Sumeet Subherwal, Richard G. Bach, Anita Y. Chen, Brian F. Gage, Sunil V. Rao, Tracy Y. Wang, W. Brian Gibler, E. Magnus Ohman, Matthew T. Roe, Eric D. Peterson, Karen P. Alexander - PowerPoint PPT Presentation

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Sumeet Subherwal, Richard G. Bach, Anita Y. Chen, Brian F. Gage, Sunil V. Rao, Tracy Y. Wang, W. Brian Gibler, E. Magnus Ohman, Matthew T. Roe, Eric D. Peterson, Karen P. Alexander

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... Cockcroft-Gault is truncated _at_ 90 mL/min; Prior Vascular disease is defined as prior PAD or stroke Predictor Range Score Baseline Hematocrit (%) ... – PowerPoint PPT presentation

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Title: Sumeet Subherwal, Richard G. Bach, Anita Y. Chen, Brian F. Gage, Sunil V. Rao, Tracy Y. Wang, W. Brian Gibler, E. Magnus Ohman, Matthew T. Roe, Eric D. Peterson, Karen P. Alexander


1
The CRUSADE Bleeding Score
A validated risk prediction tool for estimation
of baseline risk of in-hospital major bleeding in
patients with NSTEMI
  • Sumeet Subherwal, Richard G. Bach, Anita Y.
    Chen, Brian F. Gage, Sunil V. Rao, Tracy Y. Wang,
    W. Brian Gibler, E. Magnus Ohman, Matthew T. Roe,
    Eric D. Peterson, Karen P. Alexander
  • Duke Clinical Research Institute and Washington
    University St. Louis

2
Background
  • Validated risk stratification tools exist for
    baseline ischemic risk (TIMI, PURSUIT, GRACE
    ACS), however estimation of baseline bleeding
    risk in patients with NSTEMI is difficult because
    existing tools
  • include treatment variables (i.e. antithrombotics
    or invasive procedures)
  • derived from highly selected patient populations

3
CRUSADE Major Bleeding Model
  • CRUSADE Quality Improvement Initiative
  • February 15, 2003 to December 31, 2006
  • n89,134 NSTEMI patients at 485 US hospitals
  • Excluded unstable angina, home warfarin, transfer
    out, deaths within 48 hours
  • In-hospital Major Bleeding (Censored at CABG)
  • Absolute HCT drop 12 (Baseline Nadir)
  • Intracranial hemorrhage or retroperitoneal bleed
  • Transfusion if baseline HCT 28
  • Transfusion if baseline HCT lt28 AND witnessed
    bleed
  • Divided into derivation (80 of N) and validation
    cohorts (20 of N)
  • Incorporated clinically and statistically
    significant univariate associations into a
    multivariable model using generalized estimating
    equations (GEE)

4
Baseline Characteristics
Variable Derivation Cohort (N 71,277) Validation Cohort (N 17,857)
Age (years) 67.0 (56.0, 79.0) 67.0 (56.0, 79.0)
Male 60.2 60.3
Family history of CAD 33.9 33.9
History of hypertension 70.5 70.6
Diabetes mellitus 32.7 32.5
Prior vascular disease 18.4 18.1
Current/recent smoker 28.4 27.8
Hyperlipidemia 52.0 51.7
Prior myocardial infarction 28.1 27.9
Prior CABG 18.2 18.5
Baseline HCT () 40.7 (36.5, 44.2) 40.7 (36.6, 44.1)
CrCl (mL/min) 70.3 (43,8, 101.9) 70.8 (44.0, 102.0)
In-Hospital Events
Death gt 48 hrs  2.7 2.6
Major bleeding 9.4 9.6
Median (25th, 75th percentile) Prior vascular
disease defined as h/o stroke or peripheral
arterial disease Creatinine clearance as
estimated by Cockcroft-Gault Formula
5
Multivariable Predictors of Bleeding
Variable ?2 Derivation Cohort OR 95 CI Derivation Cohort OR 95 CI Validation Cohort OR 95 CI Validation Cohort OR 95 CI
Baseline HCT lt36 (vs. 36) 434.6 2.28 2.11-2.46 2.17 1.92-2.44
CrCl (per 10 mL/min decrease) 433.2 1.12 1.10-1.13 1.11 1.09-1.13
Heart rate (per 10 bpm increase) 159.2 1.08 1.07-1.10 1.09 1.07-1.12
Female 77.8 1.31 1.23-1.39 1.33 1.19-1.50
Signs of heart failure 37.7 1.23 1.15-1.31 1.13 1.01-1.28
Prior vascular disease 30.4 1.19 1.12-1.27 1.10 0.98-1.24
Diabetes mellitus 26.6 1.16 1.10-1.23 1.25 1.12-1.40
SBP 110 mm Hg (vs. 110-180) 12.6 1.26 1.16-1.36 1.27 1.10-1.47
SBP 180 mm Hg (vs. 110-180) 1.24 1.14-1.35 1.18 1.02-1.37
c-Statistic 0.72 0.72 0.72 0.71 0.71
Prior vascular disease defined as h/o stroke or
peripheral arterial disease Note Heart rate is
truncated _at_ lt70 bpm CrCl Cockcroft-Gault is
truncated _at_ gt90 mL/min
6
CRUSADE Bleeding Score
  • The CRUSADE Bleeding Score was developed by
    assigning a weighted integer to each independent
    predictor based on the predictors coefficient in
    the reduced regression model
  • The CRUSADE Bleeding Score (range 1-100 points)
    equals the sum of weighted integers for
    independent predictors

7
CRUSADE Bleeding Score Nomogram

Predictor Range Score
Baseline Hematocrit () lt 31 31-33.9 34-36.9 37-39.9 40 9 7 3 2 0
Creatinine Clearance (mL/min) 15 gt15-30 gt30-60 gt60-90 gt90-120 gt120 39 35 28 17 7 0
Heart rate (bpm) 70 71-80 81-90 91-100 101-110 111-120 121 0 1 3 6 8 10 11
Sex Male Female 0 8
Signs of CHF at presentation No Yes 0 7
Prior Vascular Disease No Yes 0 6
Diabetes Mellitus No Yes 0 6
Systolic blood pressure (mm Hg) 90 91-100 101-120 121-180 181-200 201 10 8 5 1 3 5
Note Heart rate is truncated _at_ lt70 bpm CrCl
Cockcroft-Gault is truncated _at_ gt90 mL/min Prior
Vascular disease is defined as prior PAD or stroke
8
CRUSADE Bleeding Score
9
CRUSADE Bleeding Score Risk Quintiles
  • Patients were categorized into risk quintiles
    based on CRUSADE Bleeding Score

Risk N Min Score Max Score Bleeding
Very low 19,486 1 20 3.1
Low 12,545 21 30 5.5
Moderate 11,530 31 40 8.6
High 10,961 41 50 11.9
Very High 15,210 51 91 19.5
10
Major Bleeding by Risk Quintiles in Derivation
and Validation Cohorts
11
Major Bleeding by Antithrombotic therapy
2 Antithrombotics (anti-platelet aspirin or
clopidogrel, anti-coagulant, or GP IIb/IIIa
n50,969 c-index 0.72) lt2 Antithrombotics
(anti-platelet, anti-coagulant, or GP IIb/IIIa
n5,931 c-index 0.73)
12
Major Bleeding by Invasive or Conservative
Approach
Conservative Approach (2 antithrombotics and no
catheterization n3,200 c-index 0.68) Invasive
Approach (2 antithrombotics and no
catheterization n43,492 c-index 0.73)
13
Mortality in those who did or did not have a
Major Bleed across Risk Quintiles
14
Conclusion
  • The CRUSADE Bleeding Score combines 8 predictors
    of major bleeding into a simple validated
    prediction tool that estimates baseline risk of
    in-hospital major bleeding in patients with
    NSTEMI
  • Preserved discrimination across treatment
    subgroups
  • Complements ischemic risk prediction tools to
    better enable clinicians to consider the
    potential adverse outcomes in patients with
    NSTEMI prior to initiation of therapy

15
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