Protocol for Systematic Review

Title

The prevalence of antimicrobial resistance in the most common bacteria* causing upper

respiratory tract bacterial infections (URTBI) in GCC** and MENAP *** countries. A

systematic review.

* Streptococcus Pneumoniae, Streptococcus Pyogenes, H Influenzae and Moraxella Catarrhalis **GCC – Gulf Cooperation Council that includes Bahrain, Kuwait, Oman, Qatar, United Arab Emirates, Saudi Arabia *** MENAP countries include Turkey, Pakistan, Afghanistan, Algeria, Djibouti, Morocco, Egypt, Syria, Iran, Iraq, Tunisia, Palestine, West Bank and Gaza, Lebanon, Jordan and Yemen along with GCC Countries* (IMF International Monetray Fund 2015).

Introduction

Acquisition of antimicrobial resistance (AMR) to antimicrobials is a natural phenomenon

that happens when a bacterial gene mutates during mitosis or resistant traits are

exchanged amongst microbes (WHO World Health Organisation 2015). The emergence

of resistance against antibiotics is related to use of antibiotics use with greater use leading

to increased resistance while reduction in use of antibiotics leading to a decline in

resistance levels (Austin et al. 1999). The antimicrobial resistance poses a great threat to

communities globally (Song et al. 2004; Davies & Verde 2013). Even in the western

countries where very few medications are available over the counter and antibiotics are

only available with a prescription, AMR is increasing. The situation is only expected

worsen in countries and regions where medication control policies are not fully

implemented and pharmacies dispense antibiotics without a prescription (Levy 1998).

Antibiotics are misused all over world over (World Health Organization 2014). The

MENAP region is no exception; a cross-sectional survey in Bahrain revealed excessive

use of antibiotics in the children for upper respiratory tract infection (URTI) (Senok et al.

2009). The use of antibiotics is related to development of bacterial resistance (Costelloe

et al. 2010).

Some upper respiratory tract infections (URTI) will need antibiotic treatment (Bisno et

al. 2002). Knowing the prevalence of resistance among the common bacteria is

important, as this knowledge not only helps physicians prescribe antibiotics

appropriately, it also reduces the risk of therapy failure.

More than half a billion people live in the Middle East, North Africa, Afghanistan and

Pakistan. This region is classed as developing and comprises of variety of economies

including some unstable countries like Iraq, Syria and Libya to very stable countries like

oil rich Gulf Cooperative Council countries and Iran (IMF International Monetray Fund

2015).

The 2014 WHO annual AMR surveillance report mentions that many countries in the

region do not have comprehensive national surveillance data available. Some countries

did not have any data available. In those for whom data were available it showed

alarming levels of AMR (World Health Organization 2014).

The need for a systematic review of prevalence of AMR in common pathogens

causing URTBI

The majority of the population will suffer an acute respiratory tract infection (ARTI)

each year. ARTIs are considered to be main reason why people visit their family

physicians. The common cold is the most frequent ARTI (NHS 2015). Up to 77% of

these colds are viral induced (Harnden et al. 2007) and would not require antibiotic

treatment (NHS 2015). Some these infections will be accompanied by secondary bacterial

infection (Bisno et al. 2002). It has been advised in past to use antibiotics as first line

antibiotics for suspected bacterial infection. This advice was deemed appropriate if there

is high incidence of complications after bacterial infection. As several studies have

suggested, this has not been the case, this approach is no longer justified (NICE

2008). Several current systematic reviews and overviews of systematic reviews point to

lack of benefit of antibiotics as first line therapy for URTI (Arroll 2005). The guidelines

recommend the use of antibiotics in certain circumstances; for example, NICE (National

Institute of Clinical Excellence United Kingdom) 2008 guidelines for URTI advise to use

antibiotics for high-risk patients and in those patients who deteriorated after initial

improvement. Antibiotics guidelines suggest the use of empirical antibiotics as first line

till culture sensitivity results are available. The choice of these empirical antibiotics

depends upon the prevalence of resistance and sensitivities among common bacteria

against different antibiotics in respective area. It is advised that each area should follow

their local antibiotic sensitivity and resistance prevalence to decide which antibiotic

should be used as first line empirical antibiotic.

The WHO report mentions lack of available data and surveillance in many of the

countries in MENAP. Therefore, it is important for clinicians to know the levels of

antimicrobial resistance to different antibiotics, especially for first line antibiotics, in

order to minimise the risk of therapy failure (World Health Organization 2014).

Globally, the commonest causes of URTBI are Streptococcus Pneumoniae

(Pneumococcus), Haemophilus Influenzae, Moraxella Catarrhalis (Kronman et al. 2014).

Review by Hausdorff et al. 2007 found limited evidence in two countries in MENAP

region that indicated that most common bacteria causing acute otitis media are

Streptococcus Pneumoniae , Haemophilus Influenzae, Moraxella Catarrhalis .It is well

known that humans, especially children, carry these bacteria as commensals in the URT

as commensals especially in children. These bacteria do not always cause problems

progress to overt infections. The mechanism of disease causation by these bacteria is

complex and involves an imbalance in the healthy balance among commensals and

pathogenic organisms. Subsequently, imbalances in the ecosystem may result in

overgrowth and invasion by bacterial pathogens, causing respiratory or invasive diseases,

especially in children with an immature immune system (Bosch et al. 2013).

Otitis Media

Bacterial pathogens causing Otitis Media are different in different age groups. In older

infants and children (< younger than 14 years old)r, the most frequently encountered

bacterial pathogens are Streptococcus pneumoniae, Moraxella (Branhamella) catarrhalis,

and non-typeable Haemophilus Influenzae; less commonly found bacteria are group A –

beta haemolytic streptococci and S. Aureus. In patients > older than 14 years, S.

pneumoniae, group A- beta haemolytic streptococci, and S. Aureus are commonest and,

H. Influenzae follows these in terms frequency of prevalence (Vergison 2008; Fried

2016).

Sinusitis;

Though acute sinusitis is almost always caused by viruses in otherwise well population of

healthy individuals. A small proportion will go on to develop secondary bacterial

infection. The causative organisms in these are Streptococci, Pneumococci, Haemophilus

Influenzae, Moraxella Catarrhalis, or Staphylococcus (Poole 2004; Fried 2013).

Tonsillo-pharyngitis;

Tonsillo-pharyngitis is also usually viral in aetiology but in about one third (30%) of the

affected patients individuals, it is bacterial in nature. The bacterial organism causing the

infection this are Group A-Beta haemolytic streptococcus (GABHS) is most common

(Zoorob et al. 2012; Sasaki 2014), but Staphylococcus Aureus, Streptococcus

pneumoniae, Mycoplasma pneumoniae, and Chlamydia pneumoniae are sometimes

involved (Sasaki 2014).

Current State of Knowledge

The level of AMR in the bacteria is increasing globally (World Health Organization 2014;

Davies & Verde 2013; Jones et al. 2010; Klugman 1990; Mlynarczyk et al. 2001). AMR

levels in different bacteria vary from place to place and in some places it is reaching very

high levels. WHO 2014 annual AMR surveillance report cited that in some areas 50% of

streptococci are resistant to first line antibiotics.

The MENAP region is no exception to this trend. In 2007 The Middle East and North

African (MENA) Vaccine- Preventable Diseases Regional Advisory Group which was

formed in 2003 by local experts in vaccine-preventable diseases, as a new Public–Private

partnership published a review based on published and unpublished reports. The review

(Hausdorff et al. 2007) examined the epidemiology of invasive disease caused by

Streptococcus, Haemophilus Influenzae and Meningococcus. The reviewers also

included data on non-invasive disease caused by these bacteria where it was available.

Paucity of data was apparent almost all around the region. Even in the countries where

data was collected, there was lack of standardisation in the data collection methods and

deficiency of uniform case definitions.

This review was limited as it only used one electronic database (Medline.), as authors may

have possibly missed some published studies (Wong et al. 2006). The review also greatly

relied on personal communications provided to the authors but with no specific details

of the sources or information about data verification were provided. The reviewers

concluded that levels of AMR were relatively high in many countries in the region,

although this statement was not qualified with any comparative data. This review despite

its limitations provided much needed base-line data for the region. It's been nine years

since the publication of this review. Therefore it would be imperative to have an up to

date systematic review on this topic.

Protocol

Systematic review objectives

Primary objective

● To estimate the prevalence of resistance in the most common bacteria

causing three common upper respiratory tract bacterial infections.

Secondary objectives

● To gain estimates of the magnitude of AMR in the region

● To ascertain temporal trends in AMR in the region

Methods

Types of studies

Even though systematic reviews of randomised trials provide the best evidence for

therapy. Highest level of evidence for the prevalence of any condition generally comes

from current local random sample surveys. In terms of hierarchy of evidence these

surveys are followed by systematic review of the surveys that allow for local matching.

These are followed by local non-random sample. Lowest level of evidence comes from

case series

As this review is mainly at aimed finding out the prevalence of the AMR in the bacteria

causing URTBI. It was decided to include the studies relevant to prevalence question, as

described by the Oxford Centre for Evidence Based Medicine levels of evidence (Table

1) (OCEBM Levels of Evidence Working Group* 2011). The studies suggested include

local and current random sample surveys (level 1), then systematic review of samples

which allow for local matching (level 2), then local non-random sample (level 3) and

finally case series (level 4). Antibiograms were added to the list at level 3 as these are

non-random samples.

Table 1 – (Adapted from OCEMB levels of Evidence)

Step 1

(level 1)*

Step 2

(level 2)*

Step 3

(level 3)*

Step 4

(level 4)*

Step 5

(level 5)

How

common

is the

problem

Local

current and

random

surveys

(censuses)

Systematic

review of

surveys that

allow matching

to local

circumstances*

*

1)Local non-

random

sample**

2)Antibiograms

from local

microbiology service

and hospitals (

Added)

Case-

series**

n/a

* Level may be graded down on the basis of study quality, imprecision, indirectness (study PICO does not match

questions PICO), because of inconsistency between studies, or because the absolute effect size is very small; Level may be

graded up if there is a large or very large effect size

** As always, a systematic review is generally better than an individual study.

Antibiograms

AMR Monitoring is generally performed in health care facilities using an annual

summary of susceptibility rates, among commonly isolated bacteria sent to microbiology

services, known as a cumulative antibiogram report (Hindler & Stelling 2007).

Antibiograms are readily available sources and data; these data provide information about

antibiotic resistance in bacteria in the local area. Antibiograms are mainly used to inform

institutional empirical antibiotic prescribing in institutions (Pakyz 2007; Lakshmi 2008;

Joshi 2010). If data were collected duly and continuously, these data can detect changes

in antimicrobial resistance over time along with guiding empirical therapy decisions

(Halstead et al. 2004). One can argue that they do fall in the local non random sample

which is level 3, but if enough data is available from multiple sources i.e. more than one

hospital in the region, then doing a systematic review of these antibiogram might provide

us with level 2 evidence for the AMR prevalence.

List of different types studies and reports to be included

o Local and current random sample surveys (or censuses) (level 1)

o Systematic review of surveys which allow for local matching (level 2)

o Systematic reviews of antibiograms (level 2)

o Local non-random sample (Level 3)

o Antibiograms from local pathology services in the included countries

(level 3)

o Case series (level 4)

Population

We will not limit the searches by age and will include all age groups.

We will not exclude inpatient or outpatient population.

Types of bacteria to be included in this study

As mentioned above in introduction the bacteria selected for study are

1. Streptococcus

2. H Influenzae

3. M Catarrhalis

Defining the URT bacterial infection

For the purposes of the review it was decided to limit the URTBI to include bacterial

infections of throat, nose and ears these include tonsillo-pharyngitis, rhino-sinusitis and

otitis media.

NHS UK describes URTBI as “a bacterial infection of the upper respiratory tract that

includes nose, sinuses and throat” (NHS 2015). This description excludes larynx and

trachea, which are included in description, used by PubMed (US National Library of

Health 2016). Laryngitis is rarely bacterial (Sasaki 2016) and bacterial tracheitis is

generally uncommon. Bacterial tracheitis is caused by both Streptococcus and

Staphylococcus Aureus and empirical prescribing is advised to cover both of these

(Mcbride 2013).

Naso-pharyngitis, pharyngitis, tonsillitis and otitis media account for 87.5% of all

respiratory infections (Jain et al. 2001). The current review is aimed at gathering data in

order to aid in development of empirical antibiotic prescribing guidelines for primary

care physicians treating URTBI. Hence it was decided to limit the scope of this review to

more prevalent bacterial infections of Nose, throat and sinuses.

Selection of bacteria to examine for systematic review

It was decided to keep the search limited to four bacteria (as described in the

introduction) as these are most prevalent pathogens in URTBI collectively. It is advised

that first line antibiotics should cover these Streptococcus Pneumoniae, Haemophilus Influenzae,

Moraxella catarrhalis in both rhino-sinusitis and acute otitis media and Group A beta

haemolytic streptococcus in tonsillo-pharyngitis (Zoorob et al. 2012).

All of the above bacteria are also found as commensals in population. Separating the

normal URT flora from the pathogenic bacteria grown in culture is a debated subject.

Some experts argue that many of the isolates grown from swabs and samples taken from

URT may not be showing pathogenic bacteria. One of the suggested methods of

associating pathology with bacteria is finding of purulence in the smear and finding

bacteria on gram staining and then confirming by culture. This technique has shown that

not all isolated bacteria have associated polymorph infiltration (Konno et al. 2006).

Streptococcus, H Influenzae and Moraxella Catarrhalis all demonstrated associated

polymorph infiltration while viruses, Staphylococcus Aureus and mixed growth cultures

failed show this association (Jousimies-Somer et al. 1988; Heald et al. 1993).

Geographical area:

GCC Countries and MENAP as per World Bank description (IMF International

Monetray Fund 2015).

Types of outcome measures

Primary

● Percentage of bacteria sensitive to commonly used antibiotics (e.g,. Amoxicillin,

Penicillin, Erythromycin, Tetracycline, 1st generation Cephalosporin and Co-

Amoxiclav.)

Secondary

● Percentage of bacteria sensitive to other antibiotics.

● Temporal trends in resistance patterns in different countries and regions

● We also collect information about any descriptive analysis, if available, within the

included studies on the barriers or facilitators to improving AMR in the region.

● To assess success or failure of antibiotics stewardship programs if information is

available in the included studies. Along with any descriptive information about

any barriers encountered in implementation of antibiotics stewardship programs.

Time

2006 onwards as antibiotics resistance changes over the time it was decided to use last 10

years data for analysis. We believe that 10 years data, if enough data is available, will

enable us to assess temporal trends in the AMR variation.

Exclusion Criteria

● Any report or study in which is data collection methods and population

characteristics are not reported.

● Report focusing only on highly resistant organisms (Hindler & Stelling 2007;

Pakyz 2007). Reports only focusing on highly resistant organism skew the overall

picture and may misrepresent the actual situation.

● Reports not reporting total number antibiotics tested and only reporting broad-

spectrum second line or reserve second-line testing panels (Hindler & Stelling

2007). If all tested antibiotics are not reported this will give wrong impression to

the physicians about actual resistance patterns in relevant bacteria.

● Reports not reporting the total number of isolates tested (Pakyz 2007)

● Any report with less than 30 isolates tested (Pakyz 2007; Hindler & Stelling

2007). As less than 30 isolates have limited statistical value and should be

interpreted with caution(Aberta Health Services 2009).

Data Search

Databases to be used

Medline ® 1996 to January, Embase 1996 to January 2016, Global Health 1973 to

January 2016.

Google and Google Scholar

Conference Abstracts –DARE

WHO – Database?

OpenGrey

Why use more than one database

It is estimated that if only one database is used there is chance that search will miss a

significant number of relevant articles. As it was found that there is only 30-50% overlap

between EMBASE and MEDLINE (Wong et al. 2006).

Non database search

1. Manual Search of the bibliographies of the included articles to find more articles

of interest

2. Authors names search (from included articles)

3. Local non-indexed journals

4. Request for articles from local experts for articles and reports of interest

5. Search for grey literature

We will contact all the local health authorities and request the data directly if any

surveillance data available.

We will first send letters by post and follow it up by email and if no response is

received in 4 weeks we will contact the concerned department or institute by

phone.

We will wait for 2 months if no response is received we will send a reminder by

post and email and contact again by phone after 4 weeks of letter.

6. Personal communications

We will also include the personal communications from experts working in the

region. These data will be assessed for quality using same criteria used for other

reports included in the review.

Screening of articles

Two authors will independently read the titles to screen the articles then second

screening will be done by reading the abstract.

Selection of article

Screened articles after second screening will be read full text to find if they fit inclusion

and exclusion criteria to select the articles for inclusion in the review.

Any conflicts will resolved by consensus if two authors are unable to reach the consensus

third author (S.T.) will make final decision after joint discussion with both authors.

Quality Assessment Review of Published Articles and Reports

Published reports

Quality assessment of the included studies and reports will be conducted using 10-point

quality appraisal for prevalence studies as proposed by Munn et al. (Munn et al. 2014).

This tool assesses both internal and external validity of the studies and reports. This 10-

point checklist assesses for following domains.

● Ensuring a representative sample.

● Ensuring appropriate recruitment.

● Ensuring an adequate sample size.

● Ensuring appropriate description and reporting of study subjects and setting.

● Ensuring data coverage of the identified sample is adequate.

● Ensuring the condition was measured reliably and objectively.

● Ensuring appropriate statistical analysis.

● Ensuring confounding factors/subgroups/differences are Identified and

accounted for.

Quality Assessment Review of Antibiograms

It is decided to use the standards as outlined by Clinical and Laboratory Standard

Institute and WHO (Pakyz 2007; World Health Organization 2011; Hindler & Stelling

2007). For a good and reliable antibiogram report there are some minimum standards,

which are to be adhered with. These include:

● Antibiograms should be produced annually. This ensures that physicians making

prescribing decision based on these reports are using up to date data.

● It has been suggested that if antibiogram contains data which report susceptibility

separately from different departments of hospital separately. Reporting this data

without separation may lead to over-estimation of antimicrobial resistance as

certain group of patients are more susceptible to certain infections and recurrent

infections and use of antibiotics in these groups generally leads to higher

incidence of resistant isolates e.g. cancer patients, patients admitted in ICU, cystic

fibrosis patients. It will also help in choosing more appropriate empiric therapy

for these special groups

● Inclusion of only the first isolate of a given species/patient /analysis period (e.g.,

year), irrespective of body site, antimicrobial susceptibility profile, or other

phenotypic characteristics in compilations of susceptibility data. Inclusion of

duplicate isolates in antibiogram report leads to skewing of results and report.

● Antibiogram should only include isolates if they are 30 or more. Small number

reporting leads to under or overestimation of resistance.

● Antibiograms should exclude surveillance cultures in susceptibility analyses.

● It is further advised that susceptibility results be reported for all antimicrobials

tested in accordance with CLSI guidelines for a given organism. Susceptibilities

for antimicrobials that are only tested on resistant isolates or on the basis of

clinician request should not be included

● Antibiograms should report the percentage of isolates that are susceptible versus

intermediate or resistant, documenting the inclusive dates of data collection,

noting and indicating the total number of isolates evaluated for susceptibility for

each organism tested.

● Antibiograms should contain separate tables for certain clinically relevant gram-

positive, gram-negative, and anaerobic organisms.

● All isolates stored should be analysed for the cumulative antimicrobial

susceptibility report. If only the isolates resistant to the primary agents were

analysed and reported, this would bias the secondary agents to higher levels of

resistance (Halstead et al. 2004).

● Step by step guide by WHO regional office, advises to express resistance rates as

incidence rates to express antimicrobial resistance instead of using the number of

isolates tested as denominators. This is imperative because the submission of

microbiology specimens to the laboratory is inconsistent and varies broadly. In

hospital settings, it is recommended to use the number of admissions and the

number of days of hospitalization, which are particularly useful for inter- or intra-

health-care facility comparison. It should be recognized that this process captures

data only from patients admitted to health facility and excludes those who attend

as outpatients.

Quality assessment of systematic reviews of the reports

It was decided to use AMSTAR (Shea et al. 2007) checklist to assess the quality of the

systematic reviews of surveys.

Quality assessment non-random sample reports

These non-random sample reports are similar to antibiograms. These surveys will be

assessed using the same standards, which were to be used for antibiograms quality

assessment as proposed by CLSI and WHO.

Quality assessment of case series

It was decided to use National Heart, Lung and Blood Institute’s quality assessment tool

for case series studies (NHLBI 2014) for assessment of case series as template. This tool

was modified to cater for antibiotic resistance and sensitivity case series (see appendix 1

for modified checklist.).

Flow Diagram for Review Selection and Reporting

Taken from Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. (Moher et al. 2009).

ArticlesandReportsincludedinFinalAnalysis

CharacteristicsofInculdedStudiesandReports CharacteristicsofExcludedStudiesandReports

FullTextArticlesandReportsreviewed

QualityAssessment

Noofarticlesfromallsources

TitleandAbstractScreening

Registration: PRISMA

The review protocol will be registered with PROSPERO.

Data collection/synthesis

Data collection form will be piloted on one study/report of each type.

The data collection will be done on data collection forms, which are to be stored

electronically with cloud storage backup.

Data will be collected as percentages of the sensitivities to different antibiotics.

Two authors will independently collect data and this data will be compared for the

accuracy after each cycle, which is decided to be two weeks.

We will also try collecting information about total number of isolates tested and number

of admissions number of days of hospitalization by contacting the relevant hospital and

health authorities.

Presentation and Collation of data

Data will be reported according to country and region and if possible different

population groups.

Tables will be produced for year on year resistance from each area and hospital if more

than one year's data available for different bacteria. e.g. Streptococcus Pneumoniae

sensitivity patterns taken from 4-year antibiogram (Aristo & Deshmukh 2014; Aristo et

al. 2013; Deshmukh & Sharabasi 2012; Deshmukh et al. 2011) data taken from central

Microbiology Service fro state of Qatar will be presented like this

We will produce tables describing populations from whom data was collected

We will also produce table describing the types of studies included and their quality

characteristics

We will collect all data then will perform data synthesis

We will do sensitivity analysis excluding data from low quality studies.

Collation of Data

We will use Cochrane-Armitage trend test which tests for trends in binomial proportions

across levels of an ordinal covariate, to evaluate temporal patterns in the data (Stein et al.

2003). A statistician’s help will be employed to do this test and collate data if it is possible

to collate it. Analysis will be done using IBM SPSS 22 software.

Institutional approval

Institutional approval has been applied for, it is verbally confirmed that it will be granted

at next research and IRB committee meeting.

Search Strategy

1. URTBI

(al l o f the fo l lowing search terms in this heading are to be combined with “OR”) 1.1. Common Cold 1.2. Cold 1.3. Sinusitis 1.4. Rhinosinusitis 1.5. Rhinitis 1.6. Tonsillitis 1.7. Tonsillopharyngitis 1.8. Rhinopharyngitis 1.9. Nasopharyngitis 1.10. Pharyngitis 1.11. Laryngitis 1.12. Sore throat 1.13. Otitis media 1.14. Middle Ear Infection 1.15. Mastoiditis 1.16. Strep throat 1.17. Streptococcal THROAT Infection 1.18. Scarlet fever

2. Bacteria

(al l o f the fo l lowing search terms in this heading are to be combined with “OR”)

2.1. Pneumococus 2.2. Streptococus) 2.3. H Influenzae or Haemophilus influenzae 2.4. Moraxella catarrhalis 2.5. Branhamella catarrhalis 2.6. Gram positive cocci 2.7. Group A Strep infections 2.8. Group A beta haemolytic streptococc$ 2.9. Group A beta hemolytic streptococc$ 2.10. Streptococcus Pyogenes 2.11. GABH [Group A beta hemolytic streptococcus???] 2.12. gabh (Group A beta hemolytic streptococcus) 2.13. Group A Streptococcal Disease

3. Antimicrobials

(al l o f the fo l lowing search terms in this heading are to be combined with “OR”) 3.1. antibiotic$ 3.2. antimicrobial$ 3.3. antibacterial$ 3.4. Beta-lactam$ 3.5. Tetracycline$ 3.6. Doxycycline 3.7. Cephalosporin 3.8. Cefalosporin 3.9. Penicillin$ 3.10. Phenoxymethylpenicillin 3.11. ampicillin$ 3.12. Amoxicillin$ 3.13. Amoxycillin$ 3.14. Macrolide$ 3.15. Azithromycin$ 3.16. Clarithromycin$ 3.17. Erythromycin$ 3.18. Roxithromycin 3.19. Lincomycin 3.20. Cefalexin 3.21. Cefaclor 3.22. cefadroxil 3.23. Cefdinir 3.24. cefditoren 3.25. Cefixime 3.26. Cefpodoxime 3.27. Cefprozil 3.28. ceftibuten 3.29. Ceftriaxone 3.30. Cefotaxime 3.31. Cefuroxime 3.32. Cephalexin 3.33. Doxycyclin$ 3.34. Co-amoxiclav 3.35. Clavulanic acid 3.36. Sulfonimide 3.37. Co-Trimoxazole 3.38. Septrin 3.39. Septran 3.40. aminoglycoside Doripenem 3.41. ertapenem 3.42. imipenem 3.43. meropenem 3.44. Quinolone$ 3.45. Ciprofloxacin 3.46. moxifloxacin 3.47. piperacillin

3.48. Ticarcillin

4. Region (al l o f the fo l lowing search terms in this heading are to be combined with “OR”)

4.1. Middle East 4.2. Middle East and North Africa 4.3. MENA 4.4. Arabian Gulf 4.5. Arabian Peninsula 4.6. Gulf Cooperation Council 4.7. GCC 4.8. Gulf 4.9. Qatar 4.10. Saudi$ 4.11. Saudi Arabia 4.12. Kuwait 4.13. UAE 4.14. United Arab Emirates 4.15. Oman 4.16. Bahrain 4.17. Turkey 4.18. Pakistan 4.19. Afghanistan 4.20. Algeria 4.21. Djibouti 4.22. Morocco 4.23. Egypt 4.24. Syria 4.25. Iran 4.26. Iraq 4.27. Tunisia 4.28. Palestine 4.29. West Bank and Gaza 4.30. Lebanon 4.31. Jordan 4.32. Yemen

5. Resistance (al l o f the fo l lowing search terms in this heading are to be combined with “OR”) 5.1. Resistance 5.2. Microbial resistance 5.3. Bacterial resistance 5.4. Antimicrobial resistance 5.5. Antibiotic Resistance 5.6. AMR (abbreviation for antimicrobial resistance) 5.7. ABR (abbreviation for antibacterial resistance)

6. Susceptibility or Sensitivity

7. Effectiveness

(al l o f the fo l lowing search terms in this heading are to be combined with “OR”) 7.1. efficacy 7.2. strength? 7.3. response 7.4. reactive 7.5. cure 7.6. remission 7.7. resolution 7.8. eradication 7.9. clearance

8. Antibiotic Failure

9. Combine 5 or 6 or 7 or 8

10. Combining 1 AND 2 AND 3 AND 4 AND 9

11. Limit 11 to 1.1.2006

Second Search for Published antibiograms

1. Antibiogram$

2. Region (al l o f the fo l lowing search terms in this heading are to be combined with “OR”)

2.1. Middle East 2.2. Middle East and North Africa 2.3. MENA 2.4. Arabian Gulf 2.5. Arabian Peninsula 2.6. Gulf Cooperation Council 2.7. GCC 2.8. Gulf 2.9. Qatar

2.10. Saudi$ 2.11. Saudi Arabia 2.12. Kuwait 2.13. UAE 2.14. United Arab Emirates 2.15. Oman

2.16. Bahrain 2.17. Turkey 2.18. Pakistan 2.19. Afghanistan 2.20. Algeria 2.21. Djibouti 2.22. Morocco 2.23. Egypt 2.24. Syria 2.25. Iran 2.26. Iraq 2.27. Tunisia 2.28. Palestine 2.29. West Bank and Gaza 2.30. Lebanon 2.31. Jordan 2.32. Yemen

3. 1 AND 2

4. Search limited to 1.1.2006 onwards

GlossaryARTI-AcuterespiratorytractinfectionURT-UpperrespiratorytractURTI–upperrespiratorytractinfectionURTBI-UpperrespiratorytractbacterialinfectionGCC – Gulf Co-operation Council that includes Bahrain, Kuwait, Oman, Qatar, United Arab Emirates, Saudi ArabiaMENA- Middle East and North AfricaMENAP -countries include Turkey, Pakistan, Afghanistan, Algeria, Djibouti, Morocco, Egypt, Syria, Iran, Iraq, Tunisia, Palestine, West Bank and Gaza, Lebanon, Jordan and Yemen along with GCC Countries.AMR-AntimicrobialresistanceWHO-WorldHealthOrganizationNice-Nationalinstituteofclinicalexcellence

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Appendix 1

NHLBI Quality Assessment Tool for

Case Series Studieshttp://www.nhlbi.nih.gov/health-pro/guidelines/in-develop/cardiovascular-risk-reduction/tools/case_series

Criteria Yes No

Other(CD, NR,

NA)*1. Was the study question or objective clearly stated?

2. Was the study population clearly and fully described, including a case definition?

3. Were the cases consecutive? 4. Were the subjects comparable? 5. Were identification criteria of bacteria clearly defined ?

6. Were sensitivities are reported for the bacteria include commonly used antiobiotics, and used consistently ?

7. Was the length of follow-up adequate? 8. Were the statistical methods well-described?

9. Were the results well-described? Quality Rating (Good, Fair, or Poor)

Rater #1 initials:Rater #2 initials:Additional Comments (If POOR, please state why):

*CD, cannot determine; NA, not applicable; NR, not reported

syed Tirmizi � 17/2/2016 17:49Deleted: assyed Tirmizi � 17/2/2016 17:49Deleted: the intervention clearly described?syed Tirmizi � 17/2/2016 17:50Deleted: syed Tirmizi � 17/2/2016 17:50Deleted: the outcome measures clearly defined, valid, reliablesyed Tirmizi � 17/2/2016 17:51Deleted: implemented syed Tirmizi � 17/2/2016 17:51Deleted: across all study participants