstrated that a doripenem dosing regimen of 1 g infused over 4 hours was the solitary regimen
that was able to completely suppress resistance for the full period of 10 days for wild-type isolates
[507]. Importantly, the investigators also reported that the dosing regimen produces concentrations
at >6.2 x MIC which were significantly associated with maximal resistance suppression in other
evaluations [405, 481]. In addition, Chastre et al., also observed lower occurrence of resistant P.
aeruginosa strains arising in patients treated with EI of doripenem when compared to patients who
received conventional imipenem dosing in a multicentre, RCT of critically ill patients with VAP
[336].
179
7.2.5.5 Vancomycin
Vancomycin is a glycopeptide antibiotic and is a relatively hydrophilic drug. Some in vitro [508,
509] and in vivo animal studies [510] suggest that the bactericidal activity of the antibiotic is time-
dependent whereas some have shown the ratio of Cmax/MIC to be equally important [511]. More
recently, it has been generally accepted that achieving a high ratio of AUC0-24/MIC would be more
predictive of its clinical success. Studies by Moise-Broder et al., were the earliest to quantify that a
ratio of AUC0-24/MIC of ≥400 is needed for an optimal bacteriological and clinical outcome when
treating patients with S. aureus respiratory infections [432, 512]. The findings are consistent with
Zelenitsky et al., retrospective data evaluation and the investigators also described that higher
exposures are needed, specifically a ratio of AUC0-24/MIC of ≥578, when treating critically ill
patients with septic shock [483]. Due to common clinical practice of measuring trough
concentrations when vancomycin is used, a trough concentration ranging between 15-20 mg/L is
recommended for optimal outcome in hospital-acquired pneumonia and complicated infections
[513, 514].
Although scarce data exist, it could be assumed that the development of resistance is linked to sub-
optimal vancomycin exposure. Through their in vitro PD model, Tsuji et al., was able to conclude
that the development of vancomycin-intermediately susceptible S. aureus (VISA) strains was driven
by sub-optimal vancomycin exposure in the setting of dysfunctional agr locus in S. aureus [515].
Additionally, the investigators also found that the AUC0-24/MIC ratio needed to suppress resistance
for the strains was four-fold higher than that in the parent strains. Charles et al., observed that
patients with VISA infections were more likely to present with low vancomycin trough
concentrations (i.e., <10 mg/L) [516]. Based on similar findings to Charles et al., retrospective data
evaluation [517, 518], and considering the recommended trough concentrations for successful
clinical outcomes in severe infections, vancomycin trough concentrations should also be maintained
between ≥15-20 mg/L at all times to suppress resistance emergence [513]. Thus, loading doses of
25-30 mg/kg should be considered in critically ill patients to rapidly attain the target concentration
and certainly, higher vancomycin doses of up to 40 mg/kg may be important to minimize resistance
development. In addition, doses in excess of 5 g/daily were estimated to be necessary to achieve the
target AUC0-24/MIC ratio when treating VISA infections [107]. Increasing knowledge of the
relationship between higher vancomycin exposures and drug toxicities may limit the dosing of this
drug to limit the emergence of resistance.
180
7.2.5.6 Linezolid
Linezolid belongs to a class of antibiotics known as oxazolidinones, which was developed for the
treatment of Gram-positive infections. In a murine infection model, Andes et al., demonstrated that
optimal linezolid activity correlates well with the ratio of AUC0-24/MIC, with a ratio of between 50
and 80 predicting the likelihood of successful treatment outcome [484]. However, higher clinical
success rates may occur at AUC0-24/MIC ratio of 80-120 for bacteraemia, lower respiratory tract
infections and skin structure infections as reported by Rayner et al., in their retrospective clinical
PD evaluation of 288 patients [485]. Importantly, the investigators also showed that the drug
exposure required for optimal treatment outcome was also dependent on the site and types of
infection. Additionally, the probability of treatment success appeared likely when linezolid
concentrations were maintained above the MIC for the entire dosing interval. The finding
corroborated two earlier rabbit endocarditis experimental models, which described linezolid as a
time-dependent antibiotic where an fT>MIC of 40% is needed for optimal antibiotic activity [484,
486]. A 600 mg 12-hourly dose is currently suggested to achieve these PD indices and hence,
predicts successful treatment outcome. However, it is also imperative to emphasize that the
antibiotic’s PK is highly variable [429, 505, 519-521], particularly in patients with severe
infections, and the phenomenon has, in part, contributed to treatment failures as well as the
increased occurrence of adverse events in such patients [485, 522]. As such, TDM of linezolid is
beneficial in this respect and emerging data are suggesting that general TDM may optimize patient
outcomes when linezolid is used in critically ill patients. In the context of antibiotic resistance, low
dose linezolid (200 mg 12-hourly) has been associated with the development of E. faecium and E.
faecalis resistant strains [523]. In addition, prior exposure and prolonged linezolid administration
have been suggested to increase the likelihood of resistance development [524-526]. Nevertheless,
the development of resistance against the antibiotic has not been widely reported [527, 528].
7.2.5.7 Daptomycin
Daptomycin is the first approved member of the cyclic lipopeptides with a potent activity against
Gram-positive pathogens including methicillin-resistant S. aureus (MRSA) and vancomycin-
resistant enterococci (VRE). In vivo experimental studies describe daptomycin to be a
concentration-dependent antibiotic. The ratio of Cmax/MIC in concert with AUC0-24/MIC has been
correlated with its efficacy in several in vivo animal studies [487, 529, 530]. Safdar et al., used a
neutropenic murine thigh infection model to characterize the PD characteristics of the antibiotic
[487]. In the infection model, the Cmax/MIC and AUC0-24/MIC ratio required for bacteriostasis
ranged from 59-94 and 388-537 (total drug concentration), respectively. Similar ratios were
181
required for bacteriostasis in two other clinical studies, which recruited healthy volunteers [531,
532]. Based on these suggested indices, optimal daptomycin exposure could be expected in most
patients with modest dosing (4-6 mg/kg per day). However, the emergence of daptomycin-resistant
strains has been reported with such dosing regimens [533, 534] and some experts recommend the
use of higher dosing to curb this issue (i.e., 8-12 mg/kg per day) [535], which was shown to be safe
in one retrospective data evaluation [536] and several case reports [537, 538]. A duration of therapy
exceeding 2 weeks has also been documented to increase the likelihood of daptomycin resistance
[534].
7.2.5.8 Fosfomycin
Fosfomycin, which was discovered more than 40 years ago but then forgotten, is a phosphonic acid
derivative that possesses promising in vitro activity against carbapenem-resistant K. pneumoniae
[539]. The introduction of fosfomycin into our current armamentarium of antibiotics was greeted
with some scepticism due to major setbacks in its initial in vitro evaluation and this has in part,
contributed to its limited acceptance for clinical use. Although there are suggestions that
fosfomycin’s bacterial killing appears to be driven by fT>MIC, the optimal PK/PD index relating to
its activity remains to be established and requires further investigations [540]. In addition, rapid
bacterial killing was observed in several static-time kill studies when drug concentrations were
maintained at 2-8 x MIC. Similar to the beta-lactams, the development of fosfomycin resistance is
driven by low drug exposures and prolonged duration of antibiotic course [541]. There has also
been some debate concerning the rapid development of fosfomycin resistance when it is used as a
monotherapy particularly in non-urinary tract infections. In a murine endocarditis model, Thauvin et
al., found that the combination of fosfomycin and pefloxacin was more effective in suppressing
resistant S. aureus strains emergence when compared to fosfomycin alone [542]. In several in vitro
and in vivo experimental studies, instances of synergism were also demonstrated against MRSA
when fosfomycin was combined with the beta-lactams [543, 544], linezolid [545], and moxifloxacin
[546]. Combining fosfomycin with beta-lactams is also strongly supported by in vitro data, which
describe synergism between the two antibiotics against P. aeruginosa infections [547-549].
However, whether the in vitro synergism would translate to increased clinical efficacy remains to be
demonstrated. In a recent prospective study, fosfomycin, in combination with colistin, gentamicin
or piperacillin/tazobactam, provided promising bacteriological and clinical outcome data in the
treatment of 11 critically ill patients with ICU-acquired infections caused by carbapenem-resistant
K. pneumoniae [550]. Based on limited clinical data in treating serious infections in the ICU and its
182
high tendency for developing resistance, fosfomycin should not be used as a single agent and the
choice of adjunctive antibiotic should be appropriately evaluated in future studies.
7.2.5.9 Colistin
Colistin is a polymyxin antibiotic, which is administered parenterally as colistin methanesulfonate
(CMS). The antibiotic has concentration-dependent kill characteristics with a significant in vitro
PAE against Gram-negative pathogens [551]. In vivo murine studies suggested that the most
predictive PD index for its bacterial activity, particularly against A. baumannii and P. aeruginosa, is
AUC0-24/MIC [552, 553]. Based on observations in several lung infection models, the ratio of
AUC0-24/MIC between 50 and 65 has been suggested as the optimal PD target although higher
exposures were also described in thigh infection models [488]. The heteroresistance phenomenon,
the situation whereby resistant sub-populations are present within a strain considered susceptible
based on MIC, is an emerging problem for the antibiotic and has been observed in clinical isolates
of A. baumannii [489, 554], K. pneumoniae [555], and P. aeruginosa [556]. Further to this, rapid
resistant mutants formation was demonstrated following colistin exposure in two recent in vitro
PK/PD studies mimicking clinical dosing regimens in humans [557, 558]. This is particularly
worrying as Garonzik et al., suggested that the currently recommended CMS dosing regimen is sub-
optimal in a population PK analysis of 105 critically ill patients [559] and their findings were
corroborated by other investigators who recruited smaller number of patients [560, 561]. With
increasing PK knowledge on the drug, Garonzik et al., [559] and Plachouras et al., [561] further
described optimized CMS dosing regimens in patients with varying degrees of renal function. The
dosing proposed by Plachouras et al., [561] has now been validated in a critical care setting by
Dalfino et al., [562] in the treatment of MDR infections. Among the relevant recommendations
concerning CMS dosing is the need for an initial loading dose as the conversion of the prodrug
CMS to the active entity of colistin is very slow and adequate colistin exposure may be delayed for
a few days. Although theoretically plausible based on its PD characteristics, the adoption of EDD is
not suitable on the basis of the resultant prolonged periods of low colistin concentrations leading to
the formation of heteroresistance [552, 553, 557]. Based on current PK data of critically ill patients
[559-561, 563, 564] and in vivo PK/PD experimental studies [552, 553] colistin monotherapy would
not be beneficial in maximizing therapeutic success and preventing resistance, particularly in
patients with moderate-to-good renal function and for pathogens with MICs of ≥1. In addition, a
treatment course lasting more than 12 days has been found to be associated with the development of
colistin resistance in two recent clinical studies [565, 566].
183
7.2.6 Modifying treatment approaches to prevent emergence of resistance
7.2.6.1 Combination antibiotic therapy
Although combining antibiotics is common during the treatment of infection, the relevance of the
practice has been the matter of debate with conflicting conclusions. Proponents of combination
therapy will strongly suggest that the approach will increase antibiotic exposure via extending
coverage across a wider range of potential pathogens and in some clinical evaluations, has been
found to improve survival in severely ill patients [567-570]. Further strong theoretical reasons to
seriously consider a combination antibiotic approach include; antibiotic synergism which enhances
killing potency; combined activity against biofilm-growing pathogens; increasing tissue
penetration; inhibition of pathogen’s toxin and enzyme production; and prevention of resistance
development. However, there is also clinical evidence indicating that combination therapy may not
be superior, even harmful in some instances [571-573], as opposed to monotherapy in the treatment
of Gram-negative bacilli infections [574-576]. Based on the current data, it could be deduced that
combination antibiotic therapy may not benefit all patients but rather a select patient population
with select infections. While monotherapy may be sufficient for most patients, critically ill patients
with severe infections may benefit the most from rationally optimized combination therapy.
Although some in vitro infection models [577, 578] and animal studies [579] clearly indicated
benefits behind the approach, unfortunately, the vast majority of combination schemes were chosen
randomly without considering the pre-clinical findings [580].
In the context of resistance suppression, rationally optimized combination therapy may restrict the
amplification of resistant mutants. Epstein et al., [581] suggests that the presence of more than two
antibiotics at the infection loci (with drug concentrations above the MIC), each with a different
killing mechanism, would “shut” the MSW and thereby suppressing mutant growth [582-584].
Apart from several pre-clinical studies [448, 577, 579, 585, 586], no RCTs to date have shown that
the approach reduces the emergence of resistance. Furthermore, the benefit is particularly difficult
to be demonstrated in clinical evaluations, which frequently recruit heterogeneous patient
population and are not conducted long enough to detect the emergence of resistance. In the face of
rapidly evolving resistance phenomenon, it is likely that we have to turn our attention to the concept
of rationally optimized combination antibiotic therapy, particularly in the treatment of severely ill
patients in the ICU. In addition, the approach is likely to be important early in the course of
infection when the inoculum of the infecting pathogens is the highest.
184
7.2.6.2 Duration of therapy
It has been increasingly shown in pre-clinical studies that prolonged antibiotic administration may
play an important role in the formation of resistant mutants. Conversely, the longer antibiotic
therapy persists, the more challenging it is to curtail the emergence of resistant pathogens. It has
been suggested that an antibiotic regimen that lasts for only 4-5 days should be sufficient to produce
maximal bactericidal effect with an added benefit of resistance suppression. Extending antibiotic
exposure to more than 10 days is risky on the basis of resistance development whereby higher drug
exposures are needed to suppress resistant mutants in this situation and if this threshold is not
achieved, treatment failure ensues as the resistant population dominates. This phenomenon has been
described by Tam et al., in their in vitro model of S. aureus infection which investigated two
garenoxin dosing regimens with different intensity; one with an AUC0-24/MIC ratio of 280 and the
other with 100 [438]. The investigators demonstrated that once the duration of garenoxin exposure
increased beyond 5 days, the magnitude of dosing needed for suppressing resistant mutants also
increased. The higher dosing regimen was found to suppress resistance amplification for 10 days
whilst the less intense regimen was only able to demonstrate the ability for 4-5 days.
At best, the common practice of administering an antibiotic for 10-14 days is currently based on
limited data and expert opinion rather than it being an evidence-based approach. However, for some
deep-seated infections such as osteomyelitis and endocarditis, prolonged antibiotic courses are
essential. Instances of potential benefits from shortening the duration of antibiotic therapy in
reducing the emergence of resistance while maintaining clinical efficacy have been increasingly
described [587-590]. Among these findings, Singh et al., demonstrated that patients who received
shortened antibiotic courses (i.e., ≤3 days) had reduced ICU stays, lower superinfection and
resistance rates as well as lower mortality rates compared to patients who received standard courses
[590]. Further investigations are warranted to elucidate the exact duration of therapy that maximizes
therapeutic outcome and suppresses resistance development. Until conclusive findings are made,
antibiotic therapy should “hit hard” in the early course of infection and “stop early” to assist in
resistance prevention.
7.2.6.3 Altered dosing approaches
Optimal and timely PK/PD target attainment has been associated with the likelihood of clinical
success and resistance suppression in critically ill patients [1]. However, organ function changes
that may result from either infectious or non-infectious pathologic processes may alter antibiotics
exposure. For example, the increase in Vd for hydrophilic antibiotics such as the aminoglycosides
185
[591, 592], beta-lactams [56], glycopeptides [107], and linezolid [87], have been extensively
documented in critically ill patients. Importantly, this phenomenon leads to sub-optimal antibiotic
concentration and may impair the attainment of desired PK/PD targets for optimal activity,
particularly in the early phase of severe sepsis and septic shock. In this setting, higher initial loading
doses of hydrophilic antibiotics should be applied to compensate for the volume expansion. In the
context of resistance prevention, the approach may have the potential utility to rapidly reduce
bacterial burden in the early stage of infection. Tsuji et al., recently tested the impact of a front-
loaded linezolid-dosing regimen on bacterial killing and resistance suppression in a HFIM of
MRSA infection [593]. From a PD standpoint of bacterial eradication, their findings suggest
potential benefits of increasing doses of linezolid early in therapy although no differences were
observed in terms of resistance suppression. Further pre-clinical studies are necessary to investigate
this promising dosing strategy particularly in the context of resistance suppression, before it can be
fully applied in clinical practice.
For the beta-lactams, maintaining effective exposure for extended periods or increasing % fT>MIC
would be especially appropriate in the prevention of resistance particularly in critically ill patients.
Research has shown that the traditional bolus dosing produces sub-optimal antibiotic concentrations
for much of the dosing interval, which may consequently favour resistant bacterial strains
development [13]. Numerous pre-clinical and clinical PK/PD studies have demonstrated that
improved beta-lactams exposure could be achieved via EI or CI administration [14]. These altered
dosing approaches may be especially important in patients who develop severe pathophysiological
derangements and when less susceptible pathogens are present. However, more clinical studies are
urgently needed to evaluate the relative ability of EI and CI versus IB dosing of beta-lactam
antibiotics in reducing the emergence of resistance if a global practice change is to be expected.
7.2.7 Conclusion
For decades now, clinicians have overused antibiotics and apparently did so with the notion of our
continuous supply of new antibiotics would adequately address any emerging resistance concerns.
That thought didn’t materialize and on the contrary, as our current antibiotic pipeline is nearly dry,
infecting pathogens have tremendously outperform our existing armamentarium thus far and they
are becoming increasingly difficult to treat. The current situation that we are in is not surprising as
most of our treatment goals were previously focused on maximizing clinical and microbiological
cure and not minimization of the emergence of antibiotic resistance. With numerous pre-clinical
data indicating that the magnitude of the PK/PD indices for resistance suppression is generally
186
higher than the thresholds required for clinical success, antibiotic dosing that only aims to optimize
clinical efficacy may potentially amplify resistance formation by selecting mutant bacterial strains
with reduced drug susceptibility. Furthermore, the relevance of commonly prescribed antibiotic
dosing is questionable in severely-ill patients as most dosing recommendations have been derived
from studies that do not consider the occurrence of pathophysiological changes in critical illness.
Therefore, with enhanced knowledge on antibiotic PK/PD over recent years, emerging data are
suggesting that the PD-based dosing approach should not only aim to maximize clinical outcomes
but to also include the suppression of resistance. In some antibiotics such as the fluoroquinolones,
the PD thresholds needed to prevent the emergence of resistance is readily described but
unfortunately, is often neglected and not implemented in clinical practice; whilst for most antibiotic
classes, specific research is urgently needed. To curb the development of resistance, it is likely that
we have to administer “the highest tolerated antibiotic dose” via alternative dosing strategies and
should also consider the combined use of multiple antibiotics (that are rationally optimized),
particularly early in the course of infection in severely ill patients.
187
7.3 Conclusion
Previous studies of optimization of antibiotic dosing only focused on maximizing clinical and
microbiological cure and not minimization of the emergence of antibiotic resistance. The data
presented in this chapter showed that most of the information describing PK/PD and its association
with antibiotic resistance were derived from pre-clinical studies. The application of PK/PD
principles for dosing antibiotics have been shown to reduce the risk of antibiotic resistance and
increasing data are suggesting that the dosing approach should not only be explored to maximize
patient outcomes but to also include the suppression of resistance. To minimize the development of
antibiotic resistance in critically ill patients, it is likely that clinicians will have to administer “the
highest tolerated antibiotic dose” via alternative dosing strategies.
188
Chapter 8: Summary of findings, general discussion, conclusion and
future directions
8.1 Summary of findings and general discussion
Critically ill patients are markedly different from those in general ward settings as they are
associated with higher morbidity and mortality rates. These patients commonly demonstrate a high
level of illness severity which causes profound physiological changes that can alter the PK of
antibiotics. Antibiotic dosing that does not account for these changes may lead to therapeutic failure
and the emergence of antibiotic resistance.
The issue of critical illness-related alterations affecting beta-lactam dosing requirements was
described in Chapter 2. Chapter 2 aimed to describe the population PK of doripenem in critically ill
patients with sepsis and use Monte Carlo dosing simulations to provide clinically relevant dosing
guidelines for these patients. The typical Vd of doripenem in this cohort was 0.47 L/kg, which was
two-fold greater than that previously described in healthy volunteers and non-critically ill patients.
The finding is expected and it is in agreement with other currently available data investigating the
PK of doripenem in critically ill patients with sepsis. Extreme fluid extravasation related to critical
illness and aggressive medical interventions have been suggested to cause these increases in Vd.
The typical CL in this cohort was 0.14 L/kg/hr and this estimate was significantly influenced by
CLCR such that a 30 mL/min increase in estimated CLCR would increase doripenem CL by 52%.The
importance of BOV on CL in the PK model, which is also described in Chapter 2, suggests a certain
degree of variability in CL exists between treatment days. This means that dosing requirements in
this population may be dynamic and highlights that regular dosing review and potentially, use of
TDM to maximize therapeutic outcomes. It is likely that conventional dosing of doripenem does not
consider these pathophysiological perturbations and as such, the licensed “one-dose-fits-all” dosing
strategy is likely to be flawed in critically ill patients. Data presented in Chapter 2 showed that for
pathogens with a MIC of 8 mg/L, a dose of 1000 mg 8-hourly as a 4-hour infusion is optimal for
patients with CLCR of 30-100 mL/min whilst a dose of 2000 mg 8-hourly as a 4-hour infusion is
required for patients manifesting a CLCR >100 mL/min. This, in a way, highlights that an alternative
dosing approach such as the empirical use of EI of doripenem should be strongly considered in this
patient population, particularly when pathogens with higher MICs are involved.
The primary aims of the Thesis was to investigate the potential benefits of PI dosing (i.e., CI and
EI) as an alternative dosing method to conventional IB administration in critically ill patients. Based
189
on the structured review of published literature presented in Chapter 3 and 5, current evidence
suggest that CI of beta-lactam antibiotics may not be advantageous for all critically ill patients but
may only be meritorious to a specific cohort of patients with severe infections. The niche benefits of
PI dosing was further explored in Chapter 4, which presented the findings of a post hoc analysis on
the database of the DALI study. The primary aims of the analysis was to compare the PK/PD target
attainment and clinical outcomes between PI (i.e., CI and EI) and IB dosing of two commonly used
beta-lactams (i.e., piperacillin/tazobactam and meropenem) in a large cohort of critically ill patients
who were not receiving RRT. In this analysis, the use of PI dosing significantly increased the target
attainment for most PK/PD end-points. The data presented in Chapter 4 further specified the sub-
group of patients who are more likely to benefit from PI dosing. In the sub-group of patients who
had respiratory infection, those who received beta-lactams via PI dosing demonstrated significantly
better 30-day survival as opposed to IB patients (86.2% versus 56.7%; p = 0.012). Additionally, in
patients with a SOFA score of ≥9, administration by PI as compared to IB dosing was significantly
associated with better clinical cure (73.3% versus 35.0%; p = 0.035) and higher survival rates
(73.3% versus 25.0%; p = 0.025). These findings further corroborate similar claims of previous
studies which suggested potential benefits of PI dosing of beta-lactam antibiotics in critically ill
patients with severe pneumonia. Accordingly, future clinical studies should seek to test the potential
clinical superiority of altered beta-lactam dosing strategies in a specific cohort of critically ill
patients with severe infections, particularly in those with respiratory infection and not receiving
RRT.
Although numerous pre-clinical and PK/PD data support CI of beta-lactam antibiotics in critically
ill patients, the current evidence, presented in Chapter 3 and 5, suggest neither superiority nor
inferiority of IB dosing with regards to patient outcomes. The lack of clinical outcome data to
support the pre-clinical data may be because the existing studies are underpowered to detect
differences in patient-centred outcomes (e.g., mortality) between the two dosing approaches.
Chapter 5 aimed to scrutinize the published clinical studies for their methodological shortcomings
in the comparison of CI and IB of beta-lactam antibiotics in hospitalized patients. As described in
that chapter, most of the published clinical studies used inconsistent study designs and treatment
arms, and mostly recruited heterogeneous patient populations which mainly consist non-critically ill
patients. Furthermore, most studies were found to recruit patients with highly susceptible pathogens
and this patient selection may mask the potential advantages of CI administration. If many patients
with highly susceptible pathogens are included in a study, the sample size required to show a
clinical difference between CI and IB dosing will rise dramatically. The findings in Chapter 5 also
suggest that these patients should be the focus of future clinical studies: (a) critically ill patients; (b)
190
patients with higher level of illness severity (e.g., APACHE II ≥15); (c) patients infected with less
susceptible microorganism; (d) patients infected with Gram-negative infections and; (e) patients
who are not receiving RRT.
The BLISS study, which was presented in Chapter 6, was designed to address most of the
limitations of previous studies. The BLISS study is a prospective, two-centre, RCT of CI versus IB
dosing of beta-lactam antibiotics which was conducted in two Malaysian ICUs. This study recruited
140 critically ill patients with severe sepsis who were not on RRT prior to study inclusion. The
primary outcome evaluated in the study was clinical cure at 14 days after antibiotic cessation and
secondary outcomes included PK/PD target attainment, ICU-free days and ventilator-free days at
Day 28 post-randomization, 14- and 30-day survival, and time to WCC normalization. In this study,
CI of beta-lactam antibiotics demonstrated higher clinical cure rates (56% versus 34%; p = 0.011)
and better PK/PD target attainment compared to IB dosing. CI participants were ten-times more
likely to achieve 100% fT>MIC on Day 1 (p <0.001) and nine-times more likely to achieve 100%
fT>MIC on Day 3 (p <0.001) post-randomization. Furthermore, CI participants also demonstrated
increased ventilator-free days (22 versus 14; p = 0.043) and a reduced time to WCC normalization
(3 days versus 8 days; p <0.001) as compared to IB participants. Essentially, the findings presented
in Chapter 6 highlight that CI of beta-lactam antibiotics may be highly advantageous in those with a
high level of illness severity and not receiving RRT. The findings of the BLISS study also suggest
that CI dosing may be highly important in the management of patients who are infected with
pathogens with higher MICs considering that this study was conducted in a geographical region
which is mostly implicated with less susceptible pathogens. Although actual MIC values were not
available, 41% of the causative pathogens isolated from the BLISS study were either A. baumannii
or P. aeruginosa which mostly have higher MICs to the study antibiotics, thereby reducing the
likelihood of achieving therapeutic concentrations with IB dosing. Importantly, CI participants in
this study were three-times more likely to achieve clinical cure even after controlling for
confounding variables (OR 3.21, 95% confidence interval 1.48-6.94; p = 0.003).
A final area of study which presented in this Thesis was a structured review of published literature
describing the relevance of PK/PD characteristics of different antibiotic classes on the development
of resistance. Findings presented in Chapter 7 showed that the risk of antibiotic resistance
dramatically increases with sub-optimal dosing and this phenomenon is frequently described with
the fluoroquinolones. Traditionally, most of our treatment goals were focused on maximizing
clinical outcomes and have not included minimization of the emergence of resistance and this
strategy has indirectly contributed to rapid development of bacterial resistance. The data in Chapter
191
7 also suggest that PK/PD principles should be highly considered when dosing antibiotics in
critically ill patients as the strategy has been shown to minimize the risk of antibiotic resistance. To
prevent the emergence of resistance, it is likely that clinicians need to administer “the highest
tolerated antibiotic dose” via alternative dosing strategies particularly early in the course of
infection in critically ill patients.
192
8.2 Future directions for research
Based on the findings presented in this Thesis, there are several areas for further research to address
the following gaps in knowledge:
The theoretical basis for CI administration of beta-lactam antibiotics in critically ill patients
are currently well established. However, numerous studies lacked a design that was
sufficient to explore the effect of CI and IB dosing and this may have prevented them from
obtaining a definitive answer as to which beta-lactam dosing method should be preferred in
critically ill patients. Therefore, a large-scale, prospective, multinational RCT (n = 700) is
now required to ascertain whether the potential benefits of CI dosing of beta-lactam
antibiotics do indeed translate into survival benefit in critically ill patients. The proposed
RCT should also focus on these patients: (a) critically ill patients with severe sepsis; (b)
patients who are not receiving RRT; (c) patients with severe pneumonia and; (e) patients
who are likely to be infected with less susceptible Gram-negative pathogens.
Although numerous studies have been performed to determine the optimal beta-lactam
PK/PD targets for clinical success, very little data exist describing their roles in the
prevention of bacterial resistance. Therefore, appropriate PK/PD targets are urgently
required for this antibiotic class before a dosing regimen that minimizes the emergence of
resistance can be suggested. It follows that, once these PK/PD targets are defined, they can
be employed as one of the main end-points in future RCTs in order evaluate the relative
ability of CI versus IB dosing in reducing the emergence of resistance associated with the
use of beta-lactam antibiotics.
Most antibiotic dosage suggestion in Malaysia does not appear to be based on any published
studies in Malaysian patients but rather PK/PD analyses of healthy Caucasian volunteers and
therefore, its “suitability” and “appropriateness” for the local critically ill population is yet
to be confirmed. Accordingly, there comes the need to evaluate the effectiveness of the
current antibiotic dosing regimen in the Malaysian critically ill population via PK/PD
analysis.
193
8.3 Conclusion
Profound pathophysiological changes in critically ill patients may significantly alter the PK of beta-
lactam antibiotics and consequently reduce PK/PD target attainment. Conventional beta-lactam
dosing does not address these alterations and as such, increases the likelihood of therapeutic failure
and the emergence of resistance in critically ill patients. Altered dosing approaches (i.e., CI and EI)
may be needed to ensure optimal beta-lactam exposure and may produce better therapeutic
outcomes than IB administration, particularly in critically ill patients with severe sepsis.
194
References
1. Dellinger RP, Levy MM, Rhodes A, Annane D, Gerlach H, Opal SM, Sevransky JE, Sprung
CL, Douglas IS, Jaeschke R, Osborn TM, Nunnally ME, Townsend SR, Reinhart K,
Kleinpell RM, Angus DC, Deutschman CS, Machado FR, Rubenfeld GD, Webb SA, Beale
RJ, Vincent JL, Moreno R. Surviving sepsis campaign: international guidelines for
management of severe sepsis and septic shock: 2012. Crit Care Med 2013; 41: 580-637.
2. Garnacho-Montero J, Gutierrez-Pizarraya A, Escoresca-Ortega A, Fernandez-Delgado E,
Lopez-Sanchez JM. Adequate antibiotic therapy prior to ICU admission in patients with
severe sepsis and septic shock reduces hospital mortality. Crit Care 2015; 19: 302.
3. Ferrer R, Martin-Loeches I, Phillips G, Osborn TM, Townsend S, Dellinger RP, Artigas A,
Schorr C, Levy MM. Empiric antibiotic treatment reduces mortality in severe sepsis and
septic shock from the first hour: results from a guideline-based performance improvement
program. Crit Care Med 2014; 42: 1749-55.
4. Kumar A, Roberts D, Wood KE, Light B, Parrillo JE, Sharma S, Suppes R, Feinstein D,
Zanotti S, Taiberg L, Gurka D, Kumar A, Cheang M. Duration of hypotension before
initiation of effective antimicrobial therapy is the critical determinant of survival in human
septic shock. Crit Care Med 2006; 34: 1589-96.
5. Abdul-Aziz MH, Lipman J, Mouton JW, Hope WW, Roberts JA. Applying
pharmacokinetic/pharmacodynamic principles in critically ill patients: optimizing efficacy
and reducing resistance development. Semin Respir Crit Care Med 2015; 36: 136-53.
6. Felton TW, Hope WW, Roberts JA. How severe is antibiotic pharmacokinetic variability in
critically ill patients and what can be done about it? Diagn Microbiol Infect Dis 2014; 79:
441-7.
7. Roberts JA, Abdul-Aziz MH, Lipman J, Mouton JW, Vinks AA, Felton TW, Hope WW,
Farkas A, Neely MN, Schentag JJ, Drusano G, Frey OR, Theuretzbacher U, Kuti JL,
International Society of Anti-Infective P, the P, Pharmacodynamics Study Group of the
European Society of Clinical M, Infectious D. Individualised antibiotic dosing for patients
who are critically ill: challenges and potential solutions. Lancet Infect Dis 2014; 14: 498-
509.
8. Roberts JA, Lipman J. Pharmacokinetic issues for antibiotics in the critically ill patient. Crit
Care Med 2009; 37: 840-51; quiz 59.
9. MacGowan A. Revisiting Beta-lactams - PK/PD improves dosing of old antibiotics. Curr
Opin Pharmacol 2011; 11: 470-6.
195
10. Drusano GL. Antimicrobial pharmacodynamics: critical interactions of 'bug and drug'. Nat
Rev Microbiol 2004; 2: 289-300.
11. Craig WA. Basic pharmacodynamics of antibacterials with clinical applications to the use of
beta-lactams, glycopeptides, and linezolid. Infect Dis Clin North Am 2003; 17: 479-501.
12. Craig WA. Pharmacokinetic/pharmacodynamic parameters: rationale for antibacterial
dosing of mice and men. Clin Infect Dis 1998; 26: 1-10; quiz 11-2.
13. Abdul-Aziz MH, Dulhunty JM, Bellomo R, Lipman J, Roberts JA. Continuous beta-lactam
infusion in critically ill patients: the clinical evidence. Ann Intensive Care 2012; 2: 37.
14. Mohd Hafiz AA, Staatz CE, Kirkpatrick CM, Lipman J, Roberts JA. Continuous infusion
vs. bolus dosing: implications for beta-lactam antibiotics. Minerva Anestesiol 2012; 78: 94-
104.
15. Mouton JW, Vinks AA. Continuous infusion of beta-lactams. Curr Opin Crit Care 2007; 13:
598-606.
16. MacGowan AP, Bowker KE. Continuous infusion of beta-lactam antibiotics. Clin
Pharmacokinet 1998; 35: 391-402.
17. Craig WA, Ebert SC. Continuous infusion of beta-lactam antibiotics. Antimicrob Agents
Chemother 1992; 36: 2577-83.
18. Holford NH, Sheiner LB. Kinetics of pharmacologic response. Pharmacol Ther 1982; 16:
143-66.
19. Nicolau DP. Optimizing outcomes with antimicrobial therapy through pharmacodynamic
profiling. J Infect Chemother 2003; 9: 292-6.
20. Muller AE, Punt N, Mouton JW. Exposure to ceftobiprole is associated with microbiological
eradication and clinical cure in patients with nosocomial pneumonia. Antimicrob Agents
Chemother 2014; 58: 2512-9.
21. Muller AE, Punt N, Mouton JW. Optimal exposures of ceftazidime predict the probability of
microbiological and clinical outcome in the treatment of nosocomial pneumonia. J
Antimicrob Chemother 2013; 68: 900-6.
22. Crandon JL, Bulik CC, Kuti JL, Nicolau DP. Clinical pharmacodynamics of cefepime in
patients infected with Pseudomonas aeruginosa. Antimicrob Agents Chemother 2010; 54:
1111-6.
23. Li C, Du X, Kuti JL, Nicolau DP. Clinical pharmacodynamics of meropenem in patients
with lower respiratory tract infections. Antimicrob Agents Chemother 2007; 51: 1725-30.
24. Drusano GL. Pharmacokinetics and pharmacodynamics of antimicrobials. Clin Infect Dis
2007; 45 Suppl 1: S89-95.
196
25. Ariano RE, Nyhlen A, Donnelly JP, Sitar DS, Harding GK, Zelenitsky SA.
Pharmacokinetics and pharmacodynamics of meropenem in febrile neutropenic patients with
bacteremia. Ann Pharmacother 2005; 39: 32-8.
26. Tam VH, McKinnon PS, Akins RL, Rybak MJ, Drusano GL. Pharmacodynamics of
cefepime in patients with Gram-negative infections. J Antimicrob Chemother 2002; 50: 425-
8.
27. Roberts JA, Paul SK, Akova M, Bassetti M, De Waele JJ, Dimopoulos G, Kaukonen KM,
Koulenti D, Martin C, Montravers P, Rello J, Rhodes A, Starr T, Wallis SC, Lipman J,
Study D. DALI: defining antibiotic levels in intensive care unit patients: are current beta-
lactam antibiotic doses sufficient for critically ill patients? Clin Infect Dis 2014; 58: 1072-
83.
28. McKinnon PS, Paladino JA, Schentag JJ. Evaluation of area under the inhibitory curve
(AUIC) and time above the minimum inhibitory concentration (T>MIC) as predictors of
outcome for cefepime and ceftazidime in serious bacterial infections. Int J Antimicrob
Agents 2008; 31: 345-51.
29. Stevenson EK, Rubenstein AR, Radin GT, Wiener RS, Walkey AJ. Two decades of
mortality trends among patients with severe sepsis: a comparative meta-analysis*. Crit Care
Med 2014; 42: 625-31.
30. Kaukonen KM, Bailey M, Suzuki S, Pilcher D, Bellomo R. Mortality related to severe
sepsis and septic shock among critically ill patients in Australia and New Zealand, 2000-
2012. JAMA 2014; 311: 1308-16.
31. Vincent JL, Rello J, Marshall J, Silva E, Anzueto A, Martin CD, Moreno R, Lipman J,
Gomersall C, Sakr Y, Reinhart K, Investigators EIGo. International study of the prevalence
and outcomes of infection in intensive care units. JAMA 2009; 302: 2323-9.
32. Arise, Committee AAM. The outcome of patients with sepsis and septic shock presenting to
emergency departments in Australia and New Zealand. Crit Care Resusc 2007; 9: 8-18.
33. Vincent JL, Sakr Y, Sprung CL, Ranieri VM, Reinhart K, Gerlach H, Moreno R, Carlet J,
Le Gall JR, Payen D, Sepsis Occurrence in Acutely Ill Patients I. Sepsis in European
intensive care units: results of the SOAP study. Crit Care Med 2006; 34: 344-53.
34. Finfer S, Bellomo R, Lipman J, French C, Dobb G, Myburgh J. Adult-population incidence
of severe sepsis in Australian and New Zealand intensive care units. Intensive Care Med
2004; 30: 589-96.
35. Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR.
Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and
associated costs of care. Crit Care Med 2001; 29: 1303-10.
197
36. Tong GM, Tai LL, Tan CC, Othman AS, Lim CH. Malaysian Registry of Intensive Care
2011 report. 2011.
37. Stoller J, Halpin L, Weis M, Aplin B, Qu W, Georgescu C, Nazzal M. Epidemiology of
severe sepsis: 2008-2012. J Crit Care 2015.
38. Christaki E, Opal SM. Is the mortality rate for septic shock really decreasing? Curr Opin
Crit Care 2008; 14: 580-6.
39. Friedman G, Silva E, Vincent JL. Has the mortality of septic shock changed with time. Crit
Care Med 1998; 26: 2078-86.
40. Dombrovskiy VY, Martin AA, Sunderram J, Paz HL. Rapid increase in hospitalization and
mortality rates for severe sepsis in the United States: a trend analysis from 1993 to 2003.
Crit Care Med 2007; 35: 1244-50.
41. Cheng B, Xie G, Yao S, Wu X, Guo Q, Gu M, Fang Q, Xu Q, Wang D, Jin Y, Yuan S,
Wang J, Du Z, Sun Y, Fang X. Epidemiology of severe sepsis in critically ill surgical
patients in ten university hospitals in China. Crit Care Med 2007; 35: 2538-46.
42. Tanriover MD, Guven GS, Sen D, Unal S, Uzun O. Epidemiology and outcome of sepsis in
a tertiary-care hospital in a developing country. Epidemiol Infect 2006; 134: 315-22.
43. Harrison DA, Welch CA, Eddleston JM. The epidemiology of severe sepsis in England,
Wales and Northern Ireland, 1996 to 2004: secondary analysis of a high quality clinical
database, the ICNARC Case Mix Programme Database. Crit Care 2006; 10: R42.
44. Adrie C, Alberti C, Chaix-Couturier C, Azoulay E, De Lassence A, Cohen Y, Meshaka P,
Cheval C, Thuong M, Troche G, Garrouste-Orgeas M, Timsit JF. Epidemiology and
economic evaluation of severe sepsis in France: age, severity, infection site, and place of
acquisition (community, hospital, or intensive care unit) as determinants of workload and
cost. J Crit Care 2005; 20: 46-58.
45. Silva E, Pedro Mde A, Sogayar AC, Mohovic T, Silva CL, Janiszewski M, Cal RG, de
Sousa EF, Abe TP, de Andrade J, de Matos JD, Rezende E, Assuncao M, Avezum A, Rocha
PC, de Matos GF, Bento AM, Correa AD, Vieira PC, Knobel E, Brazilian Sepsis
Epidemiological S. Brazilian Sepsis Epidemiological Study (BASES study). Crit Care 2004;
8: R251-60.
46. Coopersmith CM, Wunsch H, Fink MP, Linde-Zwirble WT, Olsen KM, Sommers MS,
Anand KJ, Tchorz KM, Angus DC, Deutschman CS. A comparison of critical care research
funding and the financial burden of critical illness in the United States. Crit Care Med 2012;
40: 1072-9.
47. Donahoe MP. Current venues of care and related costs for the chronically critically ill.
Respir Care 2012; 57: 867-86; discussion 86-8.
198
48. Bone RC, Balk RA, Cerra FB, Dellinger RP, Fein AM, Knaus WA, Schein RM, Sibbald
WJ. Definitions for sepsis and organ failure and guidelines for the use of innovative
therapies in sepsis. The ACCP/SCCM Consensus Conference Committee. American College
of Chest Physicians/Society of Critical Care Medicine. Chest 1992; 101: 1644-55.
49. Calandra T, Cohen J, International Sepsis Forum Definition of Infection in the ICUCC. The
international sepsis forum consensus conference on definitions of infection in the intensive
care unit. Crit Care Med 2005; 33: 1538-48.
50. Levy MM, Fink MP, Marshall JC, Abraham E, Angus D, Cook D, Cohen J, Opal SM,
Vincent JL, Ramsay G, Sccm/Esicm/Accp/Ats/Sis. 2001 SCCM/ESICM/ACCP/ATS/SIS
International Sepsis Definitions Conference. Crit Care Med 2003; 31: 1250-6.
51. Marshall JC, Cook DJ, Christou NV, Bernard GR, Sprung CL, Sibbald WJ. Multiple organ
dysfunction score: a reliable descriptor of a complex clinical outcome. Crit Care Med 1995;
23: 1638-52.
52. Ferreira FL, Bota DP, Bross A, Melot C, Vincent JL. Serial evaluation of the SOFA score to
predict outcome in critically ill patients. JAMA 2001; 286: 1754-8.
53. Abdul-Aziz MH, Abd Rahman AN, Mat-Nor MB, Sulaiman H, Wallis SC, Lipman J,
Roberts JA, Staatz CE. Population Pharmacokinetics of Doripenem in Critically Ill Patients
with Sepsis in a Malaysian Intensive Care Unit. Antimicrob Agents Chemother 2015; 60:
206-14.
54. Sime FB, Roberts MS, Peake SL, Lipman J, Roberts JA. Does Beta-lactam Pharmacokinetic
Variability in Critically Ill Patients Justify Therapeutic Drug Monitoring? A Systematic
Review. Ann Intensive Care 2012; 2: 35.
55. Pea F. Plasma Pharmacokinetics of Antimicrobial Agents in Critically ill Patients. Curr Clin
Pharmacol 2012.
56. Goncalves-Pereira J, Povoa P. Antibiotics in critically ill patients: a systematic review of the
pharmacokinetics of beta-lactams. Crit Care 2011; 15: R206.
57. Taccone FS, Laterre PF, Dugernier T, Spapen H, Delattre I, Wittebole X, De Backer D,
Layeux B, Wallemacq P, Vincent JL, Jacobs F. Insufficient beta-lactam concentrations in
the early phase of severe sepsis and septic shock. Crit Care 2010; 14: R126.
58. Rice TW, Bernard GR. Therapeutic intervention and targets for sepsis. Annu Rev Med
2005; 56: 225-48.
59. Bochud PY, Calandra T. Pathogenesis of sepsis: new concepts and implications for future
treatment. BMJ 2003; 326: 262-6.
199
60. Parrillo JE, Parker MM, Natanson C, Suffredini AF, Danner RL, Cunnion RE, Ognibene FP.
Septic shock in humans. Advances in the understanding of pathogenesis, cardiovascular
dysfunction, and therapy. Ann Intern Med 1990; 113: 227-42.
61. van der Poll T. Immunotherapy of sepsis. Lancet Infect Dis 2001; 1: 165-74.
62. Gosling P, Sanghera K, Dickson G. Generalized vascular permeability and pulmonary
function in patients following serious trauma. J Trauma 1994; 36: 477-81.
63. Nuytinck HK, Offermans XJ, Kubat K, Goris JA. Whole-body inflammation in trauma
patients. An autopsy study. Arch Surg 1988; 123: 1519-24.
64. Pinder M, Bellomo R, Lipman J. Pharmacological principles of antibiotic prescription in the
critically ill. Anaesth Intensive Care 2002; 30: 134-44.
65. Ocampos-Martinez E, Penaccini L, Scolletta S, Abdelhadii A, Devigili A, Cianferoni S, de
Backer D, Jacobs F, Cotton F, Vincent JL, Taccone FS. Determinants of early inadequate
vancomycin concentrations during continuous infusion in septic patients. Int J Antimicrob
Agents 2012; 39: 332-7.
66. Joukhadar C, Klein N, Mayer BX, Kreischitz N, Delle-Karth G, Palkovits P, Heinz G,
Muller M. Plasma and tissue pharmacokinetics of cefpirome in patients with sepsis. Crit
Care Med 2002; 30: 1478-82.
67. Lipman J, Wallis SC, Rickard CM, Fraenkel D. Low cefpirome levels during twice daily
dosing in critically ill septic patients: pharmacokinetic modelling calls for more frequent
dosing. Intensive Care Med 2001; 27: 363-70.
68. Botha FJ, van der Bijl P, Seifart HI, Parkin DP. Fluctuation of the volume of distribution of
amikacin and its effect on once-daily dosage and clearance in a seriously ill patient.
Intensive Care Med 1996; 22: 443-6.
69. Conil JM, Georges B, Lavit M, Laguerre J, Samii K, Houin G, Saivin S. A population
pharmacokinetic approach to ceftazidime use in burn patients: influence of glomerular
filtration, gender and mechanical ventilation. Br J Clin Pharmacol 2007; 64: 27-35.
70. Martin C, Lambert D, Bruguerolle B, Saux P, Freney J, Fleurette J, Meugnier H, Gouin F.
Ofloxacin pharmacokinetics in mechanically ventilated patients. Antimicrob Agents
Chemother 1991; 35: 1582-5.
71. Triginer C, Fernandez R, Izquierdo I, Rello J, Benito S. Gentamicin pharmacokinetic
changes related to mechanical ventilation. DICP 1989; 23: 923-4.
72. Annat G, Viale JP, Bui Xuan B, Hadj Aissa O, Benzoni D, Vincent M, Gharib C, Motin J.
Effect of PEEP ventilation on renal function, plasma renin, aldosterone, neurophysins and
urinary ADH, and prostaglandins. Anesthesiology 1983; 58: 136-41.
200
73. Roberts JA, Roberts MS, Robertson TA, Cross SE, Lipman J. A novel way to investigate the
effects of plasma exchange on antibiotic levels: use of microdialysis. Int J Antimicrob
Agents 2008; 31: 240-4.
74. Adnan S, Li JX, Wallis SC, Rudd M, Jarrett P, Paterson DL, Lipman J, Udy AA, Roberts
JA. Pharmacokinetics of meropenem and piperacillin in critically ill patients with indwelling
surgical drains. Int J Antimicrob Agents 2013; 42: 90-3.
75. Lodise TP, Jr., Rhoney DH, Tam VH, McKinnon PS, Drusano GL. Pharmacodynamic
profiling of cefepime in plasma and cerebrospinal fluid of hospitalized patients with external
ventriculostomies. Diagn Microbiol Infect Dis 2006; 54: 223-30.
76. Ronchera-Oms CL, Tormo C, Ordovas JP, Abad J, Jimenez NV. Expanded gentamicin
volume of distribution in critically ill adult patients receiving total parenteral nutrition. J
Clin Pharm Ther 1995; 20: 253-8.
77. Ryan DM. Pharmacokinetics of antibiotics in natural and experimental superficial
compartments in animals and humans. J Antimicrob Chemother 1993; 31 Suppl D: 1-16.
78. Jamal J-A, Abdul-Aziz M-H, Lipman J, Roberts JA. Defining Antibiotic Dosing in Lung
Infections. Clin Pulm Med 2013; 20: 121-28.
79. Buijk SE, Gyssens IC, Mouton JW, Metselaar HJ, Groenland TH, Verbrugh HA, Bruining
HA. Perioperative pharmacokinetics of cefotaxime in serum and bile during continuous and
intermittent infusion in liver transplant patients. J Antimicrob Chemother 2004; 54: 199-
205.
80. Boselli E, Breilh D, Cannesson M, Xuereb F, Rimmele T, Chassard D, Saux MC,
Allaouchiche B. Steady-state plasma and intrapulmonary concentrations of
piperacillin/tazobactam 4 g/0.5 g administered to critically ill patients with severe
nosocomial pneumonia. Intensive Care Med 2004; 30: 976-9.
81. Boselli E, Breilh D, Duflo F, Saux MC, Debon R, Chassard D, Allaouchiche B. Steady-state
plasma and intrapulmonary concentrations of cefepime administered in continuous infusion
in critically ill patients with severe nosocomial pneumonia. Crit Care Med 2003; 31: 2102-6.
82. Buijk SL, Gyssens IC, Mouton JW, Van Vliet A, Verbrugh HA, Bruining HA.
Pharmacokinetics of ceftazidime in serum and peritoneal exudate during continuous versus
intermittent administration to patients with severe intra-abdominal infections. J Antimicrob
Chemother 2002; 49: 121-8.
83. Varghese JM, Jarrett P, Wallis SC, Boots RJ, Kirkpatrick CM, Lipman J, Roberts JA. Are
interstitial fluid concentrations of meropenem equivalent to plasma concentrations in
critically ill patients receiving continuous renal replacement therapy? J Antimicrob
Chemother 2015; 70: 528-33.
201
84. Varghese JM, Jarrett P, Boots RJ, Kirkpatrick CM, Lipman J, Roberts JA. Pharmacokinetics
of piperacillin and tazobactam in plasma and subcutaneous interstitial fluid in critically ill
patients receiving continuous venovenous haemodiafiltration. Int J Antimicrob Agents 2014;
43: 343-8.
85. Roberts JA, Roberts MS, Robertson TA, Dalley AJ, Lipman J. Piperacillin penetration into
tissue of critically ill patients with sepsis--bolus versus continuous administration? Crit Care
Med 2009; 37: 926-33.
86. Roberts JA, Kirkpatrick CM, Roberts MS, Robertson TA, Dalley AJ, Lipman J. Meropenem
dosing in critically ill patients with sepsis and without renal dysfunction: intermittent bolus
versus continuous administration? Monte Carlo dosing simulations and subcutaneous tissue
distribution. J Antimicrob Chemother 2009; 64: 142-50.
87. Buerger C, Plock N, Dehghanyar P, Joukhadar C, Kloft C. Pharmacokinetics of unbound
linezolid in plasma and tissue interstitium of critically ill patients after multiple dosing using
microdialysis. Antimicrob Agents Chemother 2006; 50: 2455-63.
88. Joukhadar C, Klein N, Dittrich P, Zeitlinger M, Geppert A, Skhirtladze K, Frossard M,
Heinz G, Muller M. Target site penetration of fosfomycin in critically ill patients. J
Antimicrob Chemother 2003; 51: 1247-52.
89. Jaruratanasirikul S, Thengyai S, Wongpoowarak W, Wattanavijitkul T, Tangkitwanitjaroen
K, Sukarnjanaset W, Jullangkoon M, Samaeng M. Population pharmacokinetics and Monte
Carlo dosing simulations of meropenem during the early phase of severe sepsis and septic
shock in critically ill patients in intensive care units. Antimicrobial agents and chemotherapy
2015; 59: 2995-3001.
90. Joukhadar C, Frossard M, Mayer BX, Brunner M, Klein N, Siostrzonek P, Eichler HG,
Muller M. Impaired target site penetration of beta-lactams may account for therapeutic
failure in patients with septic shock. Crit Care Med 2001; 29: 385-91.
91. Sauermann R, Delle-Karth G, Marsik C, Steiner I, Zeitlinger M, Mayer-Helm BX,
Georgopoulos A, Muller M, Joukhadar C. Pharmacokinetics and pharmacodynamics of
cefpirome in subcutaneous adipose tissue of septic patients. Antimicrob Agents Chemother
2005; 49: 650-5.
92. Namendys-Silva SA, Gonzalez-Herrera MO, Texcocano-Becerra J, Herrera-Gomez A.
Hypoalbuminemia in critically ill patients with cancer: incidence and mortality. Am J Hosp
Palliat Care 2011; 28: 253-7.
93. Finfer S, Bellomo R, McEvoy S, Lo SK, Myburgh J, Neal B, Norton R. Effect of baseline
serum albumin concentration on outcome of resuscitation with albumin or saline in patients
202
in intensive care units: analysis of data from the saline versus albumin fluid evaluation
(SAFE) study. BMJ 2006; 333: 1044.
94. Fleck A, Raines G, Hawker F, Trotter J, Wallace PI, Ledingham IM, Calman KC. Increased
vascular permeability: a major cause of hypoalbuminaemia in disease and injury. Lancet
1985; 1: 781-4.
95. Kushner I. The phenomenon of the acute phase response. Ann N Y Acad Sci 1982; 389: 39-
48.
96. Kirsch R, Frith L, Black E, Hoffenberg R. Regulation of albumin synthesis and catabolism
by alteration of dietary protein. Nature 1968; 217: 578-9.
97. Roberts JA, Stove V, De Waele JJ, Sipinkoski B, McWhinney B, Ungerer JP, Akova M,
Bassetti M, Dimopoulos G, Kaukonen KM, Koulenti D, Martin C, Montravers P, Rello J,
Rhodes A, Starr T, Wallis SC, Lipman J. Variability in protein binding of teicoplanin and
achievement of therapeutic drug monitoring targets in critically ill patients: Lessons from
the DALI Study. Int J Antimicrob Agents 2014.
98. Abdul-Aziz MH, McDonald C, McWhinney B, Ungerer JP, Lipman J, Roberts JA. Low
Flucloxacillin Concentrations in a Patient With Central Nervous System Infection: The
Need for Plasma and Cerebrospinal Fluid Drug Monitoring in the ICU. Ann Pharmacother
2014.
99. Wong G, Briscoe S, Adnan S, McWhinney B, Ungerer J, Lipman J, Roberts JA. Protein
binding of beta-lactam antibiotics in critically ill patients: can we successfully predict
unbound concentrations? Antimicrob Agents Chemother 2013; 57: 6165-70.
100. Hayashi Y, Lipman J, Udy AA, Ng M, McWhinney B, Ungerer J, Lust K, Roberts JA. beta-
Lactam therapeutic drug monitoring in the critically ill: optimising drug exposure in patients
with fluctuating renal function and hypoalbuminaemia. Int J Antimicrob Agents 2013; 41:
162-6.
101. Ulldemolins M, Roberts JA, Rello J, Paterson DL, Lipman J. The effects of
hypoalbuminaemia on optimizing antibacterial dosing in critically ill patients. Clin
Pharmacokinet 2011; 50: 99-110.
102. Ulldemolins M, Roberts JA, Wallis SC, Rello J, Lipman J. Flucloxacillin dosing in critically
ill patients with hypoalbuminaemia: special emphasis on unbound pharmacokinetics. J
Antimicrob Chemother 2010; 65: 1771-8.
103. Brink AJ, Richards GA, Schillack V, Kiem S, Schentag J. Pharmacokinetics of once-daily
dosing of ertapenem in critically ill patients with severe sepsis. Int J Antimicrob Agents
2009; 33: 432-6.
203
104. Brink AJ, Richards GA, Cummins RR, Lambson J. Recommendations to achieve rapid
therapeutic teicoplanin plasma concentrations in adult hospitalised patients treated for
sepsis. Int J Antimicrob Agents 2008; 32: 455-8.
105. Burkhardt O, Kumar V, Katterwe D, Majcher-Peszynska J, Drewelow B, Derendorf H,
Welte T. Ertapenem in critically ill patients with early-onset ventilator-associated
pneumonia: pharmacokinetics with special consideration of free-drug concentration. J
Antimicrob Chemother 2007; 59: 277-84.
106. Joynt GM, Lipman J, Gomersall CD, Young RJ, Wong EL, Gin T. The pharmacokinetics of
once-daily dosing of ceftriaxone in critically ill patients. J Antimicrob Chemother 2001; 47:
421-9.
107. del Mar Fernandez de Gatta Garcia M, Revilla N, Calvo MV, Dominguez-Gil A, Sanchez
Navarro A. Pharmacokinetic/pharmacodynamic analysis of vancomycin in ICU patients.
Intensive Care Med 2007; 33: 279-85.
108. Pea F, Viale P, Candoni A, Pavan F, Pagani L, Damiani D, Casini M, Furlanut M.
Teicoplanin in patients with acute leukaemia and febrile neutropenia: a special population
benefiting from higher dosages. Clin Pharmacokinet 2004; 43: 405-15.
109. Udy AA, Roberts JA, Lipman J. Implications of augmented renal clearance in critically ill
patients. Nat Rev Nephrol 2011; 7: 539-43.
110. Roberts DM. The relevance of drug clearance to antibiotic dosing in critically ill patients.
Curr Pharm Biotechnol 2011; 12: 2002-14.
111. Di Giantomasso D, Morimatsu H, Bellomo R, May CN. Effect of low-dose vasopressin
infusion on vital organ blood flow in the conscious normal and septic sheep. Anaesth
Intensive Care 2006; 34: 427-33.
112. Di Giantomasso D, May CN, Bellomo R. Norepinephrine and vital organ blood flow during
experimental hyperdynamic sepsis. Intensive Care Med 2003; 29: 1774-81.
113. Di Giantomasso D, May CN, Bellomo R. Vital organ blood flow during hyperdynamic
sepsis. Chest 2003; 124: 1053-9.
114. Wan L, Bellomo R, May CN. The effects of normal and hypertonic saline on regional blood
flow and oxygen delivery. Anesth Analg 2007; 105: 141-7.
115. Pea F, Porreca L, Baraldo M, Furlanut M. High vancomycin dosage regimens required by
intensive care unit patients cotreated with drugs to improve haemodynamics following
cardiac surgical procedures. J Antimicrob Chemother 2000; 45: 329-35.
116. De Cock PA, Standing JF, Barker CI, de Jaeger A, Dhont E, Carlier M, Verstraete AG,
Delanghe JR, Robays H, De Paepe P. Augmented Renal Clearance Implies a Need for
204
Increased Amoxicillin-Clavulanic Acid Dosing in Critically Ill Children. Antimicrob Agents
Chemother 2015; 59: 7027-35.
117. Huttner A, Von Dach E, Renzoni A, Huttner BD, Affaticati M, Pagani L, Daali Y, Pugin J,
Karmime A, Fathi M, Lew D, Harbarth S. Augmented renal clearance, low beta-lactam
concentrations and clinical outcomes in the critically ill: an observational prospective cohort
study. Int J Antimicrob Agents 2015; 45: 385-92.
118. Udy AA, Lipman J, Jarrett P, Klein K, Wallis SC, Patel K, Kirkpatrick CM, Kruger PS,
Paterson DL, Roberts MS, Roberts JA. Are standard doses of piperacillin sufficient for
critically ill patients with augmented creatinine clearance? Crit Care 2015; 19: 28.
119. Akers KS, Niece KL, Chung KK, Cannon JW, Cota JM, Murray CK. Modified Augmented
Renal Clearance score predicts rapid piperacillin and tazobactam clearance in critically ill
surgery and trauma patients. J Trauma Acute Care Surg 2014; 77: S163-70.
120. Carlier M, Carrette S, Roberts JA, Stove V, Verstraete A, Hoste E, Depuydt P,
Decruyenaere J, Lipman J, Wallis SC, De Waele JJ. Meropenem and
piperacillin/tazobactam prescribing in critically ill patients: does augmented renal clearance
affect pharmacokinetic/pharmacodynamic target attainment when extended infusions are
used? Crit Care 2013; 17: R84.
121. Udy AA, Varghese JM, Altukroni M, Briscoe S, McWhinney BC, Ungerer JP, Lipman J,
Roberts JA. Subtherapeutic initial beta-lactam concentrations in select critically ill patients:
association between augmented renal clearance and low trough drug concentrations. Chest
2012; 142: 30-9.
122. Baptista JP, Sousa E, Martins PJ, Pimentel JM. Augmented renal clearance in septic patients
and implications for vancomycin optimisation. Int J Antimicrob Agents 2012; 39: 420-3.
123. Udy AA, Putt MT, Shanmugathasan S, Roberts JA, Lipman J. Augmented renal clearance in
the Intensive Care Unit: an illustrative case series. Int J Antimicrob Agents 2010; 35: 606-8.
124. Conil JM, Georges B, Mimoz O, Dieye E, Ruiz S, Cougot P, Samii K, Houin G, Saivin S.
Influence of renal function on trough serum concentrations of piperacillin in intensive care
unit patients. Intensive Care Med 2006; 32: 2063-6.
125. Udy AA, Morton FJ, Nguyen-Pham S, Jarrett P, Lassig-Smith M, Stuart J, Dunlop R, Starr
T, Boots RJ, Lipman J. A comparison of CKD-EPI estimated glomerular filtration rate and
measured creatinine clearance in recently admitted critically ill patients with normal plasma
creatinine concentrations. BMC Nephrol 2013; 14: 250.
126. Martin JH, Fay MF, Udy A, Roberts J, Kirkpatrick C, Ungerer J, Lipman J. Pitfalls of using
estimations of glomerular filtration rate in an intensive care population. Intern Med J 2011;
41: 537-43.
205
127. Hoste EA, Damen J, Vanholder RC, Lameire NH, Delanghe JR, Van den Hauwe K,
Colardyn FA. Assessment of renal function in recently admitted critically ill patients with
normal serum creatinine. Nephrol Dial Transplant 2005; 20: 747-53.
128. Lipman J, Gous AG, Mathivha LR, Tshukutsoane S, Scribante J, Hon H, Pinder M, Riera-
Fanego JF, Verhoef L, Stass H. Ciprofloxacin pharmacokinetic profiles in paediatric sepsis:
how much ciprofloxacin is enough? Intensive Care Med 2002; 28: 493-500.
129. Udy AA, Roberts JA, De Waele JJ, Paterson DL, Lipman J. What's behind the failure of
emerging antibiotics in the critically ill? Understanding the impact of altered
pharmacokinetics and augmented renal clearance. Int J Antimicrob Agents 2012.
130. Ulldemolins M, Roberts JA, Lipman J, Rello J. Antibiotic dosing in multiple organ
dysfunction syndrome. Chest 2011; 139: 1210-20.
131. Marshall JC. Inflammation, coagulopathy, and the pathogenesis of multiple organ
dysfunction syndrome. Crit Care Med 2001; 29: S99-106.
132. Power BM, Forbes AM, van Heerden PV, Ilett KF. Pharmacokinetics of drugs used in
critically ill adults. Clin Pharmacokinet 1998; 34: 25-56.
133. Brogard JM, Jehl F, Blickle JF, Dorner M, Arnaud JP, Monteil H. Biliary pharmacokinetic
profile of piperacillin: experimental data and evaluation in man. Int J Clin Pharmacol Ther
Toxicol 1990; 28: 462-70.
134. Brogard JM, Jehl F, Blickle JF, Adloff M, Dorner M, Montell H. Biliary elimination of
ticarcillin plus clavulanic acid (Claventin): experimental and clinical study. Int J Clin
Pharmacol Ther Toxicol 1989; 27: 135-44.
135. Bagshaw SM, Lapinsky S, Dial S, Arabi Y, Dodek P, Wood G, Ellis P, Guzman J, Marshall
J, Parrillo JE, Skrobik Y, Kumar A, Cooperative Antimicrobial Therapy of Septic Shock
Database Research G. Acute kidney injury in septic shock: clinical outcomes and impact of
duration of hypotension prior to initiation of antimicrobial therapy. Intensive Care Med
2009; 35: 871-81.
136. Bagshaw SM, George C, Dinu I, Bellomo R. A multi-centre evaluation of the RIFLE criteria
for early acute kidney injury in critically ill patients. Nephrol Dial Transplant 2008; 23:
1203-10.
137. Bagshaw SM, Uchino S, Bellomo R, Morimatsu H, Morgera S, Schetz M, Tan I, Bouman C,
Macedo E, Gibney N, Tolwani A, Oudemans-van Straaten HM, Ronco C, Kellum JA,
Beginning, Ending Supportive Therapy for the Kidney I. Septic acute kidney injury in
critically ill patients: clinical characteristics and outcomes. Clin J Am Soc Nephrol 2007; 2:
431-9.
206
138. Jamal JA, Mueller BA, Choi GY, Lipman J, Roberts JA. How can we ensure effective
antibiotic dosing in critically ill patients receiving different types of renal replacement
therapy? Diagn Microbiol Infect Dis 2015; 82: 92-103.
139. Jamal JA, Udy AA, Lipman J, Roberts JA. The impact of variation in renal replacement
therapy settings on piperacillin, meropenem, and vancomycin drug clearance in the critically
ill: an analysis of published literature and dosing regimens*. Crit Care Med 2014; 42: 1640-
50.
140. Roberts DM, Roberts JA, Roberts MS, Liu X, Nair P, Cole L, Lipman J, Bellomo R.
Variability of antibiotic concentrations in critically ill patients receiving continuous renal
replacement therapy: A multicentre pharmacokinetic study*. Crit Care Med 2012; 40: 1523-
28.
141. Jamal JA, Economou CJ, Lipman J, Roberts JA. Improving antibiotic dosing in special
situations in the ICU: burns, renal replacement therapy and extracorporeal membrane
oxygenation. Curr Opin Crit Care 2012; 18: 460-71.
142. Choi G, Gomersall CD, Tian Q, Joynt GM, Freebairn R, Lipman J. Principles of
antibacterial dosing in continuous renal replacement therapy. Crit Care Med 2009; 37: 2268-
82.
143. Donadello K, Antonucci E, Cristallini S, Roberts JA, Beumier M, Scolletta S, Jacobs F,
Rondelet B, de Backer D, Vincent JL, Taccone FS. beta-Lactam pharmacokinetics during
extracorporeal membrane oxygenation therapy: A case-control study. Int J Antimicrob
Agents 2015; 45: 278-82.
144. Donadello K, Roberts JA, Cristallini S, Beumier M, Shekar K, Jacobs F, Belhaj A, Vincent
JL, de Backer D, Taccone FS. Vancomycin population pharmacokinetics during
extracorporeal membrane oxygenation therapy: a matched cohort study. Crit Care 2014; 18:
632.
145. Shekar K, Fraser JF, Taccone FS, Welch S, Wallis SC, Mullany DV, Lipman J, Roberts JA.
The combined effects of extracorporeal membrane oxygenation and renal replacement
therapy on meropenem pharmacokinetics: a matched cohort study. Crit Care 2014; 18: 565.
146. Shekar K, Fraser JF, Smith MT, Roberts JA. Pharmacokinetic changes in patients receiving
extracorporeal membrane oxygenation. J Crit Care 2012.
147. Aitken SL, Altshuler J, Guervil DJ, Hirsch EB, Ostrosky-Zeichner LL, Ericsson CD, Tam
VH. Cefepime free minimum concentration to minimum inhibitory concentration
(fCmin/MIC) ratio predicts clinical failure in patients with Gram-negative bacterial
pneumonia. Int J Antimicrob Agents 2015; 45: 541-4.
207
148. Mouton JW, Ambrose PG, Canton R, Drusano GL, Harbarth S, MacGowan A,
Theuretzbacher U, Turnidge J. Conserving antibiotics for the future: new ways to use old
and new drugs from a pharmacokinetic and pharmacodynamic perspective. Drug Resist
Updat 2011; 14: 107-17.
149. Roberts JA, Kruger P, Paterson DL, Lipman J. Antibiotic resistance--what's dosing got to do
with it? Crit Care Med 2008; 36: 2433-40.
150. Taccone FS, Cotton F, Roisin S, Vincent JL, Jacobs F. Optimal meropenem concentrations
to treat multidrug-resistant Pseudomonas aeruginosa septic shock. Antimicrob Agents
Chemother 2012; 56: 2129-31.
151. Angus BJ, Smith MD, Suputtamongkol Y, Mattie H, Walsh AL, Wuthiekanun V,
Chaowagul W, White NJ. Pharmacokinetic-pharmacodynamic evaluation of ceftazidime
continuous infusion vs intermittent bolus injection in septicaemic melioidosis. Br J Clin
Pharmacol 2000; 50: 184-91.
152. Mouton JW, den Hollander JG. Killing of Pseudomonas aeruginosa during continuous and
intermittent infusion of ceftazidime in an in vitro pharmacokinetic model. Antimicrob
Agents Chemother 1994; 38: 931-6.
153. Sinnollareddy MG, Roberts MS, Lipman J, Roberts JA. Beta-lactam
Pharmacokinetics/Pharmacodynamics in critically ill patients and strategies for dose-
optimisation - a structured review. Clin Exp Pharmacol Physiol 2012.
154. Rodvold KA. Pharmacodynamics of antiinfective therapy: taking what we know to the
patient's bedside. Pharmacotherapy 2001; 21: 319S-30S.
155. Bowker KE, Holt HA, Reeves DS, MacGowan AP. Bactericidal activity, post antibiotic
effect and modified controlled effective regrowth time of meropenem at high concentrations.
J Antimicrob Chemother 1996; 38: 1055-60.
156. Hanberger H, Nilsson LE, Nilsson M, Maller R. Post-antibiotic effect of beta-lactam
antibiotics on gram-negative bacteria in relation to morphology, initial killing and MIC. Eur
J Clin Microbiol Infect Dis 1991; 10: 927-34.
157. Gudmundsson S, Vogelman B, Craig WA. The in-vivo postantibiotic effect of imipenem
and other new antimicrobials. J Antimicrob Chemother 1986; 18 Suppl E: 67-73.
158. Bustamante CI, Drusano GL, Tatem BA, Standiford HC. Postantibiotic effect of imipenem
on Pseudomonas aeruginosa. Antimicrob Agents Chemother 1984; 26: 678-82.
159. Burgess DS, Hastings RW, Hardin TC. Pharmacokinetics and pharmacodynamics of
cefepime administered by intermittent and continuous infusion. Clin Ther 2000; 22: 66-75.
208
160. White R, Friedrich L, Burgess D, Warkentin D, Bosso J. Comparative in vitro
pharmacodynamics of imipenem and meropenem against Pseudomonas aeruginosa.
Antimicrob Agents Chemother 1996; 40: 904-8.
161. Hanberger H, Nilsson LE, Maller R, Nilsson M. Pharmacodynamics of beta-lactam
antibiotics on gram-negative bacteria: initial killing, morphology and postantibiotic effect.
Scand J Infect Dis Suppl 1990; 74: 118-23.
162. Craig WA, Ebert SC. Killing and regrowth of bacteria in vitro: a review. Scand J Infect Dis
Suppl 1990; 74: 63-70.
163. Abbott IJ, Roberts JA. Infusional beta-lactam antibiotics in febrile neutropenia: has the time
come? Curr Opin Infect Dis 2012; 25: 619-25.
164. De Waele JJ, Lipman J, Akova M, Bassetti M, Dimopoulos G, Kaukonen M, Koulenti D,
Martin C, Montravers P, Rello J, Rhodes A, Udy AA, Starr T, Wallis SC, Roberts JA. Risk
factors for target non-attainment during empirical treatment with beta-lactam antibiotics in
critically ill patients. Intensive Care Med 2014; 40: 1340-51.
165. De Waele J, Carlier M, Hoste E, Depuydt P, Decruyenaere J, Wallis SC, Lipman J, Roberts
JA. Extended versus bolus infusion of meropenem and piperacillin: a pharmacokinetic
analysis. Minerva Anestesiol 2014; 80: 1302-9.
166. Dulhunty JM, Roberts JA, Davis JS, Webb SA, Bellomo R, Gomersall C, Shirwadkar C,
Eastwood GM, Myburgh J, Paterson DL, Lipman J. Continuous infusion of beta-lactam
antibiotics in severe sepsis: a multicenter double-blind, randomized controlled trial. Clin
Infect Dis 2013; 56: 236-44.
167. Breilh D, Fleureau C, Gordien JB, Joanes-Boyau O, Texier-Maugein J, Rapaport S, Boselli
E, Janvier G, Saux MC. Pharmacokinetics of free ertapenem in critically ill septic patients:
intermittent versus continuous infusion. Minerva Anestesiol 2011; 77: 1058-62.
168. Adembri C, Ristori R, Chelazzi C, Arrigucci S, Cassetta MI, De Gaudio AR, Novelli A.
Cefazolin bolus and continuous administration for elective cardiac surgery: improved
pharmacokinetic and pharmacodynamic parameters. J Thorac Cardiovasc Surg 2010; 140:
471-5.
169. Roberts JA, Kirkpatrick CM, Roberts MS, Dalley AJ, Lipman J. First-dose and steady-state
population pharmacokinetics and pharmacodynamics of piperacillin by continuous or
intermittent dosing in critically ill patients with sepsis. Int J Antimicrob Agents 2010; 35:
156-63.
170. Shea KM, Cheatham SC, Smith DW, Wack MF, Sowinski KM, Kays MB. Comparative
pharmacodynamics of intermittent and prolonged infusions of piperacillin/tazobactam using
209
Monte Carlo simulations and steady-state pharmacokinetic data from hospitalized patients.
Ann Pharmacother 2009; 43: 1747-54.
171. Sakka SG, Glauner AK, Bulitta JB, Kinzig-Schippers M, Pfister W, Drusano GL, Sorgel F.
Population pharmacokinetics and pharmacodynamics of continuous versus short-term
infusion of imipenem-cilastatin in critically ill patients in a randomized, controlled trial.
Antimicrob Agents Chemother 2007; 51: 3304-10.
172. Georges B, Conil JM, Cougot P, Decun JF, Archambaud M, Seguin T, Chabanon G,
Virenque C, Houin G, Saivin S. Cefepime in critically ill patients: continuous infusion vs.
an intermittent dosing regimen. Int J Clin Pharmacol Ther 2005; 43: 360-9.
173. Buck C, Bertram N, Ackermann T, Sauerbruch T, Derendorf H, Paar WD. Pharmacokinetics
of piperacillin-tazobactam: intermittent dosing versus continuous infusion. Int J Antimicrob
Agents 2005; 25: 62-7.
174. Lipman J, Wallis SC, Rickard C. Low plasma cefepime levels in critically ill septic patients:
pharmacokinetic modeling indicates improved troughs with revised dosing. Antimicrob
Agents Chemother 1999; 43: 2559-61.
175. Young RJ, Lipman J, Gin T, Gomersall CD, Joynt GM, Oh TE. Intermittent bolus dosing of
ceftazidime in critically ill patients. J Antimicrob Chemother 1997; 40: 269-73.
176. Yahav D, Paul M, Fraser A, Sarid N, Leibovici L. Efficacy and safety of cefepime: a
systematic review and meta-analysis. The Lancet infectious diseases 2007; 7: 338-48.
177. Lamoth F, Buclin T, Pascual A, Vora S, Bolay S, Decosterd LA, Calandra T, Marchetti O.
High cefepime plasma concentrations and neurological toxicity in febrile neutropenic
patients with mild impairment of renal function. Antimicrob Agents Chemother 2010; 54:
4360-7.
178. Sonck J, Laureys G, Verbeelen D. The neurotoxicity and safety of treatment with cefepime
in patients with renal failure. Nephrol Dial Transplant 2008; 23: 966-70.
179. Chatellier D, Jourdain M, Mangalaboyi J, Ader F, Chopin C, Derambure P, Fourrier F.
Cefepime-induced neurotoxicity: an underestimated complication of antibiotherapy in
patients with acute renal failure. Intensive Care Med 2002; 28: 214-7.
180. Jallon P, Fankhauser L, Du Pasquier R, Coeytaux A, Picard F, Hefft S, Assal F. Severe but
reversible encephalopathy associated with cefepime. Neurophysiol Clin 2000; 30: 383-6.
181. Udy AA, Baptista JP, Lim NL, Joynt GM, Jarrett P, Wockner L, Boots RJ, Lipman J.
Augmented renal clearance in the ICU: results of a multicenter observational study of renal
function in critically ill patients with normal plasma creatinine concentrations*. Crit Care
Med 2014; 42: 520-7.
210
182. Couffignal C, Pajot O, Laouenan C, Burdet C, Foucrier A, Wolff M, Armand-Lefevre L,
Mentre F, Massias L. Population pharmacokinetics of imipenem in critically ill patients with
suspected ventilator-associated pneumonia and evaluation of dosage regimens. Br J Clin
Pharmacol 2014; 78: 1022-34.
183. Sime FB, Roberts MS, Warner MS, Hahn U, Robertson TA, Yeend S, Phay A, Lehman S,
Lipman J, Peake SL, Roberts JA. Altered pharmacokinetics of piperacillin in febrile
neutropenic patients with haematological malignancy. Antimicrob Agents Chemother 2014.
184. Carlier M, Noe M, De Waele JJ, Stove V, Verstraete AG, Lipman J, Roberts JA. Population
pharmacokinetics and dosing simulations of amoxicillin/clavulanic acid in critically ill
patients. J Antimicrob Chemother 2013; 68: 2600-8.
185. Harada M, Inui N, Suda T, Nakamura Y, Wajima T, Matsuo Y, Chida K. Pharmacokinetic
analysis of doripenem in elderly patients with nosocomial pneumonia. Int J Antimicrob
Agents 2013; 42: 149-54.
186. Bhalodi AA, Keel RA, Quintiliani R, Lodise TP, Nicolau DP, Kuti JL. Pharmacokinetics of
doripenem in infected patients treated within and outside the intensive care unit. Ann
Pharmacother 2013; 47: 617-27.
187. Roberts JA, Lipman J. Optimal doripenem dosing simulations in critically ill nosocomial
pneumonia patients with obesity, augmented renal clearance, and decreased bacterial
susceptibility. Crit Care Med 2013; 41: 489-95.
188. Jaruratanasirikul S, Wongpoowarak W, Kositpantawong N, Aeinlang N, Jullangkoon M.
Pharmacodynamics of doripenem in critically ill patients with ventilator-associated Gram-
negative bacilli pneumonia. Int J Antimicrob Agents 2012; 40: 434-9.
189. Karjagin J, Lefeuvre S, Oselin K, Kipper K, Marchand S, Tikkerberi A, Starkopf J, Couet
W, Sawchuk RJ. Pharmacokinetics of meropenem determined by microdialysis in the
peritoneal fluid of patients with severe peritonitis associated with septic shock. Clin
Pharmacol Ther 2008; 83: 452-9.
190. Jaruratanasirikul S, Sriwiriyajan S, Punyo J. Comparison of the pharmacodynamics of
meropenem in patients with ventilator-associated pneumonia following administration by 3-
hour infusion or bolus injection. Antimicrob Agents Chemother 2005; 49: 1337-9.
191. Kitzes-Cohen R, Farin D, Piva G, De Myttenaere-Bursztein SA. Pharmacokinetics and
pharmacodynamics of meropenem in critically ill patients. Int J Antimicrob Agents 2002;
19: 105-10.
192. de Stoppelaar F, Stolk L, van Tiel F, Beysens A, van der Geest S, de Leeuw P. Meropenem
pharmacokinetics and pharmacodynamics in patients with ventilator-associated pneumonia.
J Antimicrob Chemother 2000; 46: 150-1.
211
193. Thalhammer F, Traunmuller F, El Menyawi I, Frass M, Hollenstein UM, Locker GJ, Stoiser
B, Staudinger T, Thalhammer-Scherrer R, Burgmann H. Continuous infusion versus
intermittent administration of meropenem in critically ill patients. J Antimicrob Chemother
1999; 43: 523-7.
194. Lovering AM, Vickery CJ, Watkin DS, Leaper D, McMullin CM, White LO, Reeves DS,
MacGowan AP. The pharmacokinetics of meropenem in surgical patients with moderate or
severe infections. J Antimicrob Chemother 1995; 36: 165-72.
195. Ljungberg B, Nilsson-Ehle I. Pharmacokinetics of meropenem and its metabolite in young
and elderly healthy men. Antimicrob Agents Chemother 1992; 36: 1437-40.
196. Wong G, Brinkman A, Benefield RJ, Carlier M, De Waele JJ, El Helali N, Frey O, Harbarth
S, Huttner A, McWhinney B, Misset B, Pea F, Preisenberger J, Roberts MS, Robertson TA,
Roehr A, Sime FB, Taccone FS, Ungerer JP, Lipman J, Roberts JA. An international,
multicentre survey of beta-lactam antibiotic therapeutic drug monitoring practice in
intensive care units. J Antimicrob Chemother 2014; 69: 1416-23.
197. Roberts JA, Ulldemolins M, Roberts MS, McWhinney B, Ungerer J, Paterson DL, Lipman
J. Therapeutic drug monitoring of beta-lactams in critically ill patients: proof of concept. Int
J Antimicrob Agents 2010; 36: 332-9.
198. Chapuis TM, Giannoni E, Majcherczyk PA, Chiolero R, Schaller MD, Berger MM, Bolay S,
Decosterd LA, Bugnon D, Moreillon P. Prospective monitoring of cefepime in intensive
care unit adult patients. Crit Care 2010; 14: R51.
199. Aubert G, Carricajo A, Coudrot M, Guyomarc'h S, Auboyer C, Zeni F. Prospective
determination of serum ceftazidime concentrations in intensive care units. Ther Drug Monit
2010; 32: 517-9.
200. De Waele JJ, Dumoulin A, Janssen A, Hoste EA. Epidemiology of augmented renal
clearance in mixed ICU patients. Minerva Anestesiol 2015.
201. Garot D, Respaud R, Lanotte P, Simon N, Mercier E, Ehrmann S, Perrotin D, Dequin PF, Le
Guellec C. Population pharmacokinetics of ceftriaxone in critically ill septic patients: a
reappraisal. Br J Clin Pharmacol 2011; 72: 758-67.
202. Conil JM, Georges B, Fourcade O, Seguin T, Houin G, Saivin S. Intermittent administration
of ceftazidime to burns patients: influence of glomerular filtration. Int J Clin Pharmacol
Ther 2007; 45: 133-42.
203. Conil JM, Georges B, Lavit M, Seguin T, Tack I, Samii K, Chabanon G, Houin G, Saivin S.
Pharmacokinetics of ceftazidime and cefepime in burn patients: the importance of age and
creatinine clearance. Int J Clin Pharmacol Ther 2007; 45: 529-38.
212
204. Roos JF, Lipman J, Kirkpatrick CM. Population pharmacokinetics and pharmacodynamics
of cefpirome in critically ill patients against Gram-negative bacteria. Intensive Care Med
2007; 33: 781-8.
205. Roos JF, Bulitta J, Lipman J, Kirkpatrick CM. Pharmacokinetic-pharmacodynamic rationale
for cefepime dosing regimens in intensive care units. J Antimicrob Chemother 2006; 58:
987-93.
206. Tam VH, McKinnon PS, Akins RL, Drusano GL, Rybak MJ. Pharmacokinetics and
pharmacodynamics of cefepime in patients with various degrees of renal function.
Antimicrob Agents Chemother 2003; 47: 1853-61.
207. Sime FB, Udy AA, Roberts JA. Augmented renal clearance in critically ill patients:
etiology, definition and implications for beta-lactam dose optimization. Curr Opin
Pharmacol 2015; 24: 1-6.
208. Tegeder I, Schmidtko A, Brautigam L, Kirschbaum A, Geisslinger G, Lotsch J. Tissue
distribution of imipenem in critically ill patients. Clin Pharmacol Ther 2002; 71: 325-33.
209. Cousson J, Floch T, Guillard T, Vernet V, Raclot P, Wolak-Thierry A, Jolly D. Lung
concentrations of ceftazidime administered by continuous versus intermittent infusion in
patients with ventilator-associated pneumonia. Antimicrob Agents Chemother 2015; 59:
1905-9.
210. Huang H, Huang S, Zhu P, Xi X. Continuous versus intermittent infusion of cefepime in
neurosurgical patients with post-operative intracranial infections. Int J Antimicrob Agents
2014; 43: 68-72.
211. Boselli E, Breilh D, Rimmele T, Guillaume C, Xuereb F, Saux MC, Bouvet L, Chassard D,
Allaouchiche B. Alveolar concentrations of piperacillin/tazobactam administered in
continuous infusion to patients with ventilator-associated pneumonia. Crit Care Med 2008;
36: 1500-6.
212. Boselli E, Breilh D, Rimmele T, Poupelin JC, Saux MC, Chassard D, Allaouchiche B.
Plasma and lung concentrations of ceftazidime administered in continuous infusion to
critically ill patients with severe nosocomial pneumonia. Intensive Care Med 2004; 30: 989-
91.
213. Carlier M, Noe M, Roberts JA, Stove V, Verstraete AG, Lipman J, De Waele JJ. Population
pharmacokinetics and dosing simulations of cefuroxime in critically ill patients: non-
standard dosing approaches are required to achieve therapeutic exposures. J Antimicrob
Chemother 2014; 69: 2797-803.
213
214. Jaruratanasirikul S, Aeinlang N, Jullangkoon M, Wongpoowarak W. Pharmacodynamics of
imipenem in critically ill patients with ventilator-associated pneumonia. J Med Assoc Thai
2013; 96: 551-7.
215. Roberts JA, Abdul-Aziz MH, Davis JS, Dulhunty JM, Cotta MO, Myburgh J, Bellomo R,
Lipman J. Continuous versus Intermittent Beta-lactam Infusion in Severe Sepsis: A Meta-
analysis of Individual Patient Data From Randomized Trials. Am J Respir Crit Care Med
2016.
216. Abdul-Aziz MH, Sulaiman H, Mat-Nor MB, Rai V, Wong KK, Hasan MS, Abd Rahman
AN, Jamal JA, Wallis SC, Lipman J, Staatz CE, Roberts JA. Beta-Lactam Infusion in
Severe Sepsis (BLISS): a prospective, two-centre, open-labelled randomised controlled trial
of continuous versus intermittent beta-lactam infusion in critically ill patients with severe
sepsis. Intensive Care Med 2016.
217. Roberts JA, Webb S, Paterson D, Ho KM, Lipman J. A systematic review on clinical
benefits of continuous administration of beta-lactam antibiotics. Crit Care Med 2009; 37:
2071-8.
218. Gerber AU, Brugger HP, Feller C, Stritzko T, Stalder B. Antibiotic therapy of infections due
to Pseudomonas aeruginosa in normal and granulocytopenic mice: comparison of murine
and human pharmacokinetics. J Infect Dis 1986; 153: 90-7.
219. Alou L, Aguilar L, Sevillano D, Gimenez MJ, Echeverria O, Gomez-Lus ML, Prieto J. Is
there a pharmacodynamic need for the use of continuous versus intermittent infusion with
ceftazidime against Pseudomonas aeruginosa? An in vitro pharmacodynamic model. J
Antimicrob Chemother 2005; 55: 209-13.
220. Tessier PR, Nicolau DP, Onyeji CO, Nightingale CH. Pharmacodynamics of intermittent-
and continuous-infusion cefepime alone and in combination with once-daily tobramycin
against Pseudomonas aeruginosa in an in vitro infection model. Chemotherapy 1999; 45:
284-95.
221. Mouton JW, Vinks AA, Punt NC. Pharmacokinetic-pharmacodynamic modeling of activity
of ceftazidime during continuous and intermittent infusion. Antimicrob Agents Chemother
1997; 41: 733-8.
222. Garrison MW, Malone CL, Eiland JE. Activity of once-daily cefpodoxime regimens against
Haemophilus influenzae and Streptococcus pneumoniae with an in vitro pharmacodynamic
chamber model. Antimicrob Agents Chemother 1996; 40: 1545-7.
223. Cappelletty DM, Kang SL, Palmer SM, Rybak MJ. Pharmacodynamics of ceftazidime
administered as continuous infusion or intermittent bolus alone and in combination with
214
single daily-dose amikacin against Pseudomonas aeruginosa in an in vitro infection model.
Antimicrob Agents Chemother 1995; 39: 1797-801.
224. White CA, Toothaker RD. Influence of ampicillin elimination half-life on in-vitro
bactericidal effect. J Antimicrob Chemother 1985; 15 Suppl A: 257-60.
225. Gerber AU, Wiprachtiger P, Stettler-Spichiger U, Lebek G. Constant infusions vs.
intermittent doses of gentamicin against Pseudomonas aeruginosa in vitro. J Infect Dis 1982;
145: 554-60.
226. Tottrup M, Bibby BM, Hardlei TF, Bue M, Kerrn-Jespersen S, Fuursted K, Soballe K,
Birke-Sorensen H. Continuous versus short-term infusion of cefuroxime: assessment of
concept based on plasma, subcutaneous tissue, and bone pharmacokinetics in an animal
model. Antimicrob Agents Chemother 2015; 59: 67-75.
227. Robaux MA, Dube L, Caillon J, Bugnon D, Kergueris MF, Navas D, Le Conte P, Baron D,
Potel G. In vivo efficacy of continuous infusion versus intermittent dosing of ceftazidime
alone or in combination with amikacin relative to human kinetic profiles in a Pseudomonas
aeruginosa rabbit endocarditis model. J Antimicrob Chemother 2001; 47: 617-22.
228. Leggett JE, Fantin B, Ebert S, Totsuka K, Vogelman B, Calame W, Mattie H, Craig WA.
Comparative antibiotic dose-effect relations at several dosing intervals in murine
pneumonitis and thigh-infection models. J Infect Dis 1989; 159: 281-92.
229. Vogelman B, Gudmundsson S, Leggett J, Turnidge J, Ebert S, Craig WA. Correlation of
antimicrobial pharmacokinetic parameters with therapeutic efficacy in an animal model. J
Infect Dis 1988; 158: 831-47.
230. Thauvin C, Eliopoulos GM, Willey S, Wennersten C, Moellering RC, Jr. Continuous-
infusion ampicillin therapy of enterococcal endocarditis in rats. Antimicrob Agents
Chemother 1987; 31: 139-43.
231. Roosendaal R, Bakker-Woudenberg IA, van den Berghe-van Raffe M, Michel MF.
Continuous versus intermittent administration of ceftazidime in experimental Klebsiella
pneumoniae pneumonia in normal and leukopenic rats. Antimicrob Agents Chemother 1986;
30: 403-8.
232. Bergeron MG, Simard P. Influence of three modes of administration on the penetration of
latamoxef into interstitial fluid and fibrin clots and its in-vivo activity against Haemophilus
influenzae. J Antimicrob Chemother 1986; 17: 775-84.
233. Roosendaal R, Bakker-Woudenberg IA, van den Berg JC, Michel MF. Therapeutic efficacy
of continuous versus intermittent administration of ceftazidime in an experimental
Klebsiella pneumoniae pneumonia in rats. J Infect Dis 1985; 152: 373-8.
215
234. Lavoie GY, Bergeron MG. Influence of four modes of administration on penetration of
aztreonam, cefuroxime, and ampicillin into interstitial fluid and fibrin clots and on in vivo
efficacy against Haemophilus influenzae. Antimicrob Agents Chemother 1985; 28: 404-12.
235. Mordenti JJ, Quintiliani R, Nightingale CH. Combination antibiotic therapy: comparison of
constant infusion and intermittent bolus dosing in an experimental animal model. J
Antimicrob Chemother 1985; 15 Suppl A: 313-21.
236. Bakker-Woudenberg IA, van den Berg JC, Fontijne P, Michel MF. Efficacy of continuous
versus intermittent administration of penicillin G in Streptococcus pneumoniae pneumonia
in normal and immunodeficient rats. Eur J Clin Microbiol 1984; 3: 131-5.
237. Gengo FM, Mannion TW, Nightingale CH, Schentag JJ. Integration of pharmacokinetics
and pharmacodynamics of methicillin in curative treatment of experimental endocarditis. J
Antimicrob Chemother 1984; 14: 619-31.
238. Elkhaili H, Peter JD, Pompei D, Levless-Than-Or-Eq Slanteque D, Linger L, Salmon Y,
Salmon J, Monteil H. Pharmacokinetics in vivo and pharmacodynamics ex vivo/in vitro of
meropenem and cefpirome in the Yucatan micropig model: continuous infusion versus
intermittent injection. Clin Microbiol Infect 1998; 4: 18-26.
239. Teo J, Liew Y, Lee W, Kwa AL. Prolonged infusion versus intermittent boluses of beta-
lactam antibiotics for treatment of acute infections: a meta-analysis. Int J Antimicrob Agents
2014; 43: 403-11.
240. Shiu J, Wang E, Tejani AM, Wasdell M. Continuous versus intermittent infusions of
antibiotics for the treatment of severe acute infections. Cochrane Database Syst Rev 2013; 3:
CD008481.
241. Dulhunty JM, Roberts JA, Davis JS, Webb SA, Bellomo R, Gomersall C, Shirwadkar C,
Eastwood GM, Myburgh J, Paterson DL, Starr T, Paul SK, Lipman J, * BIIftACTG. A
Multicenter Randomized Trial of Continuous versus Intermittent beta-Lactam Infusion in
Severe Sepsis. Am J Respir Crit Care Med 2015; 192: 1298-305.
242. Chytra I, Stepan M, Benes J, Pelnar P, Zidkova A, Bergerova T, Pradl R, Kasal E. Clinical
and microbiological efficacy of continuous versus intermittent application of meropenem in
critically ill patients: a randomized open-label controlled trial. Crit Care 2012; 16: R113.
243. Roberts JA, Boots R, Rickard CM, Thomas P, Quinn J, Roberts DM, Richards B, Lipman J.
Is continuous infusion ceftriaxone better than once-a-day dosing in intensive care? A
randomized controlled pilot study. J Antimicrob Chemother 2007; 59: 285-91.
244. Jamal JA, Mat-Nor MB, Mohamad-Nor FS, Udy AA, Wallis SC, Lipman J, Roberts JA.
Pharmacokinetics of meropenem in critically ill patients receiving continuous venovenous
216
haemofiltration: a randomised controlled trial of continuous infusion versus intermittent
bolus administration. Int J Antimicrob Agents 2015; 45: 41-5.
245. Jamal JA, Roberts DM, Udy AA, Mat-Nor MB, Mohamad-Nor FS, Wallis SC, Lipman J,
Roberts JA. Pharmacokinetics of piperacillin in critically ill patients receiving continuous
venovenous haemofiltration: A randomised controlled trial of continuous infusion versus
intermittent bolus administration. Int J Antimicrob Agents 2015; 46: 39-44.
246. Tamer AH, Aglan AA, Elsakkar MF. Continuous versus intermittent intravenous
meropenem in severe sepsis. International Journal of Pharmacy and Biological Sciences
2015; 5: 44-57.
247. De Jongh R, Hens R, Basma V, Mouton JW, Tulkens PM, Carryn S. Continuous versus
intermittent infusion of temocillin, a directed spectrum penicillin for intensive care patients
with nosocomial pneumonia: stability, compatibility, population pharmacokinetic studies
and breakpoint selection. J Antimicrob Chemother 2008; 61: 382-8.
248. Rafati MR, Rouini MR, Mojtahedzadeh M, Najafi A, Tavakoli H, Gholami K, Fazeli MR.
Clinical efficacy of continuous infusion of piperacillin compared with intermittent dosing in
septic critically ill patients. Int J Antimicrob Agents 2006; 28: 122-7.
249. Cousson J, Floch T, Vernet-Garnier V, Appriou M, Petit JS, Jovenin N, Lamiable D, Hoizey
G. [Pharmacodynamic interest of ceftazidime continuous infusion vs intermittent bolus
administration in patients with severe nosocomial pneumonia]. Pathol Biol (Paris) 2005; 53:
546-50.
250. Lipman J, Gomersall CD, Gin T, Joynt GM, Young RJ. Continuous infusion ceftazidime in
intensive care: a randomized controlled trial. J Antimicrob Chemother 1999; 43: 309-11.
251. Nicolau D, McNabb J, Lacy M, Li J, Quintiliani R, Nightingale C. Pharmacokinetics and
pharmacodynamics of continuous and intermittent ceftazidime during the treatment of
nosocomial pneumonia. Clin Drug Investig 1999; 18: 133-39.
252. Nicolau DP, Lacy MK, McNabb J, Quintiliani R, Nightingale CH. Pharmacokinetics of
continuous and intermittent ceftazidime in intensive care unit patients with nosocomial
pneumonia. Infectious Diseases in Clinical Practice 1999; 8: 45-49.
253. Langgartner J, Vasold A, Gluck T, Reng M, Kees F. Pharmacokinetics of meropenem
during intermittent and continuous intravenous application in patients treated by continuous
renal replacement therapy. Intensive Care Med 2008; 34: 1091-6.
254. Hanes SD, Wood GC, Herring V, Croce MA, Fabian TC, Pritchard E, Boucher BA.
Intermittent and continuous ceftazidime infusion for critically ill trauma patients. Am J Surg
2000; 179: 436-40.
217
255. Bodey GP, Ketchel SJ, Rodriguez V. A randomized study of carbenicillin plus cefamandole
or tobramycin in the treatment of febrile episodes in cancer patients. Am J Med 1979; 67:
608-16.
256. Lau WK, Mercer D, Itani KM, Nicolau DP, Kuti JL, Mansfield D, Dana A. Randomized,
open-label, comparative study of piperacillin-tazobactam administered by continuous
infusion versus intermittent infusion for treatment of hospitalized patients with complicated
intra-abdominal infection. Antimicrob Agents Chemother 2006; 50: 3556-61.
257. van Zanten AR, Oudijk M, Nohlmans-Paulssen MK, van der Meer YG, Girbes AR,
Polderman KH. Continuous vs. intermittent cefotaxime administration in patients with
chronic obstructive pulmonary disease and respiratory tract infections:
pharmacokinetics/pharmacodynamics, bacterial susceptibility and clinical efficacy. Br J Clin
Pharmacol 2007; 63: 100-9.
258. Lubasch A, Luck S, Lode H, Mauch H, Lorenz J, Bolcskei P, Welte T, Group CS.
Optimizing ceftazidime pharmacodynamics in patients with acute exacerbation of severe
chronic bronchitis. J Antimicrob Chemother 2003; 51: 659-64.
259. Laterre PF, Wittebole X, Van de Velde S, Muller AE, Mouton JW, Carryn S, Tulkens PM,
Dugernier T. Temocillin (6 g daily) in critically ill patients: continuous infusion versus three
times daily administration. J Antimicrob Chemother 2015; 70: 891-8.
260. Okimoto N, Ishiga M, Nanba F, Kibayashi T, Kishimoto M, Kurihara T, Honda Y, Asaoka
N, Tamada S. [Clinical effects of continuous infusion and intermittent infusion of
meropenem on bacterial pneumonia in the elderly]. Nihon Kokyuki Gakkai Zasshi 2009; 47:
553-7.
261. Pedeboscq S, Dubau B, Frappier S, Hernandez V, Veyssieres D, Winnock S, Pometan JP.
[Comparison of 2 administration protocols (continuous or discontinuous) of a time-
dependent antibiotic, Tazocin]. Pathol Biol (Paris) 2001; 49: 540-7.
262. Lagast H, Meunier-Carpentier F, Klastersky J. Treatment of gram-negative bacillary
septicemia with cefoperazone. Eur J Clin Microbiol 1983; 2: 554-8.
263. Smuszkiewicz P, Szalek E, Tomczak H, Grzeskowiak E. Continuous infusion of antibiotics
in critically ill patients. Curr Clin Pharmacol 2013; 8: 13-24.
264. Roberts JA, Paratz J, Paratz E, Krueger WA, Lipman J. Continuous infusion of beta-lactam
antibiotics in severe infections: a review of its role. Int J Antimicrob Agents 2007; 30: 11-8.
265. Mouton JW, Vinks AA. Is continuous infusion of beta-lactam antibiotics worthwhile?--
efficacy and pharmacokinetic considerations. J Antimicrob Chemother 1996; 38: 5-15.
218
266. Nicolau DP, McNabb J, Lacy MK, Quintiliani R, Nightingale CH. Continuous versus
intermittent administration of ceftazidime in intensive care unit patients with nosocomial
pneumonia. Int J Antimicrob Agents 2001; 17: 497-504.
267. Kasiakou SK, Sermaides GJ, Michalopoulos A, Soteriades ES, Falagas ME. Continuous
versus intermittent intravenous administration of antibiotics: a meta-analysis of randomised
controlled trials. Lancet Infect Dis 2005; 5: 581-9.
268. Yang H, Zhang C, Zhou Q, Wang Y, Chen L. Clinical outcomes with alternative dosing
strategies for piperacillin/tazobactam: a systematic review and meta-analysis. PLoS One
2015; 10: e0116769.
269. Chant C, Leung A, Friedrich JO. Optimal dosing of antibiotics in critically ill patients using
continuous/extended infusions: a systematic review and meta-analysis. Crit Care 2013; 17:
R279.
270. Falagas ME, Tansarli GS, Ikawa K, Vardakas KZ. Clinical outcomes with extended or
continuous versus short-term intravenous infusion of carbapenems and
piperacillin/tazobactam: a systematic review and meta-analysis. Clin Infect Dis 2013; 56:
272-82.
271. Korbila IP, Tansarli GS, Karageorgopoulos DE, Vardakas KZ, Falagas ME. Extended or
continuous versus short-term intravenous infusion of cephalosporins: a meta-analysis.
Expert Rev Anti Infect Ther 2013; 11: 585-95.
272. Manning L, Wright C, Ingram PR, Whitmore TJ, Heath CH, Manson I, Page-Sharp M,
Salman S, Dyer J, Davis TM. Continuous infusions of meropenem in ambulatory care:
clinical efficacy, safety and stability. PLoS One 2014; 9: e102023.
273. Gonçalves-Pereira J, Oliveira BS, Janeiro S, Estilita J, Monteiro C, Salgueiro A, Vieira A,
Gouveia J, Paulino C, Bento L, Póvoa P. Continuous Infusion of Piperacillin/Tazobactam in
Septic Critically Ill Patients—A Multicenter Propensity Matched Analysis. PLoS One 2012;
7.
274. Lorente L, Jimenez A, Martin MM, Iribarren JL, Jimenez JJ, Mora ML. Clinical cure of
ventilator-associated pneumonia treated with piperacillin/tazobactam administered by
continuous or intermittent infusion. Int J Antimicrob Agents 2009; 33: 464-8.
275. Lorente L, Jimenez A, Palmero S, Jimenez JJ, Iribarren JL, Santana M, Martin MM, Mora
ML. Comparison of clinical cure rates in adults with ventilator-associated pneumonia treated
with intravenous ceftazidime administered by continuous or intermittent infusion: a
retrospective, nonrandomized, open-label, historical chart review. Clin Ther 2007; 29: 2433-
9.
219
276. Lorente L, Lorenzo L, Martin MM, Jimenez A, Mora ML. Meropenem by continuous versus
intermittent infusion in ventilator-associated pneumonia due to gram-negative bacilli. Ann
Pharmacother 2006; 40: 219-23.
277. Roberts JA, Lipman J, Blot S, Rello J. Better outcomes through continuous infusion of time-
dependent antibiotics to critically ill patients? Curr Opin Crit Care 2008; 14: 390-6.
278. Keel RA, Sutherland CA, Crandon JL, Nicolau DP. Stability of doripenem, imipenem and
meropenem at elevated room temperatures. Int J Antimicrob Agents 2011; 37: 184-5.
279. Berthoin K, Le Duff CS, Marchand-Brynaert J, Carryn S, Tulkens PM. Stability of
meropenem and doripenem solutions for administration by continuous infusion. J
Antimicrob Chemother 2010; 65: 1073-5.
280. Crandon JL, Sutherland C, Nicolau DP. Stability of doripenem in polyvinyl chloride bags
and elastomeric pumps. Am J Health Syst Pharm 2010; 67: 1539-44.
281. Psathas PA, Kuzmission A, Ikeda K, Yasuo S. Stability of doripenem in vitro in
representative infusion solutions and infusion bags. Clin Ther 2008; 30: 2075-87.
282. Baririan N, Chanteux H, Viaene E, Servais H, Tulkens PM. Stability and compatibility
study of cefepime in comparison with ceftazidime for potential administration by continuous
infusion under conditions pertinent to ambulatory treatment of cystic fibrosis patients and to
administration in intensive care units. J Antimicrob Chemother 2003; 51: 651-8.
283. Jaruratanasirikul S, Sriwiriyajan S. Stability of meropenem in normal saline solution after
storage at room temperature. Southeast Asian J Trop Med Public Health 2003; 34: 627-9.
284. Viaene E, Chanteux H, Servais H, Mingeot-Leclercq MP, Tulkens PM. Comparative
stability studies of antipseudomonal beta-lactams for potential administration through
portable elastomeric pumps (home therapy for cystic fibrosis patients) and motor-operated
syringes (intensive care units). Antimicrob Agents Chemother 2002; 46: 2327-32.
285. Jaruratanasirikul S, Sriwiriyajan S. Stability of ceftazidime in normal saline solution after
exposure to light. Southeast Asian J Trop Med Public Health 2001; 32: 216-8.
286. Frippiat F, Musuamba FT, Seidel L, Albert A, Denooz R, Charlier C, Van Bambeke F,
Wallemacq P, Descy J, Lambermont B, Layios N, Damas P, Moutschen M. Modelled target
attainment after meropenem infusion in patients with severe nosocomial pneumonia: the
PROMESSE study. J Antimicrob Chemother 2015; 70: 207-16.
287. Macvane SH, Kuti JL, Nicolau DP. Prolonging beta-lactam infusion: A review of the
rationale and evidence, and guidance for implementation. Int J Antimicrob Agents 2013.
288. George JM, Towne TG, Rodvold KA. Prolonged infusions of beta-lactam antibiotics:
implication for antimicrobial stewardship. Pharmacotherapy 2012; 32: 707-21.
220
289. Feher C, Rovira M, Soriano A, Esteve J, Martinez JA, Marco F, Carreras E, Martinez C,
Fernandez-Aviles F, Suarez-Lledo M, Mensa J. Effect of meropenem administration in
extended infusion on the clinical outcome of febrile neutropenia: a retrospective
observational study. J Antimicrob Chemother 2014; 69: 2556-62.
290. Hsaiky L, Murray KP, Kokoska L, Desai N, Cha R. Standard versus prolonged doripenem
infusion for treatment of gram-negative infections. Ann Pharmacother 2013; 47: 999-1006.
291. Abdul-Aziz MH, Lipman J, Akova M, Bassetti M, De Waele JJ, Dimopoulos G, Dulhunty J,
Kaukonen KM, Koulenti D, Martin C, Montravers P, Rello J, Rhodes A, Starr T, Wallis SC,
Roberts JA, Group DS. Is prolonged infusion of piperacillin/tazobactam and meropenem in
critically ill patients associated with improved pharmacokinetic/pharmacodynamic and
patient outcomes? An observation from the Defining Antibiotic Levels in Intensive care unit
patients (DALI) cohort. J Antimicrob Chemother 2016; 71: 196-207.
292. Arnold HM, Hollands JM, Skrupky LP, Smith JR, Juang PH, Hampton NB, McCormick S,
Reichley RM, Hoban A, Hoffmann J, Micek ST, Kollef MH. Prolonged infusion antibiotics
for suspected gram-negative infections in the ICU: a before-after study. Ann Pharmacother
2013; 47: 170-80.
293. Bauer KA, West JE, O'Brien JM, Goff DA. Extended-infusion cefepime reduces mortality
in patients with Pseudomonas aeruginosa infections. Antimicrob Agents Chemother 2013;
57: 2907-12.
294. Lee GC, Liou H, Yee R, Quan CF, Neldner K. Outcomes of extended-infusion piperacillin-
tazobactam: a retrospective analysis of critically ill patients. Clin Ther 2012; 34: 2297-300.
295. Yost RJ, Cappelletty DM, group RS. The Retrospective Cohort of Extended-Infusion
Piperacillin-Tazobactam (RECEIPT) study: a multicenter study. Pharmacotherapy 2011; 31:
767-75.
296. Patel GW, Patel N, Lat A, Trombley K, Enbawe S, Manor K, Smith R, Lodise TP, Jr.
Outcomes of extended infusion piperacillin/tazobactam for documented Gram-negative
infections. Diagn Microbiol Infect Dis 2009; 64: 236-40.
297. Wang D. Experience with extended-infusion meropenem in the management of ventilator-
associated pneumonia due to multidrug-resistant Acinetobacter baumannii. Int J Antimicrob
Agents 2009; 33: 290-1.
298. Lodise TP, Jr., Lomaestro B, Drusano GL. Piperacillin-tazobactam for Pseudomonas
aeruginosa infection: clinical implications of an extended-infusion dosing strategy. Clin
Infect Dis 2007; 44: 357-63.
221
299. Fritsche TR, Sader HS, Stillwell MG, Jones RN. Antimicrobial activity of doripenem tested
against prevalent Gram-positive pathogens: results from a global surveillance study (2003-
2007). Diagn Microbiol Infect Dis 2009; 63: 440-6.
300. Fritsche TR, Stilwell MG, Jones RN. Antimicrobial activity of doripenem (S-4661): a global
surveillance report (2003). Clin Microbiol Infect 2005; 11: 974-84.
301. Lucasti C, Jasovich A, Umeh O, Jiang J, Kaniga K, Friedland I. Efficacy and tolerability of
IV doripenem versus meropenem in adults with complicated intra-abdominal infection: a
phase III, prospective, multicenter, randomized, double-blind, noninferiority study. Clin
Ther 2008; 30: 868-83.
302. Redman R, Damiao R, Kotey P, Kaniga K, Davies T, Naber KG. Safety and efficacy of
intravenous doripenem for the treatment of complicated urinary tract infections and
pyelonephritis. J Chemother 2010; 22: 384-91.
303. Wagenlehner FM, Wagenlehner C, Redman R, Weidner W, Naber KG. Urinary bactericidal
activity of Doripenem versus that of levofloxacin in patients with complicated urinary tract
infections or pyelonephritis. Antimicrob Agents Chemother 2009; 53: 1567-73.
304. Naber KG, Llorens L, Kaniga K, Kotey P, Hedrich D, Redman R. Intravenous doripenem at
500 milligrams versus levofloxacin at 250 milligrams, with an option to switch to oral
therapy, for treatment of complicated lower urinary tract infection and pyelonephritis.
Antimicrob Agents Chemother 2009; 53: 3782-92.
305. Chastre J, Wunderink R, Prokocimer P, Lee M, Kaniga K, Friedland I. Efficacy and safety
of intravenous infusion of doripenem versus imipenem in ventilator-associated pneumonia: a
multicenter, randomized study. Crit Care Med 2008; 36: 1089-96.
306. Rea-Neto A, Niederman M, Lobo SM, Schroeder E, Lee M, Kaniga K, Ketter N,
Prokocimer P, Friedland I. Efficacy and safety of doripenem versus piperacillin/tazobactam
in nosocomial pneumonia: a randomized, open-label, multicenter study. Curr Med Res Opin
2008; 24: 2113-26.
307. Qu XY, Hu TT, Zhou W. A meta-analysis of efficacy and safety of doripenem for treating
bacterial infections. Braz J Infect Dis 2015; 19: 156-62.
308. Kollef MH, Nathwani D, Merchant S, Gast C, Quintana A, Ketter N. Medical resource
utilization among patients with ventilator-associated pneumonia: pooled analysis of
randomized studies of doripenem versus comparators. Crit Care 2010; 14: R84.
309. McGarry LJ, Merchant S, Nathwani D, Pawar V, DeLong K, Thompson D, Akhras K,
Ingham M, Weinstein MC. Economic assessment of doripenem versus imipenem in the
treatment of ventilator-associated pneumonia. J Med Econ 2010; 13: 142-7.
222
310. Kongnakorn T, Mwamburi M, Merchant S, Akhras K, Caro JJ, Nathwani D. Economic
evaluation of doripenem for the treatment of nosocomial pneumonia in the US: discrete
event simulation. Curr Med Res Opin 2010; 26: 17-24.
311. Jenkins SG, Fisher AC, Peterson JA, Nicholson SC, Kaniga K. Meta-analysis of doripenem
vs comparators in patients with pseudomonas infections enrolled in four phase III efficacy
and safety clinical trials. Curr Med Res Opin 2009; 25: 3029-36.
312. Merchant S, Gast C, Nathwani D, Lee M, Quintana A, Ketter N, Friedland I, Ingham M.
Hospital resource utilization with doripenem versus imipenem in the treatment of ventilator-
associated pneumonia. Clin Ther 2008; 30: 717-33.
313. Nandy P, Samtani MN, Lin R. Population pharmacokinetics of doripenem based on data
from phase 1 studies with healthy volunteers and phase 2 and 3 studies with critically ill
patients. Antimicrob Agents Chemother 2010; 54: 2354-9.
314. Samtani MN, Flamm R, Kaniga K, Nandy P. Pharmacokinetic-pharmacodynamic-model-
guided doripenem dosing in critically ill patients. Antimicrob Agents Chemother 2010; 54:
2360-4.
315. Van Wart SA, Andes DR, Ambrose PG, Bhavnani SM. Pharmacokinetic-pharmacodynamic
modeling to support doripenem dose regimen optimization for critically ill patients. Diagn
Microbiol Infect Dis 2009; 63: 409-14.
316. Bhavnani SM, Hammel JP, Cirincione BB, Wikler MA, Ambrose PG. Use of
pharmacokinetic-pharmacodynamic target attainment analyses to support phase 2 and 3
dosing strategies for doripenem. Antimicrob Agents Chemother 2005; 49: 3944-7.
317. Crandon JL, Bulik CC, Nicolau DP. In vivo efficacy of 1- and 2-gram human simulated
prolonged infusions of doripenem against Pseudomonas aeruginosa. Antimicrob Agents
Chemother 2009; 53: 4352-6.
318. Kim A, Banevicius MA, Nicolau DP. In vivo pharmacodynamic profiling of doripenem
against Pseudomonas aeruginosa by simulating human exposures. Antimicrob Agents
Chemother 2008; 52: 2497-502.
319. Jones RN, Huynh HK, Biedenbach DJ, Fritsche TR, Sader HS. Doripenem (S-4661), a novel
carbapenem: comparative activity against contemporary pathogens including bactericidal
action and preliminary in vitro methods evaluations. J Antimicrob Chemother 2004; 54:
144-54.
320. Matsuo Y, Ishibashi T, Kubota R, Wajima T. Population pharmacokinetics of doripenem in
Japanese subjects and Monte-Carlo simulation for patients with renal impairment. J Infect
Chemother 2015; 21: 123-9.
223
321. Kays MB, Fleming MR, Cheatham SC, Chung EK, Juenke JM. Comparative
pharmacokinetics and pharmacodynamics of doripenem and meropenem in obese patients.
Ann Pharmacother 2014; 48: 178-86.
322. Stein GE, Kulhanek G, Smith CL, Kuti JL, Nicolau DP, Scharmen A, Farnum C, Tran M,
Kalra A, Havlichek DH. Pharmacokinetics and monte carlo simulations of doripenem in
patients with febrile neutropenia. Ann Pharmacother 2012; 46: 1281-6.
323. Cirillo I, Vaccaro N, Redman R, Black PL, Kearns GL. Pharmacokinetics of single-dose
doripenem in adults with cystic fibrosis. J Clin Pharmacol 2012; 52: 1645-53.
324. Katsube T, Yano Y, Wajima T, Yamano Y, Takano M. Pharmacokinetic/pharmacodynamic
modeling and simulation to determine effective dosage regimens for doripenem. J Pharm Sci
2010; 99: 2483-91.
325. Ikawa K, Morikawa N, Ikeda K, Ohge H, Sueda T. Pharmacodynamic assessment of
doripenem in peritoneal fluid against Gram-negative organisms: use of population
pharmacokinetic modeling and Monte Carlo simulation. Diagn Microbiol Infect Dis 2008;
62: 292-7.
326. Watanabe A, Fujimura S, Kikuchi T, Gomi K, Fuse K, Nukiwa T. Evaluation of dosing
designs of carbapenems for severe respiratory infection using Monte Carlo simulation. J
Infect Chemother 2007; 13: 332-40.
327. Ikawa K, Morikawa N, Uehara S, Monden K, Yamada Y, Honda N, Kumon H.
Pharmacokinetic-pharmacodynamic target attainment analysis of doripenem in infected
patients. Int J Antimicrob Agents 2009; 33: 276-9.
328. Cirillo I, Vaccaro N, Turner K, Solanki B, Natarajan J, Redman R. Pharmacokinetics,
safety, and tolerability of doripenem after 0.5-, 1-, and 4-hour infusions in healthy
volunteers. J Clin Pharmacol 2009; 49: 798-806.
329. Cirillo I, Mannens G, Janssen C, Vermeir M, Cuyckens F, Desai-Krieger D, Vaccaro N, Kao
LM, Devineni D, Redman R, Turner K. Disposition, metabolism, and excretion of
[14C]doripenem after a single 500-milligram intravenous infusion in healthy men.
Antimicrob Agents Chemother 2008; 52: 3478-83.
330. Roberts JA, Lipman J. Antibacterial dosing in intensive care: pharmacokinetics, degree of
disease and pharmacodynamics of sepsis. Clin Pharmacokinet 2006; 45: 755-73.
331. Kiratisin P, Keel RA, Nicolau DP. Pharmacodynamic profiling of doripenem, imipenem and
meropenem against prevalent Gram-negative organisms in the Asia-Pacific region. Int J
Antimicrob Agents 2013; 41: 47-51.
332. Kiratisin P, Chongthaleong A, Tan TY, Lagamayo E, Roberts S, Garcia J, Davies T.
Comparative in vitro activity of carbapenems against major Gram-negative pathogens:
224
results of Asia-Pacific surveillance from the COMPACT II study. Int J Antimicrob Agents
2012; 39: 311-6.
333. Christiansen KJ, Ip M, Ker HB, Mendoza M, Hsu L, Kiratisin P, Chongthaleong A, Redjeki
IS, Quintana A, Flamm R, Garcia J, Cassettari M, Cooper D, Okolo P, Morrissey I. In vitro
activity of doripenem and other carbapenems against contemporary Gram-negative
pathogens isolated from hospitalised patients in the Asia-Pacific region: results of the
COMPACT Asia-Pacific Study. Int J Antimicrob Agents 2010; 36: 501-6.
334. Zhanel GG, DeCorby M, Laing N, Weshnoweski B, Vashisht R, Tailor F, Nichol KA,
Wierzbowski A, Baudry PJ, Karlowsky JA, Lagace-Wiens P, Walkty A, McCracken M,
Mulvey MR, Johnson J, Canadian Antimicrobial Resistance A, Hoban DJ. Antimicrobial-
resistant pathogens in intensive care units in Canada: results of the Canadian National
Intensive Care Unit (CAN-ICU) study, 2005-2006. Antimicrob Agents Chemother 2008; 52:
1430-7.
335. Rhomberg PR, Fritsche TR, Sader HS, Jones RN. Antimicrobial susceptibility pattern
comparisons among intensive care unit and general ward Gram-negative isolates from the
Meropenem Yearly Susceptibility Test Information Collection Program (USA). Diagn
Microbiol Infect Dis 2006; 56: 57-62.
336. Kollef MH, Chastre J, Clavel M, Restrepo MI, Michiels B, Kaniga K, Cirillo I, Kimko H,
Redman R. A randomized trial of 7-day doripenem versus 10-day imipenem-cilastatin for
ventilator-associated pneumonia. Crit Care 2012; 16: R218.
337. Ambrose PG, Bhavnani SM, Ellis-Grosse EJ, Drusano GL. Pharmacokinetic-
pharmacodynamic considerations in the design of hospital-acquired or ventilator-associated
bacterial pneumonia studies: look before you leap! Clin Infect Dis 2010; 51 Suppl 1: S103-
10.
338. Paterson DL, Depestel DD. Doripenem. Clin Infect Dis 2009; 49: 291-8.
339. Tsai D, Jamal JA, Davis JS, Lipman J, Roberts JA. Interethnic differences in
pharmacokinetics of antibacterials. Clin Pharmacokinet 2015; 54: 243-60.
340. Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease
classification system. Crit Care Med 1985; 13: 818-29.
341. Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine.
Nephron 1976; 16: 31-41.
342. Food and Drug Administration. Guidance for industry: bioanalytical method validation. In,
Rockville, MD, 2001.
343. Ortho-McNeil-Janssen Pharmaceutical Inc. Doribax (doripenem for injection). Prescribing
information. In, Raritan, NJ, 2008.
225
344. Lindbom L, Ribbing J, Jonsson EN. Perl-speaks-NONMEM (PsN)--a Perl module for
NONMEM related programming. Comput Methods Programs Biomed 2004; 75: 85-94.
345. Lindbom L, Pihlgren P, Jonsson EN. PsN-Toolkit--a collection of computer intensive
statistical methods for non-linear mixed effect modeling using NONMEM. Comput
Methods Programs Biomed 2005; 79: 241-57.
346. Keizer RJ, van Benten M, Beijnen JH, Schellens JH, Huitema AD. Pirana and PCluster: a
modeling environment and cluster infrastructure for NONMEM. Comput Methods Programs
Biomed 2011; 101: 72-9.
347. R Core Team. A Language and Environment for Statistical Computing. In, Vienna, Austria,
2014.
348. Anderson BJ, Holford NH. Mechanism-based concepts of size and maturity in
pharmacokinetics. Annu Rev Pharmacol Toxicol 2008; 48: 303-32.
349. Freire AT, Melnyk V, Kim MJ, Datsenko O, Dzyublik O, Glumcher F, Chuang YC, Maroko
RT, Dukart G, Cooper CA, Korth-Bradley JM, Dartois N, Gandjini H, Study G. Comparison
of tigecycline with imipenem/cilastatin for the treatment of hospital-acquired pneumonia.
Diagn Microbiol Infect Dis 2010; 68: 140-51.
350. Burdet C, Pajot O, Couffignal C, Armand-Lefevre L, Foucrier A, Laouenan C, Wolff M,
Massias L, Mentre F. Population pharmacokinetics of single-dose amikacin in critically ill
patients with suspected ventilator-associated pneumonia. Eur J Clin Pharmacol 2015; 71:
75-83.
351. Marik PE. Aminoglycoside volume of distribution and illness severity in critically ill septic
patients. Anaesth Intensive Care 1993; 21: 172-3.
352. Baptista JP, Udy AA, Sousa E, Pimentel J, Wang L, Roberts JA, Lipman J. A comparison of
estimates of glomerular filtration in critically ill patients with augmented renal clearance.
Crit Care 2011; 15: R139.
353. Fuster-Lluch O, Geronimo-Pardo M, Peyro-Garcia R, Lizan-Garcia M. Glomerular
hyperfiltration and albuminuria in critically ill patients. Anaesth Intensive Care 2008; 36:
674-80.
354. Adnan S, Ratnam S, Kumar S, Paterson D, Lipman J, Roberts J, Udy AA. Select critically ill
patients at risk of augmented renal clearance: experience in a Malaysian intensive care unit.
Anaesth Intensive Care 2014; 42: 715-22.
355. Roberts JA, Kwa A, Montakantikul P, Gomersall C, Kuti JL, Nicolau DP.
Pharmacodynamic profiling of intravenous antibiotics against prevalent Gram-negative
organisms across the globe: the PASSPORT Program-Asia-Pacific Region. Int J Antimicrob
Agents 2011; 37: 225-9.
226
356. Koomanachai P, Bulik CC, Kuti JL, Nicolau DP. Pharmacodynamic modeling of
intravenous antibiotics against gram-negative bacteria collected in the United States. Clin
Ther 2010; 32: 766-79.
357. Dellinger RP, Levy MM, Carlet JM, Bion J, Parker MM, Jaeschke R, Reinhart K, Angus
DC, Brun-Buisson C, Beale R, Calandra T, Dhainaut JF, Gerlach H, Harvey M, Marini JJ,
Marshall J, Ranieri M, Ramsay G, Sevransky J, Thompson BT, Townsend S, Vender JS,
Zimmerman JL, Vincent JL. Surviving Sepsis Campaign: international guidelines for
management of severe sepsis and septic shock: 2008. Intensive Care Med 2008; 34: 17-60.
358. Turnidge JD. The pharmacodynamics of beta-lactams. Clin Infect Dis 1998; 27: 10-22.
359. European Committee on Antimicrobial Susceptibility Testing. Breakpoint tables for
interpretation of MICs and zone diameters. In, 2016.
360. Clinical and Laboratory Standards Institute. Performance Standards for Antimicrobial
Susceptibility Testing: Twenty-fifth Informational Supplement. In, 2015.
361. Andes D, Craig WA. Treatment of infections with ESBL-producing organisms:
pharmacokinetic and pharmacodynamic considerations. Clin Microbiol Infect 2005; 11
Suppl 6: 10-7.
362. Li C, Kuti JL, Nightingale CH, Mansfield DL, Dana A, Nicolau DP. Population
pharmacokinetics and pharmacodynamics of piperacillin/tazobactam in patients with
complicated intra-abdominal infection. J Antimicrob Chemother 2005; 56: 388-95.
363. Benko AS, Cappelletty DM, Kruse JA, Rybak MJ. Continuous infusion versus intermittent
administration of ceftazidime in critically ill patients with suspected gram-negative
infections. Antimicrob Agents Chemother 1996; 40: 691-5.
364. Riethmueller J, Junge S, Schroeter TW, Kuemmerer K, Franke P, Ballmann M, Claass A,
Broemme S, Jeschke R, Hebestreit A, Staab D, Koetz K, Doering G, Stern M. Continuous
vs thrice-daily ceftazidime for elective intravenous antipseudomonal therapy in cystic
fibrosis. Infection 2009; 37: 418-23.
365. Hubert D, Le Roux E, Lavrut T, Wallaert B, Scheid P, Manach D, Grenet D, Sermet-
Gaudelus I, Ramel S, Cracowski C, Sardet A, Wizla N, Deneuville E, Garraffo R.
Continuous versus intermittent infusions of ceftazidime for treating exacerbation of cystic
fibrosis. Antimicrob Agents Chemother 2009; 53: 3650-6.
366. Rappaz I, Decosterd LA, Bille J, Pilet M, Belaz N, Roulet M. Continuous infusion of
ceftazidime with a portable pump is as effective as thrice-a-day bolus in cystic fibrosis
children. Eur J Pediatr 2000; 159: 919-25.
227
367. Langgartner J, Lehn N, Gluck T, Herzig H, Kees F. Comparison of the pharmacokinetics of
piperacillin and sulbactam during intermittent and continuous intravenous infusion.
Chemotherapy 2007; 53: 370-7.
368. Suffoletta TJ, Jennings HR, Oh JJ, Stephens D, Poe KL. Continuous versus intermittent
infusion of prophylactic cefoxitin after colorectal surgery: a pilot study. Pharmacotherapy
2008; 28: 1133-9.
369. Kuti JL, Nightingale CH, Knauft RF, Nicolau DP. Pharmacokinetic properties and stability
of continuous-infusion meropenem in adults with cystic fibrosis. Clin Ther 2004; 26: 493-
501.
370. Permin H, Koch C, Hoiby N, Christensen HO, Moller AF, Moller S. Ceftazidime treatment
of chronic Pseudomonas aeruginosa respiratory tract infection in cystic fibrosis. J
Antimicrob Chemother 1983; 12 Suppl A: 313-23.
371. Vinks AA, Brimicombe RW, Heijerman HG, Bakker W. Continuous infusion of ceftazidime
in cystic fibrosis patients during home treatment: clinical outcome, microbiology and
pharmacokinetics. J Antimicrob Chemother 1997; 40: 125-33.
372. Dalle JH, Gnansounou M, Husson MO, Lambilliotte A, Mazingue F, Nelken B. Continuous
infusion of ceftazidime in the empiric treatment of febrile neutropenic children with cancer.
J Pediatr Hematol Oncol 2002; 24: 714-6.
373. Egerer G, Goldschmidt H, Hensel M, Harter C, Schneeweiss A, Ehrhard I, Bastert G, Ho
AD. Continuous infusion of ceftazidime for patients with breast cancer and multiple
myeloma receiving high-dose chemotherapy and peripheral blood stem cell transplantation.
Bone Marrow Transplant 2002; 30: 427-31.
374. Hughes DW, Frei CR, Maxwell PR, Green K, Patterson JE, Crawford GE, Lewis JS, 2nd.
Continuous versus intermittent infusion of oxacillin for treatment of infective endocarditis
caused by methicillin-susceptible Staphylococcus aureus. Antimicrob Agents Chemother
2009; 53: 2014-9.
375. McNabb JJ, Nightingale CH, Quintiliani R, Nicolau DP. Cost-effectiveness of ceftazidime
by continuous infusion versus intermittent infusion for nosocomial pneumonia.
Pharmacotherapy 2001; 21: 549-55.
376. Jaruratanasirikul S, Sriwiriyajan S. Comparison of the pharmacodynamics of meropenem in
healthy volunteers following administration by intermittent infusion or bolus injection. J
Antimicrob Chemother 2003; 52: 518-21.
377. Tamma PD, Putcha N, Suh YD, Van Arendonk KJ, Rinke ML. Does prolonged beta-lactam
infusions improve clinical outcomes compared to intermittent infusions? A meta-analysis
and systematic review of randomized, controlled trials. BMC Infect Dis 2011; 11: 181.
228
378. Roberts JA, De Waele JJ, Dimopoulos G, Koulenti D, Martin C, Montravers P, Rello J,
Rhodes A, Starr T, Wallis SC, Lipman J. DALI: Defining Antibiotic Levels in Intensive
care unit patients: a multi-centre point of prevalence study to determine whether
contemporary antibiotic dosing for critically ill patients is therapeutic. BMC Infect Dis
2012; 12: 152.
379. Briscoe SE, McWhinney BC, Lipman J, Roberts JA, Ungerer JP. A method for determining
the free (unbound) concentration of ten beta-lactam antibiotics in human plasma using high
performance liquid chromatography with ultraviolet detection. J Chromatogr B Analyt
Technol Biomed Life Sci 2012; 907: 178-84.
380. MacVane SH, Kuti JL, Nicolau DP. Clinical pharmacodynamics of antipseudomonal
cephalosporins in patients with ventilator-associated pneumonia. Antimicrob Agents
Chemother 2014; 58: 1359-64.
381. Houck PM, Bratzler DW, Nsa W, Ma A, Bartlett JG. Timing of antibiotic administration
and outcomes for Medicare patients hospitalized with community-acquired pneumonia.
Archives of internal medicine 2004; 164: 637-44.
382. Hanes SD, Demirkan K, Tolley E, Boucher BA, Croce MA, Wood GC, Fabian TC. Risk
factors for late-onset nosocomial pneumonia caused by Stenotrophomonas maltophilia in
critically ill trauma patients. Clinical infectious diseases : an official publication of the
Infectious Diseases Society of America 2002; 35: 228-35.
383. Dulhunty JM, Paterson D, Webb SA, Lipman J. Antimicrobial utilisation in 37 Australian
and New Zealand intensive care units. Anaesth Intensive Care 2011; 39: 231-7.
384. Dulhunty JM, Webb SA, Paterson DL, Bellomo R, Myburgh J, Roberts JA, Lipman J. A
survey of antibiotic prescribing practices in Australian and New Zealand intensive care
units. Crit Care Resusc 2010; 12: 162-70.
385. Udy AA, Varghese JM, Altukroni M, Briscoe S, McWhinney B, Ungerer J, Lipman J,
Roberts JA. Sub-therapeutic initial beta-lactam concentrations in select critically ill patients:
association between augmented renal clearance and low trough drug concentrations. Chest
2011.
386. Moore RD, Lietman PS, Smith CR. Clinical response to aminoglycoside therapy:
importance of the ratio of peak concentration to minimal inhibitory concentration. J Infect
Dis 1987; 155: 93-9.
387. Moore RD, Smith CR, Lietman PS. Association of aminoglycoside plasma levels with
therapeutic outcome in gram-negative pneumonia. Am J Med 1984; 77: 657-62.
229
388. Freeman CD, Nicolau DP, Belliveau PP, Nightingale CH. Once-daily dosing of
aminoglycosides: review and recommendations for clinical practice. J Antimicrob
Chemother 1997; 39: 677-86.
389. Forrest A, Nix DE, Ballow CH, Goss TF, Birmingham MC, Schentag JJ.
Pharmacodynamics of intravenous ciprofloxacin in seriously ill patients. Antimicrob Agents
Chemother 1993; 37: 1073-81.
390. Craig WA. Interrelationship between pharmacokinetics and pharmacodynamics in
determining dosage regimens for broad-spectrum cephalosporins. Diagn Microbiol Infect
Dis 1995; 22: 89-96.
391. Eagle H, Fleischman R, Levy M. "Continuous" vs. "discontinuous" therapy with penicillin;
the effect of the interval between injections on therapeutic efficacy. N Engl J Med 1953;
248: 481-8.
392. Gerber AU, Craig WA, Brugger HP, Feller C, Vastola AP, Brandel J. Impact of dosing
intervals on activity of gentamicin and ticarcillin against Pseudomonas aeruginosa in
granulocytopenic mice. J Infect Dis 1983; 147: 910-7.
393. Mouton JW, Punt N, Vinks AA. Concentration-effect relationship of ceftazidime explains
why the time above the MIC is 40 percent for a static effect in vivo. Antimicrob Agents
Chemother 2007; 51: 3449-51.
394. Scaglione F, Paraboni L. Pharmacokinetics/pharmacodynamics of antibacterials in the
Intensive Care Unit: setting appropriate dosing regimens. Int J Antimicrob Agents 2008; 32:
294-301.
395. Nicolau DP. Pharmacodynamic optimization of beta-lactams in the patient care setting. Crit
Care 2008; 12 Suppl 4: S2.
396. Kasiakou SK, Lawrence KR, Choulis N, Falagas ME. Continuous versus intermittent
intravenous administration of antibacterials with time-dependent action: a systematic review
of pharmacokinetic and pharmacodynamic parameters. Drugs 2005; 65: 2499-511.
397. Jaruratanasirikul S, Sriwiriyajan S, Ingviya N. Continuous infusion versus intermittent
administration of cefepime in patients with Gram-negative bacilli bacteraemia. J Pharm
Pharmacol 2002; 54: 1693-6.
398. Drusano GL. Prevention of resistance: a goal for dose selection for antimicrobial agents.
Clin Infect Dis 2003; 36: S42-50.
399. Livermore DM. Fourteen years in resistance. Int J Antimicrob Agents 2012; 39: 283-94.
400. Chahine EB, Ferrill MJ, Poulakos MN. Doripenem: a new carbapenem antibiotic. Am J
Health Syst Pharm 2010; 67: 2015-24.
230
401. Jumbe N, Louie A, Leary R, Liu W, Deziel MR, Tam VH, Bachhawat R, Freeman C, Kahn
JB, Bush K, Dudley MN, Miller MH, Drusano GL. Application of a mathematical model to
prevent in vivo amplification of antibiotic-resistant bacterial populations during therapy. J
Clin Invest 2003; 112: 275-85.
402. Thomas JK, Forrest A, Bhavnani SM, Hyatt JM, Cheng A, Ballow CH, Schentag JJ.
Pharmacodynamic evaluation of factors associated with the development of bacterial
resistance in acutely ill patients during therapy. Antimicrob Agents Chemother 1998; 42:
521-7.
403. Odenholt I, Gustafsson I, Lowdin E, Cars O. Suboptimal antibiotic dosage as a risk factor
for selection of penicillin-resistant Streptococcus pneumoniae: in vitro kinetic model.
Antimicrob Agents Chemother 2003; 47: 518-23.
404. Fantin B, Farinotti R, Thabaut A, Carbon C. Conditions for the emergence of resistance to
cefpirome and ceftazidime in experimental endocarditis due to Pseudomonas aeruginosa. J
Antimicrob Chemother 1994; 33: 563-9.
405. Tam VH, Schilling AN, Neshat S, Poole K, Melnick DA, Coyle EA. Optimization of
meropenem minimum concentration/MIC ratio to suppress in vitro resistance of
Pseudomonas aeruginosa. Antimicrob Agents Chemother 2005; 49: 4920-7.
406. Eagle H, Fleischman R, Musselman AD. Effect of schedule of administration on the
therapeutic efficacy of penicillin; importance of the aggregate time penicillin remains at
effectively bactericidal levels. Am J Med 1950; 9: 280-99.
407. Kojika M, Sato N, Hakozaki M, Suzuki Y, Takahasi G, Endo S, Suzuki K, Wakabayasi G.
[A preliminary study of the administration of carbapenem antibiotics in sepsis patients on
the basis of the administration time]. Jpn J Antibiot 2005; 58: 452-7.
408. Ranieri VM, Thompson BT, Barie PS, Dhainaut JF, Douglas IS, Finfer S, Gardlund B,
Marshall JC, Rhodes A, Artigas A, Payen D, Tenhunen J, Al-Khalidi HR, Thompson V,
Janes J, Macias WL, Vangerow B, Williams MD, Group P-SS. Drotrecogin alfa (activated)
in adults with septic shock. N Engl J Med 2012; 366: 2055-64.
409. Duszynska W, Taccone FS, Switala M, Hurkacz M, Kowalska-Krochmal B, Kubler A.
Continuous infusion of piperacillin/tazobactam in ventilator-associated pneumonia: a pilot
study on efficacy and costs. Int J Antimicrob Agents 2012; 39: 153-8.
410. Kellum JA. Acute kidney injury. Crit Care Med 2008; 36: S141-5.
411. Hoste EA, Clermont G, Kersten A, Venkataraman R, Angus DC, De Bacquer D, Kellum JA.
RIFLE criteria for acute kidney injury are associated with hospital mortality in critically ill
patients: a cohort analysis. Crit Care 2006; 10: R73.
231
412. Dyson A, Singer M. Animal models of sepsis: why does preclinical efficacy fail to translate
to the clinical setting? Crit Care Med 2009; 37: S30-7.
413. Rittirsch D, Hoesel LM, Ward PA. The disconnect between animal models of sepsis and
human sepsis. J Leukoc Biol 2007; 81: 137-43.
414. Abdul-Aziz M, Sulaiman H, Mat-Nor M, Rai V, Wong K, Hasan M, Wallis S, Lipman J,
Staatz C, Roberts J. The BLISS Study: Beta-Lactam Infusion in Severe Sepsis-Randomised
controlled trial of continuous versus intermittent beta-lactam infusion in critically ill patients
with severe sepsis in a Malaysian ICU setting. In 55th Interscience Conference of
Antimicrobial Agents and Chemotherapy (ICAAC): September 18-21, 2015; San Diego, CA
2015.
415. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic
comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987; 40:
373-83.
416. Naranjo CA, Busto U, Sellers EM, Sandor P, Ruiz I, Roberts EA, Janecek E, Domecq C,
Greenblatt DJ. A method for estimating the probability of adverse drug reactions. Clin
Pharmacol Ther 1981; 30: 239-45.
417. McWhinney BC, Wallis SC, Hillister T, Roberts JA, Lipman J, Ungerer JP. Analysis of 12
beta-lactam antibiotics in human plasma by HPLC with ultraviolet detection. J Chromatogr
B Analyt Technol Biomed Life Sci 2010; 878: 2039-43.
418. Mustafa M, Chan WM, Lee C, Harijanto E, Loo CM, Van Kinh N, Anh ND, Garcia J. A
PROspective study on the Usage patterns of Doripenem in the Asia-Pacific region (PROUD
study). Int J Antimicrob Agents 2014; 43: 353-60.
419. Carlier M, Dumoulin A, Janssen A, Picavet S, Vanthuyne S, Van Eynde R, Vanholder R,
Delanghe J, De Schoenmakere G, De Waele JJ, Hoste EA. Comparison of different
equations to assess glomerular filtration in critically ill patients. Intensive Care Med 2015;
41: 427-35.
420. Warren BL, Eid A, Singer P, Pillay SS, Carl P, Novak I, Chalupa P, Atherstone A, Penzes I,
Kubler A, Knaub S, Keinecke HO, Heinrichs H, Schindel F, Juers M, Bone RC, Opal SM.
Caring for the critically ill patient. High-dose antithrombin III in severe sepsis: a
randomized controlled trial. JAMA 2001; 286: 1869-78.
421. Finfer S, Chittock DR, Su SY, Blair D, Foster D, Dhingra V, Bellomo R, Cook D, Dodek P,
Henderson WR, Hebert PC, Heritier S, Heyland DK, McArthur C, McDonald E, Mitchell I,
Myburgh JA, Norton R, Potter J, Robinson BG, Ronco JJ. Intensive versus conventional
glucose control in critically ill patients. N Engl J Med 2009; 360: 1283-97.
232
422. Garnacho-Montero J, Aldabo-Pallas T, Garnacho-Montero C, Cayuela A, Jimenez R,
Barroso S, Ortiz-Leyba C. Timing of adequate antibiotic therapy is a greater determinant of
outcome than are TNF and IL-10 polymorphisms in patients with sepsis. Crit Care 2006; 10:
R111.
423. Garnacho-Montero J, Garcia-Garmendia JL, Barrero-Almodovar A, Jimenez-Jimenez FJ,
Perez-Paredes C, Ortiz-Leyba C. Impact of adequate empirical antibiotic therapy on the
outcome of patients admitted to the intensive care unit with sepsis. Crit Care Med 2003; 31:
2742-51.
424. Singh N, Yu VL. Rational empiric antibiotic prescription in the ICU. Chest 2000; 117:
1496-9.
425. Fridkin SK, Gaynes RP. Antimicrobial resistance in intensive care units. Clin Chest Med
1999; 20: 303-16, viii.
426. Ben-David D, Kordevani R, Keller N, Tal I, Marzel A, Gal-Mor O, Maor Y, Rahav G.
Outcome of carbapenem resistant Klebsiella pneumoniae bloodstream infections. Clin
Microbiol Infect 2012; 18: 54-60.
427. Lye DC, Earnest A, Ling ML, Lee TE, Yong HC, Fisher DA, Krishnan P, Hsu LY. The
impact of multidrug resistance in healthcare-associated and nosocomial Gram-negative
bacteraemia on mortality and length of stay: cohort study. Clin Microbiol Infect 2011.
428. Shorr AF. Review of studies of the impact on Gram-negative bacterial resistance on
outcomes in the intensive care unit. Crit Care Med 2009; 37: 1463-9.
429. Zeitlinger MA, Derendorf H, Mouton JW, Cars O, Craig WA, Andes D, Theuretzbacher U.
Protein binding: do we ever learn? Antimicrob Agents Chemother 2011; 55: 3067-74.
430. Mouton JW, Jacobs N, Tiddens H, Horrevorts AM. Pharmacodynamics of tobramycin in
patients with cystic fibrosis. Diagn Microbiol Infect Dis 2005; 52: 123-7.
431. Craig WA, Redington J, Ebert SC. Pharmacodynamics of amikacin in vitro and in mouse
thigh and lung infections. J Antimicrob Chemother 1991; 27 Suppl C: 29-40.
432. Moise-Broder PA, Forrest A, Birmingham MC, Schentag JJ. Pharmacodynamics of
vancomycin and other antimicrobials in patients with Staphylococcus aureus lower
respiratory tract infections. Clin Pharmacokinet 2004; 43: 925-42.
433. Firsov AA, Strukova EN, Shlykova DS, Portnoy YA, Kozyreva VK, Edelstein MV,
Dovzhenko SA, Kobrin MB, Zinner SH. Bacterial resistance studies using in vitro dynamic
models: the predictive power of the mutant prevention and minimum inhibitory antibiotic
concentrations. Antimicrob Agents Chemother 2013; 57: 4956-62.
434. Tam VH, Louie A, Deziel MR, Liu W, Drusano GL. The relationship between quinolone
exposures and resistance amplification is characterized by an inverted U: a new paradigm
233
for optimizing pharmacodynamics to counterselect resistance. Antimicrob Agents
Chemother 2007; 51: 744-7.
435. Tam VH, Louie A, Deziel MR, Liu W, Leary R, Drusano GL. Bacterial-population
responses to drug-selective pressure: examination of garenoxacin's effect on Pseudomonas
aeruginosa. J Infect Dis 2005; 192: 420-8.
436. Firsov AA, Vostrov SN, Lubenko IY, Drlica K, Portnoy YA, Zinner SH. In vitro
pharmacodynamic evaluation of the mutant selection window hypothesis using four
fluoroquinolones against Staphylococcus aureus. Antimicrob Agents Chemother 2003; 47:
1604-13.
437. Stearne LE, Goessens WH, Mouton JW, Gyssens IC. Effect of dosing and dosing frequency
on the efficacy of ceftizoxime and the emergence of ceftizoxime resistance during the early
development of murine abscesses caused by Bacteroides fragilis and Enterobacter cloacae
mixed infection. Antimicrob Agents Chemother 2007; 51: 3605-11.
438. Tam VH, Louie A, Fritsche TR, Deziel M, Liu W, Brown DL, Deshpande L, Leary R, Jones
RN, Drusano GL. Impact of drug-exposure intensity and duration of therapy on the
emergence of Staphylococcus aureus resistance to a quinolone antimicrobial. J Infect Dis
2007; 195: 1818-27.
439. LaPlante KL, Rybak MJ, Tsuji B, Lodise TP, Kaatz GW. Fluoroquinolone resistance in
Streptococcus pneumoniae: area under the concentration-time curve/MIC ratio and
resistance development with gatifloxacin, gemifloxacin, levofloxacin, and moxifloxacin.
Antimicrob Agents Chemother 2007; 51: 1315-20.
440. Drusano GL, Bonomo RA, Bahniuk N, Bulitta JB, Vanscoy B, Defiglio H, Fikes S, Brown
D, Drawz SM, Kulawy R, Louie A. Resistance emergence mechanism and mechanism of
resistance suppression by tobramycin for cefepime for Pseudomonas aeruginosa. Antimicrob
Agents Chemother 2012; 56: 231-42.
441. Gumbo T, Louie A, Deziel MR, Parsons LM, Salfinger M, Drusano GL. Selection of a
moxifloxacin dose that suppresses drug resistance in Mycobacterium tuberculosis, by use of
an in vitro pharmacodynamic infection model and mathematical modeling. J Infect Dis
2004; 190: 1642-51.
442. Baquero F, Negri MC. Strategies to minimize the development of antibiotic resistance. J
Chemother 1997; 9 Suppl 3: 29-37.
443. Baquero F. Resistance to quinolones in gram-negative microorganisms: mechanisms and
prevention. Eur Urol 1990; 17 Suppl 1: 3-12.
444. Zhao X, Drlica K. Restricting the selection of antibiotic-resistant mutants: a general strategy
derived from fluoroquinolone studies. Clin Infect Dis 2001; 33 Suppl 3: S147-56.
234
445. Dong Y, Zhao X, Kreiswirth BN, Drlica K. Mutant prevention concentration as a measure of
antibiotic potency: studies with clinical isolates of Mycobacterium tuberculosis. Antimicrob
Agents Chemother 2000; 44: 2581-4.
446. Dong Y, Zhao X, Domagala J, Drlica K. Effect of fluoroquinolone concentration on
selection of resistant mutants of Mycobacterium bovis BCG and Staphylococcus aureus.
Antimicrob Agents Chemother 1999; 43: 1756-8.
447. Zhou J, Dong Y, Zhao X, Lee S, Amin A, Ramaswamy S, Domagala J, Musser JM, Drlica
K. Selection of antibiotic-resistant bacterial mutants: allelic diversity among
fluoroquinolone-resistant mutations. J Infect Dis 2000; 182: 517-25.
448. Firsov AA, Smirnova MV, Lubenko IY, Vostrov SN, Portnoy YA, Zinner SH. Testing the
mutant selection window hypothesis with Staphylococcus aureus exposed to daptomycin
and vancomycin in an in vitro dynamic model. J Antimicrob Chemother 2006; 58: 1185-92.
449. Campion JJ, Chung P, McNamara PJ, Titlow WB, Evans ME. Pharmacodynamic modeling
of the evolution of levofloxacin resistance in Staphylococcus aureus. Antimicrob Agents
Chemother 2005; 49: 2189-99.
450. Zinner SH, Lubenko IY, Gilbert D, Simmons K, Zhao X, Drlica K, Firsov AA. Emergence
of resistant Streptococcus pneumoniae in an in vitro dynamic model that simulates
moxifloxacin concentrations inside and outside the mutant selection window: related
changes in susceptibility, resistance frequency and bacterial killing. J Antimicrob
Chemother 2003; 52: 616-22.
451. Cui J, Liu Y, Wang R, Tong W, Drlica K, Zhao X. The mutant selection window in rabbits
infected with Staphylococcus aureus. J Infect Dis 2006; 194: 1601-8.
452. Croisier D, Etienne M, Piroth L, Bergoin E, Lequeu C, Portier H, Chavanet P. In vivo
pharmacodynamic efficacy of gatifloxacin against Streptococcus pneumoniae in an
experimental model of pneumonia: impact of the low levels of fluoroquinolone resistance on
the enrichment of resistant mutants. J Antimicrob Chemother 2004; 54: 640-7.
453. Etienne M, Croisier D, Charles PE, Lequeu C, Piroth L, Portier H, Drlica K, Chavanet P.
Effect of low-level resistance on subsequent enrichment of fluoroquinolone-resistant
Streptococcus pneumoniae in rabbits. J Infect Dis 2004; 190: 1472-5.
454. Andes D, Craig WA. Pharmacodynamics of the new fluoroquinolone gatifloxacin in murine
thigh and lung infection models. Antimicrob Agents Chemother 2002; 46: 1665-70.
455. Olofsson SK, Marcusson LL, Komp Lindgren P, Hughes D, Cars O. Selection of
ciprofloxacin resistance in Escherichia coli in an in vitro kinetic model: relation between
drug exposure and mutant prevention concentration. J Antimicrob Chemother 2006; 57:
1116-21.
235
456. Croisier D, Etienne M, Bergoin E, Charles PE, Lequeu C, Piroth L, Portier H, Chavanet P.
Mutant selection window in levofloxacin and moxifloxacin treatments of experimental
pneumococcal pneumonia in a rabbit model of human therapy. Antimicrob Agents
Chemother 2004; 48: 1699-707.
457. Knudsen JD, Odenholt I, Erlendsdottir H, Gottfredsson M, Cars O, Frimodt-Moller N,
Espersen F, Kristinsson KG, Gudmundsson S. Selection of resistant Streptococcus
pneumoniae during penicillin treatment in vitro and in three animal models. Antimicrob
Agents Chemother 2003; 47: 2499-506.
458. Liang B, Bai N, Cai Y, Wang R, Drlica K, Zhao X. Mutant prevention concentration-based
pharmacokinetic/pharmacodynamic indices as dosing targets for suppressing the enrichment
of levofloxacin-resistant subpopulations of Staphylococcus aureus. Antimicrob Agents
Chemother 2011; 55: 2409-12.
459. Firsov AA, Smirnova MV, Strukova EN, Vostrov SN, Portnoy YA, Zinner SH. Enrichment
of resistant Staphylococcus aureus at ciprofloxacin concentrations simulated within the
mutant selection window: bolus versus continuous infusion. Int J Antimicrob Agents 2008;
32: 488-93.
460. Firsov AA, Vostrov SN, Lubenko IY, Arzamastsev AP, Portnoy YA, Zinner SH. ABT492
and levofloxacin: comparison of their pharmacodynamics and their abilities to prevent the
selection of resistant Staphylococcus aureus in an in vitro dynamic model. J Antimicrob
Chemother 2004; 54: 178-86.
461. Gugel J, Dos Santos Pereira A, Pignatari AC, Gales AC. beta-Lactam MICs correlate poorly
with mutant prevention concentrations for clinical isolates of Acinetobacter spp. and
Pseudomonas aeruginosa. Antimicrob Agents Chemother 2006; 50: 2276-7.
462. Hansen GT, Metzler K, Drlica K, Blondeau JM. Mutant prevention concentration of
gemifloxacin for clinical isolates of Streptococcus pneumoniae. Antimicrob Agents
Chemother 2003; 47: 440-1.
463. Drusano GL, Johnson DE, Rosen M, Standiford HC. Pharmacodynamics of a
fluoroquinolone antimicrobial agent in a neutropenic rat model of Pseudomonas sepsis.
Antimicrob Agents Chemother 1993; 37: 483-90.
464. Blaser J, Stone BB, Groner MC, Zinner SH. Comparative study with enoxacin and
netilmicin in a pharmacodynamic model to determine importance of ratio of antibiotic peak
concentration to MIC for bactericidal activity and emergence of resistance. Antimicrob
Agents Chemother 1987; 31: 1054-60.
236
465. Thorburn CE, Edwards DI. The effect of pharmacokinetics on the bactericidal activity of
ciprofloxacin and sparfloxacin against Streptococcus pneumoniae and the emergence of
resistance. J Antimicrob Chemother 2001; 48: 15-22.
466. Peloquin CA, Cumbo TJ, Nix DE, Sands MF, Schentag JJ. Evaluation of intravenous
ciprofloxacin in patients with nosocomial lower respiratory tract infections. Impact of
plasma concentrations, organism, minimum inhibitory concentration, and clinical condition
on bacterial eradication. Arch Intern Med 1989; 149: 2269-73.
467. Zelenitsky SA, Ariano RE. Support for higher ciprofloxacin AUC 24/MIC targets in treating
Enterobacteriaceae bloodstream infection. J Antimicrob Chemother 2010; 65: 1725-32.
468. Drusano GL, Preston SL, Fowler C, Corrado M, Weisinger B, Kahn J. Relationship between
fluoroquinolone area under the curve: minimum inhibitory concentration ratio and the
probability of eradication of the infecting pathogen, in patients with nosocomial pneumonia.
J Infect Dis 2004; 189: 1590-7.
469. Ambrose PG, Grasela DM, Grasela TH, Passarell J, Mayer HB, Pierce PF.
Pharmacodynamics of fluoroquinolones against Streptococcus pneumoniae in patients with
community-acquired respiratory tract infections. Antimicrob Agents Chemother 2001; 45:
2793-7.
470. Mattoes HM, Banevicius M, Li D, Turley C, Xuan D, Nightingale CH, Nicolau DP.
Pharmacodynamic assessment of gatifloxacin against Streptococcus pneumoniae.
Antimicrob Agents Chemother 2001; 45: 2092-7.
471. Bedos JP, Azoulay-Dupuis E, Moine P, Muffat-Joly M, Veber B, Pocidalo JJ, Vallee E.
Pharmacodynamic activities of ciprofloxacin and sparfloxacin in a murine pneumococcal
pneumonia model: relevance for drug efficacy. J Pharmacol Exp Ther 1998; 286: 29-35.
472. Schentag JJ, Gilliland KK, Paladino JA. What have we learned from pharmacokinetic and
pharmacodynamic theories? Clin Infect Dis 2001; 32 Suppl 1: S39-46.
473. Burgess DS, Hall RG, 2nd. Simulated comparison of the pharmacodynamics of
ciprofloxacin and levofloxacin against Pseudomonas aeruginosa using pharmacokinetic data
from healthy volunteers and 2002 minimum inhibitory concentration data. Clin Ther 2007;
29: 1421-7.
474. Zelenitsky SA, Harding GK, Sun S, Ubhi K, Ariano RE. Treatment and outcome of
Pseudomonas aeruginosa bacteraemia: an antibiotic pharmacodynamic analysis. J
Antimicrob Chemother 2003; 52: 668-74.
475. Smith PF, Ballow CH, Booker BM, Forrest A, Schentag JJ. Pharmacokinetics and
pharmacodynamics of aztreonam and tobramycin in hospitalized patients. Clin Ther 2001;
23: 1231-44.
237
476. Drusano GL, Ambrose PG, Bhavnani SM, Bertino JS, Nafziger AN, Louie A. Back to the
future: using aminoglycosides again and how to dose them optimally. Clin Infect Dis 2007;
45: 753-60.
477. Tam VH, Ledesma KR, Vo G, Kabbara S, Lim TP, Nikolaou M. Pharmacodynamic
modeling of aminoglycosides against Pseudomonas aeruginosa and Acinetobacter
baumannii: identifying dosing regimens to suppress resistance development. Antimicrob
Agents Chemother 2008; 52: 3987-93.
478. Kashuba AD, Nafziger AN, Drusano GL, Bertino JS, Jr. Optimizing aminoglycoside
therapy for nosocomial pneumonia caused by gram-negative bacteria. Antimicrob Agents
Chemother 1999; 43: 623-9.
479. Goessens WH, Mouton JW, ten Kate MT, Bijl AJ, Ott A, Bakker-Woudenberg IA. Role of
ceftazidime dose regimen on the selection of resistant Enterobacter cloacae in the intestinal
flora of rats treated for an experimental pulmonary infection. J Antimicrob Chemother 2007;
59: 507-16.
480. Tam VH, Ledesma KR, Schilling AN, Lim TP, Yuan Z, Ghose R, Lewis RE. In vivo
dynamics of carbapenem-resistant Pseudomonas aeruginosa selection after suboptimal
dosing. Diagn Microbiol Infect Dis 2009; 64: 427-33.
481. Zinner SH, Gilbert D, Greer K, Portnoy YA, Firsov AA. Concentration-resistance
relationships with Pseudomonas aeruginosa exposed to doripenem and ciprofloxacin in an in
vitro model. J Antimicrob Chemother 2013; 68: 881-7.
482. Firsov AA, Vostrov SN, Lubenko IY, Zinner SH, Portnoy YA. Concentration-dependent
changes in the susceptibility and killing of Staphylococcus aureus in an in vitro dynamic
model that simulates normal and impaired gatifloxacin elimination. Int J Antimicrob Agents
2004; 23: 60-6.
483. Zelenitsky S, Rubinstein E, Ariano R, Iacovides H, Dodek P, Mirzanejad Y, Kumar A, the
Cooperative Antimicrobial Therapy of Septic Shock Database Research G. Vancomycin
pharmacodynamics and survival in patients with methicillin-resistant Staphylococcus
aureus-associated septic shock. Int J Antimicrob Agents 2013.
484. Andes D, van Ogtrop ML, Peng J, Craig WA. In vivo pharmacodynamics of a new
oxazolidinone (linezolid). Antimicrob Agents Chemother 2002; 46: 3484-9.
485. Rayner CR, Forrest A, Meagher AK, Birmingham MC, Schentag JJ. Clinical
pharmacodynamics of linezolid in seriously ill patients treated in a compassionate use
programme. Clin Pharmacokinet 2003; 42: 1411-23.
238
486. Buchanan LV, Dailey CF, LeMay RJ, Zielinski RJ, Kuo MS, Gibson JK. Time-dependent
antibacterial effects of linezolid in experimental rabbit endocarditis. J Antimicrob
Chemother 2002; 50: 440-2.
487. Safdar N, Andes D, Craig WA. In vivo pharmacodynamic activity of daptomycin.
Antimicrob Agents Chemother 2004; 48: 63-8.
488. Lim LM, Ly N, Anderson D, Yang JC, Macander L, Jarkowski A, 3rd, Forrest A, Bulitta JB,
Tsuji BT. Resurgence of colistin: a review of resistance, toxicity, pharmacodynamics, and
dosing. Pharmacotherapy 2010; 30: 1279-91.
489. Yau W, Owen RJ, Poudyal A, Bell JM, Turnidge JD, Yu HH, Nation RL, Li J. Colistin
hetero-resistance in multidrug-resistant Acinetobacter baumannii clinical isolates from the
Western Pacific region in the SENTRY antimicrobial surveillance programme. J Infect
2009; 58: 138-44.
490. Gebru E, Choi MJ, Lee SJ, Damte D, Park SC. Mutant-prevention concentration and
mechanism of resistance in clinical isolates and enrofloxacin/marbofloxacin-selected
mutants of Escherichia coli of canine origin. J Med Microbiol 2011; 60: 1512-22.
491. Khachman D, Conil JM, Georges B, Saivin S, Houin G, Toutain PL, Laffont CM.
Optimizing ciprofloxacin dosing in intensive care unit patients through the use of population
pharmacokinetic-pharmacodynamic analysis and Monte Carlo simulations. J Antimicrob
Chemother 2011; 66: 1798-809.
492. MacArthur RD, Lolans V, Zar FA, Jackson GG. Biphasic, concentration-dependent and
rate-limited, concentration-independent bacterial killing by an aminoglycoside antibiotic. J
Infect Dis 1984; 150: 778-9.
493. Mouton JW, Vinks AA. Pharmacokinetic/pharmacodynamic modelling of antibacterials in
vitro and in vivo using bacterial growth and kill kinetics: the minimum inhibitory
concentration versus stationary concentration. Clin Pharmacokinet 2005; 44: 201-10.
494. Xiong YQ, Caillon J, Kergueris MF, Drugeon H, Baron D, Potel G, Bayer AS. Adaptive
resistance of Pseudomonas aeruginosa induced by aminoglycosides and killing kinetics in a
rabbit endocarditis model. Antimicrob Agents Chemother 1997; 41: 823-6.
495. Barclay ML, Begg EJ, Chambers ST. Adaptive resistance following single doses of
gentamicin in a dynamic in vitro model. Antimicrob Agents Chemother 1992; 36: 1951-7.
496. Daikos GL, Lolans VT, Jackson GG. First-exposure adaptive resistance to aminoglycoside
antibiotics in vivo with meaning for optimal clinical use. Antimicrob Agents Chemother
1991; 35: 117-23.
497. Prins JM, Buller HR, Kuijper EJ, Tange RA, Speelman P. Once versus thrice daily
gentamicin in patients with serious infections. Lancet 1993; 341: 335-9.
239
498. Marik PE, Lipman J, Kobilski S, Scribante J. A prospective randomized study comparing
once- versus twice-daily amikacin dosing in critically ill adult and paediatric patients. J
Antimicrob Chemother 1991; 28: 753-64.
499. Bailey TC, Little JR, Littenberg B, Reichley RM, Dunagan WC. A meta-analysis of
extended-interval dosing versus multiple daily dosing of aminoglycosides. Clin Infect Dis
1997; 24: 786-95.
500. Munckhof WJ, Grayson ML, Turnidge JD. A meta-analysis of studies on the safety and
efficacy of aminoglycosides given either once daily or as divided doses. J Antimicrob
Chemother 1996; 37: 645-63.
501. Ong CT, Tessier PR, Li C, Nightingale CH, Nicolau DP. Comparative in vivo efficacy of
meropenem, imipenem, and cefepime against Pseudomonas aeruginosa expressing MexA-
MexB-OprM efflux pumps. Diagn Microbiol Infect Dis 2007; 57: 153-61.
502. Olofsson SK, Geli P, Andersson DI, Cars O. Pharmacodynamic model to describe the
concentration-dependent selection of cefotaxime-resistant Escherichia coli. Antimicrob
Agents Chemother 2005; 49: 5081-91.
503. Tam VH, Schilling AN, Melnick DA, Coyle EA. Comparison of beta-lactams in counter-
selecting resistance of Pseudomonas aeruginosa. Diagn Microbiol Infect Dis 2005; 52: 145-
51.
504. Felton TW, Goodwin J, O'Connor L, Sharp A, Gregson L, Livermore J, Howard SJ, Neely
MN, Hope WW. Impact of Bolus dosing versus continuous infusion of Piperacillin and
Tazobactam on the development of antimicrobial resistance in Pseudomonas aeruginosa.
Antimicrob Agents Chemother 2013; 57: 5811-9.
505. Fuentes F, Martin MM, Izquierdo J, Gomez-Lus ML, Prieto J. In vivo and in vitro study of
several pharmacodynamic effects of meropenem. Scand J Infect Dis 1995; 27: 469-74.
506. Krueger WA, Bulitta J, Kinzig-Schippers M, Landersdorfer C, Holzgrabe U, Naber KG,
Drusano GL, Sorgel F. Evaluation by monte carlo simulation of the pharmacokinetics of two
doses of meropenem administered intermittently or as a continuous infusion in healthy
volunteers. Antimicrob Agents Chemother 2005; 49: 1881-9.
507. Louie A, Bied A, Fregeau C, Van Scoy B, Brown D, Liu W, Bush K, Queenan AM, Morrow
B, Khashab M, Kahn JB, Nicholson S, Kulawy R, Drusano GL. Impact of different
carbapenems and regimens of administration on resistance emergence for three isogenic
Pseudomonas aeruginosa strains with differing mechanisms of resistance. Antimicrob
Agents Chemother 2010; 54: 2638-45.
240
508. Lowdin E, Odenholt I, Cars O. In vitro studies of pharmacodynamic properties of
vancomycin against Staphylococcus aureus and Staphylococcus epidermidis. Antimicrob
Agents Chemother 1998; 42: 2739-44.
509. Larsson AJ, Walker KJ, Raddatz JK, Rotschafer JC. The concentration-independent effect
of monoexponential and biexponential decay in vancomycin concentrations on the killing of
Staphylococcus aureus under aerobic and anaerobic conditions. J Antimicrob Chemother
1996; 38: 589-97.
510. Chambers HF, Kennedy S. Effects of dosage, peak and trough concentrations in serum,
protein binding, and bactericidal rate on efficacy of teicoplanin in a rabbit model of
endocarditis. Antimicrob Agents Chemother 1990; 34: 510-4.
511. Knudsen JD, Fuursted K, Raber S, Espersen F, Frimodt-Moller N. Pharmacodynamics of
glycopeptides in the mouse peritonitis model of Streptococcus pneumoniae or
Staphylococcus aureus infection. Antimicrob Agents Chemother 2000; 44: 1247-54.
512. Moise PA, Forrest A, Bhavnani SM, Birmingham MC, Schentag JJ. Area under the
inhibitory curve and a pneumonia scoring system for predicting outcomes of vancomycin
therapy for respiratory infections by Staphylococcus aureus. Am J Health Syst Pharm 2000;
57 Suppl 2: S4-9.
513. Rybak MJ, Lomaestro BM, Rotschafer JC, Moellering RC, Craig WA, Billeter M, Dalovisio
JR, Levine DP. Vancomycin therapeutic guidelines: a summary of consensus
recommendations from the infectious diseases Society of America, the American Society of
Health-System Pharmacists, and the Society of Infectious Diseases Pharmacists. Clin Infect
Dis 2009; 49: 325-7.
514. Guidelines for the management of adults with hospital-acquired, ventilator-associated, and
healthcare-associated pneumonia. Am J Respir Crit Care Med 2005; 171: 388-416.
515. Tsuji BT, Rybak MJ, Lau KL, Sakoulas G. Evaluation of accessory gene regulator (agr)
group and function in the proclivity towards vancomycin intermediate resistance in
Staphylococcus aureus. Antimicrob Agents Chemother 2007; 51: 1089-91.
516. Charles PG, Ward PB, Johnson PD, Howden BP, Grayson ML. Clinical features associated
with bacteremia due to heterogeneous vancomycin-intermediate Staphylococcus aureus.
Clin Infect Dis 2004; 38: 448-51.
517. Sakoulas G, Gold HS, Cohen RA, Venkataraman L, Moellering RC, Eliopoulos GM. Effects
of prolonged vancomycin administration on methicillin-resistant Staphylococcus aureus
(MRSA) in a patient with recurrent bacteraemia. J Antimicrob Chemother 2006; 57: 699-
704.
241
518. Howden BP, Ward PB, Charles PG, Korman TM, Fuller A, du Cros P, Grabsch EA, Roberts
SA, Robson J, Read K, Bak N, Hurley J, Johnson PD, Morris AJ, Mayall BC, Grayson ML.
Treatment outcomes for serious infections caused by methicillin-resistant Staphylococcus
aureus with reduced vancomycin susceptibility. Clin Infect Dis 2004; 38: 521-8.
519. Zoller M, Maier B, Hornuss C, Neugebauer C, Dobbeler G, Nagel D, Holdt LM, Bruegel M,
Weig T, Grabein B, Frey L, Teupser D, Vogeser M, Zander J. Variability of linezolid
concentrations after standard dosing in critically ill patients: a prospective observational
study. Crit Care 2014; 18: R148.
520. Dong H, Wang X, Dong Y, Lei J, Li H, You H, Wang M, Xing J, Sun J, Zhu H. Clinical
pharmacokinetic/pharmacodynamic profile of linezolid in severely ill intensive care unit
patients. Int J Antimicrob Agents 2011; 38: 296-300.
521. Adembri C, Fallani S, Cassetta MI, Arrigucci S, Ottaviano A, Pecile P, Mazzei T, De
Gaudio R, Novelli A. Linezolid pharmacokinetic/pharmacodynamic profile in critically ill
septic patients: intermittent versus continuous infusion. Int J Antimicrob Agents 2008; 31:
122-9.
522. Cattaneo D, Orlando G, Cozzi V, Cordier L, Baldelli S, Merli S, Fucile S, Gulisano C,
Rizzardini G, Clementi E. Linezolid plasma concentrations and occurrence of drug-related
haematological toxicity in patients with gram-positive infections. Int J Antimicrob Agents
2013; 41: 586-9.
523. Livermore DM. Linezolid in vitro: mechanism and antibacterial spectrum. J Antimicrob
Chemother 2003; 51 Suppl 2: ii9-16.
524. Sanchez Garcia M, De la Torre MA, Morales G, Pelaez B, Tolon MJ, Domingo S, Candel
FJ, Andrade R, Arribi A, Garcia N, Martinez Sagasti F, Fereres J, Picazo J. Clinical
outbreak of linezolid-resistant Staphylococcus aureus in an intensive care unit. JAMA 2010;
303: 2260-4.
525. Hentschke M, Saager B, Horstkotte MA, Scherpe S, Wolters M, Kabisch H, Grosse R,
Heisig P, Aepfelbacher M, Rohde H. Emergence of linezolid resistance in a methicillin
resistant Staphylococcus aureus strain. Infection 2008; 36: 85-7.
526. Pai MP, Rodvold KA, Schreckenberger PC, Gonzales RD, Petrolatti JM, Quinn JP. Risk
factors associated with the development of infection with linezolid- and vancomycin-
resistant Enterococcus faecium. Clin Infect Dis 2002; 35: 1269-72.
527. Wunderink RG, Niederman MS, Kollef MH, Shorr AF, Kunkel MJ, Baruch A, McGee WT,
Reisman A, Chastre J. Linezolid in methicillin-resistant Staphylococcus aureus nosocomial
pneumonia: a randomized, controlled study. Clin Infect Dis 2012; 54: 621-9.
242
528. Herrmann DJ, Peppard WJ, Ledeboer NA, Theesfeld ML, Weigelt JA, Buechel BJ.
Linezolid for the treatment of drug-resistant infections. Expert Rev Anti Infect Ther 2008; 6:
825-48.
529. Dandekar PK, Tessier PR, Williams P, Zhang C, Nightingale CH, Nicolau DP.
Determination of the pharmacodynamic profile of daptomycin against Streptococcus
pneumoniae isolates with varying susceptibility to penicillin in a murine thigh infection
model. Chemotherapy 2004; 50: 11-6.
530. Louie A, Kaw P, Liu W, Jumbe N, Miller MH, Drusano GL. Pharmacodynamics of
daptomycin in a murine thigh model of Staphylococcus aureus infection. Antimicrob Agents
Chemother 2001; 45: 845-51.
531. Dvorchik BH, Brazier D, DeBruin MF, Arbeit RD. Daptomycin pharmacokinetics and
safety following administration of escalating doses once daily to healthy subjects.
Antimicrob Agents Chemother 2003; 47: 1318-23.
532. Woodworth JR, Nyhart EH, Jr., Brier GL, Wolny JD, Black HR. Single-dose
pharmacokinetics and antibacterial activity of daptomycin, a new lipopeptide antibiotic, in
healthy volunteers. Antimicrob Agents Chemother 1992; 36: 318-25.
533. Gould IM, David MZ, Esposito S, Garau J, Lina G, Mazzei T, Peters G. New insights into
meticillin-resistant Staphylococcus aureus (MRSA) pathogenesis, treatment and resistance.
Int J Antimicrob Agents 2012; 39: 96-104.
534. Fowler VG, Jr., Boucher HW, Corey GR, Abrutyn E, Karchmer AW, Rupp ME, Levine DP,
Chambers HF, Tally FP, Vigliani GA, Cabell CH, Link AS, DeMeyer I, Filler SG, Zervos
M, Cook P, Parsonnet J, Bernstein JM, Price CS, Forrest GN, Fatkenheuer G, Gareca M,
Rehm SJ, Brodt HR, Tice A, Cosgrove SE. Daptomycin versus standard therapy for
bacteremia and endocarditis caused by Staphylococcus aureus. N Engl J Med 2006; 355:
653-65.
535. Liu C, Bayer A, Cosgrove SE, Daum RS, Fridkin SK, Gorwitz RJ, Kaplan SL, Karchmer
AW, Levine DP, Murray BE, M JR, Talan DA, Chambers HF. Clinical practice guidelines
by the infectious diseases society of america for the treatment of methicillin-resistant
Staphylococcus aureus infections in adults and children. Clin Infect Dis 2011; 52: e18-55.
536. Moise PA, Hershberger E, Amodio-Groton MI, Lamp KC. Safety and clinical outcomes
when utilizing high-dose (> or =8 mg/kg) daptomycin therapy. Ann Pharmacother 2009; 43:
1211-9.
537. Bassetti M, Nicco E, Ginocchio F, Ansaldi F, de Florentiis D, Viscoli C. High-dose
daptomycin in documented Staphylococcus aureus infections. Int J Antimicrob Agents
2010; 36: 459-61.
243
538. Figueroa DA, Mangini E, Amodio-Groton M, Vardianos B, Melchert A, Fana C, Wehbeh
W, Urban CM, Segal-Maurer S. Safety of high-dose intravenous daptomycin treatment:
three-year cumulative experience in a clinical program. Clin Infect Dis 2009; 49: 177-80.
539. Falagas ME, Maraki S, Karageorgopoulos DE, Kastoris AC, Mavromanolakis E, Samonis
G. Antimicrobial susceptibility of multidrug-resistant (MDR) and extensively drug-resistant
(XDR) Enterobacteriaceae isolates to fosfomycin. Int J Antimicrob Agents 2010; 35: 240-3.
540. Patel SS, Balfour JA, Bryson HM. Fosfomycin tromethamine. A review of its antibacterial
activity, pharmacokinetic properties and therapeutic efficacy as a single-dose oral treatment
for acute uncomplicated lower urinary tract infections. Drugs 1997; 53: 637-56.
541. Dinh A, Salomon J, Bru JP, Bernard L. Fosfomycin: efficacy against infections caused by
multidrug-resistant bacteria. Scand J Infect Dis 2012; 44: 182-9.
542. Thauvin C, Lemeland JF, Humbert G, Fillastre JP. Efficacy of pefloxacin-fosfomycin in
experimental endocarditis caused by methicillin-resistant Staphylococcus aureus.
Antimicrob Agents Chemother 1988; 32: 919-21.
543. Komatsuzawa H, Suzuki J, Sugai M, Miyake Y, Suginaka H. Effect of combination of
oxacillin and non-beta-lactam antibiotics on methicillin-resistant Staphylococcus aureus. J
Antimicrob Chemother 1994; 33: 1155-63.
544. Portier H, Kazmierczak A, Lucht F, Tremeaux JC, Chavanet P, Duez JM. Cefotaxime in
combination with other antibiotics for the treatment of severe methicillin-resistant
staphylococcal infections. Infection 1985; 13 Suppl 1: S123-8.
545. Sahuquillo Arce JM, Colombo Gainza E, Gil Brusola A, Ortiz Estevez R, Canton E,
Gobernado M. In vitro activity of linezolid in combination with doxycycline, fosfomycin,
levofloxacin, rifampicin and vancomycin against methicillin-susceptible Staphylococcus
aureus. Rev Esp Quimioter 2006; 19: 252-7.
546. Ferrara A, Dos Santos C, Cimbro M, Gialdroni Grassi G. Effect of different combinations of
sparfloxacin, oxacillin, and fosfomycin against methicillin-resistant staphylococci. Eur J
Clin Microbiol Infect Dis 1997; 16: 535-7.
547. Okazaki M, Suzuki K, Asano N, Araki K, Shukuya N, Egami T, Higurashi Y, Morita K,
Uchimura H, Watanabe T. Effectiveness of fosfomycin combined with other antimicrobial
agents against multidrug-resistant Pseudomonas aeruginosa isolates using the efficacy time
index assay. J Infect Chemother 2002; 8: 37-42.
548. Hayami H, Goto T, Kawahara M, Ohi Y. Activities of beta-lactams, fluoroquinolones,
amikacin and fosfomycin alone and in combination against Pseudomonas aeruginosa
isolated from complicated urinary tract infections. J Infect Chemother 1999; 5: 130-38.
244
549. Reguera JA, Baquero F, Berenguer J, Martinez-Ferrer M, Martinez JL. Beta-lactam-
fosfomycin antagonism involving modification of penicillin-binding protein 3 in
Pseudomonas aeruginosa. Antimicrob Agents Chemother 1990; 34: 2093-6.
550. Michalopoulos A, Virtzili S, Rafailidis P, Chalevelakis G, Damala M, Falagas ME.
Intravenous fosfomycin for the treatment of nosocomial infections caused by carbapenem-
resistant Klebsiella pneumoniae in critically ill patients: a prospective evaluation. Clin
Microbiol Infect 2010; 16: 184-6.
551. Li J, Turnidge J, Milne R, Nation RL, Coulthard K. In vitro pharmacodynamic properties of
colistin and colistin methanesulfonate against Pseudomonas aeruginosa isolates from
patients with cystic fibrosis. Antimicrob Agents Chemother 2001; 45: 781-5.
552. Dudhani RV, Turnidge JD, Coulthard K, Milne RW, Rayner CR, Li J, Nation RL.
Elucidation of the pharmacokinetic/pharmacodynamic determinant of colistin activity
against Pseudomonas aeruginosa in murine thigh and lung infection models. Antimicrob
Agents Chemother 2010; 54: 1117-24.
553. Dudhani RV, Turnidge JD, Nation RL, Li J. fAUC/MIC is the most predictive
pharmacokinetic/pharmacodynamic index of colistin against Acinetobacter baumannii in
murine thigh and lung infection models. J Antimicrob Chemother 2010; 65: 1984-90.
554. Hawley JS, Murray CK, Jorgensen JH. Colistin heteroresistance in acinetobacter and its
association with previous colistin therapy. Antimicrob Agents Chemother 2008; 52: 351-2.
555. Poudyal A, Howden BP, Bell JM, Gao W, Owen RJ, Turnidge JD, Nation RL, Li J. In vitro
pharmacodynamics of colistin against multidrug-resistant Klebsiella pneumoniae. J
Antimicrob Chemother 2008; 62: 1311-8.
556. Bergen PJ, Forrest A, Bulitta JB, Tsuji BT, Sidjabat HE, Paterson DL, Li J, Nation RL.
Clinically relevant plasma concentrations of colistin in combination with imipenem enhance
pharmacodynamic activity against multidrug-resistant Pseudomonas aeruginosa at multiple
inocula. Antimicrob Agents Chemother 2011; 55: 5134-42.
557. Bergen PJ, Li J, Nation RL, Turnidge JD, Coulthard K, Milne RW. Comparison of once-,
twice- and thrice-daily dosing of colistin on antibacterial effect and emergence of resistance:
studies with Pseudomonas aeruginosa in an in vitro pharmacodynamic model. J Antimicrob
Chemother 2008; 61: 636-42.
558. Tan CH, Li J, Nation RL. Activity of colistin against heteroresistant Acinetobacter
baumannii and emergence of resistance in an in vitro pharmacokinetic/pharmacodynamic
model. Antimicrob Agents Chemother 2007; 51: 3413-5.
559. Garonzik SM, Li J, Thamlikitkul V, Paterson DL, Shoham S, Jacob J, Silveira FP, Forrest
A, Nation RL. Population pharmacokinetics of colistin methanesulfonate and formed
245
colistin in critically ill patients from a multicenter study provide dosing suggestions for
various categories of patients. Antimicrob Agents Chemother 2011; 55: 3284-94.
560. Marchand S, Frat JP, Petitpas F, Lemaitre F, Gobin P, Robert R, Mimoz O, Couet W.
Removal of colistin during intermittent haemodialysis in two critically ill patients. J
Antimicrob Chemother 2010; 65: 1836-7.
561. Plachouras D, Karvanen M, Friberg LE, Papadomichelakis E, Antoniadou A, Tsangaris I,
Karaiskos I, Poulakou G, Kontopidou F, Armaganidis A, Cars O, Giamarellou H.
Population pharmacokinetic analysis of colistin methanesulfonate and colistin after
intravenous administration in critically ill patients with infections caused by gram-negative
bacteria. Antimicrob Agents Chemother 2009; 53: 3430-6.
562. Dalfino L, Puntillo F, Mosca A, Monno R, Spada ML, Coppolecchia S, Miragliotta G,
Bruno F, Brienza N. High-dose, extended-interval colistin administration in critically ill
patients: is this the right dosing strategy? A preliminary study. Clin Infect Dis 2012; 54:
1720-6.
563. Karvanen M, Plachouras D, Friberg LE, Paramythiotou E, Papadomichelakis E, Karaiskos I,
Tsangaris I, Armaganidis A, Cars O, Giamarellou H. Colistin methanesulfonate and colistin
pharmacokinetics in critically ill patients receiving continuous venovenous
hemodiafiltration. Antimicrob Agents Chemother 2013; 57: 668-71.
564. Markou N, Fousteri M, Markantonis SL, Zidianakis B, Hroni D, Boutzouka E, Baltopoulos
G. Colistin pharmacokinetics in intensive care unit patients on continuous venovenous
haemodiafiltration: an observational study. J Antimicrob Chemother 2012; 67: 2459-62.
565. Matthaiou DK, Michalopoulos A, Rafailidis PI, Karageorgopoulos DE, Papaioannou V,
Ntani G, Samonis G, Falagas ME. Risk factors associated with the isolation of colistin-
resistant gram-negative bacteria: a matched case-control study. Crit Care Med 2008; 36:
807-11.
566. Mentzelopoulos SD, Pratikaki M, Platsouka E, Kraniotaki H, Zervakis D, Koutsoukou A,
Nanas S, Paniara O, Roussos C, Giamarellos-Bourboulis E, Routsi C, Zakynthinos SG.
Prolonged use of carbapenems and colistin predisposes to ventilator-associated pneumonia
by pandrug-resistant Pseudomonas aeruginosa. Intensive Care Med 2007; 33: 1524-32.
567. Martinez JA, Cobos-Trigueros N, Soriano A, Almela M, Ortega M, Marco F, Pitart C,
Sterzik H, Lopez J, Mensa J. Influence of empiric therapy with a beta-lactam alone or
combined with an aminoglycoside on prognosis of bacteremia due to gram-negative
microorganisms. Antimicrob Agents Chemother 2010; 54: 3590-6.
568. Kumar A, Zarychanski R, Light B, Parrillo J, Maki D, Simon D, Laporta D, Lapinsky S,
Ellis P, Mirzanejad Y, Martinka G, Keenan S, Wood G, Arabi Y, Feinstein D, Kumar A,
246
Dodek P, Kravetsky L, Doucette S. Early combination antibiotic therapy yields improved
survival compared with monotherapy in septic shock: a propensity-matched analysis. Crit
Care Med 2010; 38: 1773-85.
569. Kumar A, Safdar N, Kethireddy S, Chateau D. A survival benefit of combination antibiotic
therapy for serious infections associated with sepsis and septic shock is contingent only on
the risk of death: a meta-analytic/meta-regression study. Crit Care Med 2010; 38: 1651-64.
570. Chamot E, Boffi El Amari E, Rohner P, Van Delden C. Effectiveness of combination
antimicrobial therapy for Pseudomonas aeruginosa bacteremia. Antimicrob Agents
Chemother 2003; 47: 2756-64.
571. Cosgrove SE, Vigliani GA, Fowler VG, Jr., Abrutyn E, Corey GR, Levine DP, Rupp ME,
Chambers HF, Karchmer AW, Boucher HW. Initial low-dose gentamicin for
Staphylococcus aureus bacteremia and endocarditis is nephrotoxic. Clin Infect Dis 2009; 48:
713-21.
572. Riedel DJ, Weekes E, Forrest GN. Addition of rifampin to standard therapy for treatment of
native valve infective endocarditis caused by Staphylococcus aureus. Antimicrob Agents
Chemother 2008; 52: 2463-7.
573. Falagas ME, Matthaiou DK, Bliziotis IA. The role of aminoglycosides in combination with
a beta-lactam for the treatment of bacterial endocarditis: a meta-analysis of comparative
trials. J Antimicrob Chemother 2006; 57: 639-47.
574. Vardakas KZ, Tansarli GS, Bliziotis IA, Falagas ME. beta-Lactam plus aminoglycoside or
fluoroquinolone combination versus beta-lactam monotherapy for Pseudomonas aeruginosa
infections: a meta-analysis. Int J Antimicrob Agents 2013; 41: 301-10.
575. Pena C, Suarez C, Ocampo-Sosa A, Murillas J, Almirante B, Pomar V, Aguilar M,
Granados A, Calbo E, Rodriguez-Bano J, Rodriguez F, Tubau F, Oliver A, Martinez-
Martinez L. Effect of adequate single-drug vs combination antimicrobial therapy on
mortality in Pseudomonas aeruginosa bloodstream infections: a post Hoc analysis of a
prospective cohort. Clin Infect Dis 2013; 57: 208-16.
576. Marcus R, Paul M, Elphick H, Leibovici L. Clinical implications of beta-lactam-
aminoglycoside synergism: systematic review of randomised trials. Int J Antimicrob Agents
2011; 37: 491-503.
577. Louie A, Grasso C, Bahniuk N, Van Scoy B, Brown DL, Kulawy R, Drusano GL. The
combination of meropenem and levofloxacin is synergistic with respect to both
Pseudomonas aeruginosa kill rate and resistance suppression. Antimicrob Agents
Chemother 2010; 54: 2646-54.
247
578. den Hollander JG, Horrevorts AM, van Goor ML, Verbrugh HA, Mouton JW. Synergism
between tobramycin and ceftazidime against a resistant Pseudomonas aeruginosa strain,
tested in an in vitro pharmacokinetic model. Antimicrob Agents Chemother 1997; 41: 95-
100.
579. Mouton JW, van Ogtrop ML, Andes D, Craig WA. Use of pharmacodynamic indices to
predict efficacy of combination therapy in vivo. Antimicrob Agents Chemother 1999; 43:
2473-8.
580. Zavascki AP, Bulitta JB, Landersdorfer CB. Combination therapy for carbapenem-resistant
Gram-negative bacteria. Expert Rev Anti Infect Ther 2013; 11: 1333-53.
581. Epstein BJ, Gums JG, Drlica K. The changing face of antibiotic prescribing: the mutant
selection window. Ann Pharmacother 2004; 38: 1675-82.
582. Zhanel GG, Mayer M, Laing N, Adam HJ. Mutant prevention concentrations of levofloxacin
alone and in combination with azithromycin, ceftazidime, colistin (Polymyxin E),
meropenem, piperacillin-tazobactam, and tobramycin against Pseudomonas aeruginosa.
Antimicrob Agents Chemother 2006; 50: 2228-30.
583. Lister PD, Wolter DJ. Levofloxacin-imipenem combination prevents the emergence of
resistance among clinical isolates of Pseudomonas aeruginosa. Clin Infect Dis 2005; 40
Suppl 2: S105-14.
584. Firsov AA, Vostrov SN, Lubenko IY, Portnoy YA, Zinner SH. Prevention of the selection
of resistant Staphylococcus aureus by moxifloxacin plus doxycycline in an in vitro dynamic
model: an additive effect of the combination. Int J Antimicrob Agents 2004; 23: 451-6.
585. Drusano GL, Liu W, Fregeau C, Kulawy R, Louie A. Differing effects of combination
chemotherapy with meropenem and tobramycin on cell kill and suppression of resistance of
wild-type Pseudomonas aeruginosa PAO1 and its isogenic MexAB efflux pump-
overexpressed mutant. Antimicrob Agents Chemother 2009; 53: 2266-73.
586. Mendes RE, Fritsche TR, Sader HS, Jones RN. Increased antimicrobial susceptibility
profiles among polymyxin-resistant Acinetobacter baumannii clinical isolates. Clin Infect
Dis 2008; 46: 1324-6.
587. Mantzarlis K, Makris D, Manoulakas E, Karvouniaris M, Zakynthinos E. Risk factors for
the first episode of Klebsiella pneumoniae resistant to carbapenems infection in critically ill
patients: a prospective study. Biomed Res Int 2013; 2013: 850547.
588. Micek ST, Ward S, Fraser VJ, Kollef MH. A randomized controlled trial of an antibiotic
discontinuation policy for clinically suspected ventilator-associated pneumonia. Chest 2004;
125: 1791-9.
248
589. Chastre J, Wolff M, Fagon JY, Chevret S, Thomas F, Wermert D, Clementi E, Gonzalez J,
Jusserand D, Asfar P, Perrin D, Fieux F, Aubas S. Comparison of 8 vs 15 days of antibiotic
therapy for ventilator-associated pneumonia in adults: a randomized trial. JAMA 2003; 290:
2588-98.
590. Singh N, Rogers P, Atwood CW, Wagener MM, Yu VL. Short-course empiric antibiotic
therapy for patients with pulmonary infiltrates in the intensive care unit. A proposed solution
for indiscriminate antibiotic prescription. Am J Respir Crit Care Med 2000; 162: 505-11.
591. Taccone FS, Laterre PF, Spapen H, Dugernier T, Delattre I, Layeux B, De Backer D,
Wittebole X, Wallemacq P, Vincent JL, Jacobs F. Revisiting the loading dose of amikacin
for patients with severe sepsis and septic shock. Crit Care 2010; 14: R53.
592. Rea RS, Capitano B, Bies R, Bigos KL, Smith R, Lee H. Suboptimal aminoglycoside dosing
in critically ill patients. Ther Drug Monit 2008; 30: 674-81.
593. Tsuji BT, Brown T, Parasrampuria R, Brazeau DA, Forrest A, Kelchlin PA, Holden PN,
Peloquin CA, Hanna D, Bulitta JB. Front-loaded linezolid regimens result in increased
killing and suppression of the accessory gene regulator system of Staphylococcus aureus.
Antimicrob Agents Chemother 2012; 56: 3712-9.