matthew w. sherwood, yongfei wang, jeptha p. curtis, eric d. peterson, sunil v. rao

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Patterns of red blood cell transfusion use and outcomes in patients undergoing percutaneous coronary intervention in contemporary clinical practice: Insights from the NCDR ® Matthew W. Sherwood, Yongfei Wang, Jeptha P. Curtis, Eric D. Peterson, Sunil V. Rao

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Patterns of red blood cell transfusion use and outcomes in patients undergoing percutaneous coronary intervention in contemporary clinical practice: Insights from the NCDR ®. Matthew W. Sherwood, Yongfei Wang, Jeptha P. Curtis, Eric D. Peterson, Sunil V. Rao. Disclosures. - PowerPoint PPT Presentation

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Page 1: Matthew W. Sherwood,  Yongfei  Wang,  Jeptha  P. Curtis, Eric D. Peterson,  Sunil V.  Rao

Patterns of red blood cell transfusion use and outcomes in patients undergoing percutaneous coronary intervention in contemporary clinical practice: Insights

from the NCDR®

Matthew W. Sherwood, Yongfei Wang, Jeptha P. Curtis, Eric D.

Peterson, Sunil V. Rao

Page 2: Matthew W. Sherwood,  Yongfei  Wang,  Jeptha  P. Curtis, Eric D. Peterson,  Sunil V.  Rao

DisclosuresMatthew W. Sherwood – None Yongfei Wang – NoneJeptha P. Curtis – None Eric D. Peterson – Research Support >10K :

Eli Lilly, Janssen Pharm., PI of Data Analytic Center for ACCSunil V. Rao – Research grants - Ikaria, sanofi-aventis;

Consultant/honoraria - The Medicines Co, Terumo Medical, ZOLL, Astra Zeneca, Daiichi Sankyo Lilly, Janssen

Page 3: Matthew W. Sherwood,  Yongfei  Wang,  Jeptha  P. Curtis, Eric D. Peterson,  Sunil V.  Rao

Funding Support and Disclaimer This research was supported by the American College of Cardiology Foundation’s National Cardiovascular Data Registry (NCDR). The views expressed in this presentation represent those of the author(s), and do not necessarily represent the official views of the NCDR or its associated professional societies identified at www.ncdr.com.

Page 4: Matthew W. Sherwood,  Yongfei  Wang,  Jeptha  P. Curtis, Eric D. Peterson,  Sunil V.  Rao

Background• Prior studies have shown that there is marked

variation in the use of red blood cell transfusion (RBCT) among patients with acute coronary syndromes

• Contemporary post-procedure RBCT patterns in patients undergoing PCI are unclear

• Documenting variation in RBCT practice is important since RBCT has been independently associated with morbidity and mortality in patients with ischemic heart disease

Page 5: Matthew W. Sherwood,  Yongfei  Wang,  Jeptha  P. Curtis, Eric D. Peterson,  Sunil V.  Rao

Objectives• To determine the variability in use of RBCT in

hospitals across the United States• To determine patient factors associated with

RBCT• To determine whether RBCT has an

independent association with patient outcomes– Is an association of transfusion with outcomes

independent of bleeding

Page 6: Matthew W. Sherwood,  Yongfei  Wang,  Jeptha  P. Curtis, Eric D. Peterson,  Sunil V.  Rao

Methods• Database – NCDR® Cath-PCI® database• Patients – 1,323,965 patients undergoing PCI

at 1282 hospitals between 7/2009-9/2011 • Exclusions

– patients who underwent in-hospital CABG– More then 1 PCI during hospital stay– Missing data on bleeding events, procedural

complications, d/c status

Page 7: Matthew W. Sherwood,  Yongfei  Wang,  Jeptha  P. Curtis, Eric D. Peterson,  Sunil V.  Rao

Outcomes and Definitions• Primary – Transfusion rates• Secondary – Clinical Outcomes

– MI– Stroke– In-hospital Death

• Definition – Bleeding Events– Hemoglobin drop of ≥3 g/dL– Transfusion of whole blood or packed red blood cells– Procedural intervention/surgery at the bleeding site to

reverse/stop or correct the bleeding

Page 8: Matthew W. Sherwood,  Yongfei  Wang,  Jeptha  P. Curtis, Eric D. Peterson,  Sunil V.  Rao

Analyses• Rates of transfusion by site were determined and

then risk adjusted rates were calculated• Patient clinical characteristics and in-hospital

outcomes were compared between patients who did and did not receive RBCT

• Logistic regression was used to determine the adjusted association between RBCT and in-hospital death, MI, or stroke– Secondary analyses performed to determine whether any

adverse effect of transfusion was independent of bleeding events

Page 9: Matthew W. Sherwood,  Yongfei  Wang,  Jeptha  P. Curtis, Eric D. Peterson,  Sunil V.  Rao

Patient CharacteristicsPatient Characteristics

(%)

Without RBCTN=1294710

With RBCTN=29255

Age (mean, SD) 64.5 (12.1) 70.5 (12.1)

Gender (% Female) 32.2 57.4

HTN 81.8 86.2

Diabetes 34.1 44.3

ESRD on dialysis 2.2 7.8

Prior MI 29.9 32.4

Prior CHF 11.4 26.0

P values for all comparisons <0.001

Page 10: Matthew W. Sherwood,  Yongfei  Wang,  Jeptha  P. Curtis, Eric D. Peterson,  Sunil V.  Rao

Transfusion Pattern by Hgb

<=7 8 9 10 11 12 13 14 >=150

10

20

30

40

50

60

70

80

90

100

With bleedingWithout bleeding

Post Procedure Hgb

% u

se o

f RBC

T

Page 11: Matthew W. Sherwood,  Yongfei  Wang,  Jeptha  P. Curtis, Eric D. Peterson,  Sunil V.  Rao

Transfusion Rates by hospital site

0 1 2 3 4 5 6 7 >=80

5

10

15

20

25

30

% Patient receiving RBCT

% o

f Hos

ptia

ls

Page 12: Matthew W. Sherwood,  Yongfei  Wang,  Jeptha  P. Curtis, Eric D. Peterson,  Sunil V.  Rao

Adjusted transfusion rates0

5010

015

020

025

0N

umbe

r of H

ospi

tals

0 2 4 6 8 10Risk-Standardized Rate of Patients Receiving RBCT(%)

Num

ber o

f hos

pita

ls

Risk adjusted for all variables in the established NCDR mortality and bleeding models

Page 13: Matthew W. Sherwood,  Yongfei  Wang,  Jeptha  P. Curtis, Eric D. Peterson,  Sunil V.  Rao

Outcomes by transfusion statusPatient Outcomes

(%)

Without RBCTN=1294710

With RBCTN=29255

MI 1.9 4.8

Stroke 0.2 1.9

CHF 0.7 9.6

Cardiogenic Shock 0.7 9.9

In-hospital Death 1.1 11.9

Bleeding Events 0.9 36.2

Access Site bleeding 0.5 12.3

Non-Access Site bleeding 0.4 23.9

P values for all comparisons <0.001

Page 14: Matthew W. Sherwood,  Yongfei  Wang,  Jeptha  P. Curtis, Eric D. Peterson,  Sunil V.  Rao

Independent assoc. of RBCT with outcomes

Patient Outcomes Odds Ratios

MI, Stroke, In-hospital Death 2.18 (2.09-2.26)

MI 1.96 (1.85-2.08)

Stroke 3.92 (3.53-4.35)

In-hospital Death 2.02 (1.92-2.13)

Model includes all variable in the established NCDR mortality model; Reference is no transfusion

All patients

Page 15: Matthew W. Sherwood,  Yongfei  Wang,  Jeptha  P. Curtis, Eric D. Peterson,  Sunil V.  Rao

Patient Outcomes Odds Ratios

MI, Stroke, In-hospital Death 1.95 (1.86-2.05)

MI 1.71 (1.58-1.85)

Stroke 4.07 (3.60-4.60)

In-hospital Death 1.73 (1.62-1.84)

Model includes all variable in the established NCDR mortality model; Reference is no transfusion

Independent assoc. of RBCT with outcomesPatients without bleeding

Page 16: Matthew W. Sherwood,  Yongfei  Wang,  Jeptha  P. Curtis, Eric D. Peterson,  Sunil V.  Rao

Limitations• Data is observational thus events are

reported, not adjudicated

• Temporal relationship between Hct, transfusion, and events is uncertain

• Cannot infer causality

Page 17: Matthew W. Sherwood,  Yongfei  Wang,  Jeptha  P. Curtis, Eric D. Peterson,  Sunil V.  Rao

Conclusions• Considerable variation in transfusion practices

exists across the U.S., and persists after adjustment for patient differences

• Transfusion patterns by Hgb level are different in patient with bleeding vs. without bleeding

• RBCT is independently associated with adverse cardiac events in patients undergoing PCI– This association still holds in patients without

bleeding events

Page 18: Matthew W. Sherwood,  Yongfei  Wang,  Jeptha  P. Curtis, Eric D. Peterson,  Sunil V.  Rao

Clinical Implications• Our results are consistent with prior reports

demonstrating the potential hazard associated with RBCT among ACS patients

• Randomized trials of transfusion strategies are needed in patients undergoing PCI to guide clinical practice

• Until these data are available, operators should continue to adopt practices that reduce the risk for bleeding and transfusion