Risk Stratification of ACS Patients Frans Van de Werf, MD, PhD University of Leuven, Belgium
Which type of ACS patients are we talking about to day? 4/14/2011
STEMI and NSTEMI in the NRMI registry from 1990 to 2006 and % in whom a troponin assay was used to diagnose MI Roger, V. L. et al. Trends in incidence, severity, and outcome of hospitalized myocardial infarction. Circulation 121, 863 869 (2010),
Trends in incidence of hospitalized MI from 1987 to 2006 in OlmstedCounty, MN, USA, by ST-segment elevation status Roger, V. L. et al. Trends in incidence, severity, and outcome of hospitalized myocardial infarction. Circulation 121, 863 869 (2010)
Trends in incidence of hospitalized MI from 1987 to 2006 in OlmstedCounty, MN, USA, by ST-segment elevation status Roger, V. L. et al. Trends in incidence, severity, and outcome of hospitalized myocardial infarction. Circulation 121, 863 869 (2010)
Age-adjusted and sex-adjusted incidence of acute MI in KaiserPermanente, Northern California, USA, from 1999 to 2008 Yeh, R. W. et al. Population trends in the incidence and outcomes of acute myocardial infarction. N. Engl. J. Med. 362, 2155 2165 (2010)
30-day case fatality rates for hospitalized MI overall and by age, sex, and time period BUT.Long-term survival among 30-day survivors did not improve!.causes of death shifted from CV to non-cv in most recent year quartile (50% non-cv) Copyright 2010 American Heart Association Roger, V. L. et al. Circulation 2010;121:863-869
What is a myocardial infarction nowadays? 4/14/2011
Flow Diagram of Patient Recruitment Copyright 2011 American College of Cardiology Foundation. Restrictions may apply. Lim, C. C. S. et al. J Am Coll Cardiol 2011;57:653-661
Copyright 2011 American College of Cardiology Foundation. Restrictions may apply. Peak CK-MB and Troponin Values Lim, C. C. S. et al. J Am Coll Cardiol 2011;57:653-661
Copyright 2011 American College of Cardiology Foundation. Restrictions may apply. PMI Groups Lim, C. C. S. et al. J Am Coll Cardiol 2011;57:653-661
Percentage Change From Baseline of CRP, SAA, MPO, and TNF-Alpha Levels Copyright 2011 American College of Cardiology Foundation. Restrictions may apply. Lim, C. C. S. et al. J Am Coll Cardiol 2011;57:653-661
The classical risk models 4/14/2011
Risk Models and Risk Scores GUSTO-I Model for 30-Day Mortality in STEMI TIMI Risk Score for STEMI and NonSTEMI GRACE Risk Model for 6 Months Outcome in ACS (STEMI, NonSTEMI and UA)
GUSTO-I : Independent Clinical Predictors of 30-Day Mortality* Variable Adjusted c 2 Age, y Systolic BP, mm Hg Killip class Heart rate, bpm Location of infarction ----------------------------------- Previous infarction Age-by-Killip class interaction Height, cm Time to treatment, h Diabetes Weight, kg Smoking Choice of thrombolytic therapy Previous bypass surgery Hypertension Prior cerebrovascular disease 717 550 350 (3 df) 275 (2 df) 143 (2 df) -------------- 64 29 31 (4 df) 23 21 16 22 (2 df) 15 (3 df) 16 14 10 *Indicates the independent contribution of each variable after adjustment for all other factors in the list. The first 10 factors are significant with P<0.00001; the next four P <0.0001; the last two P<0.01. Sex (P=0.043) and US enrollment (P=0.047) were marginal predictors. Lee et al. Circulation 1995
Predictors of 30 Day Mortality in > 40 000 STEMI patients (GUSTO) Lee, K. L. et al. Circulation 1995;91:1659-1668
GUSTO-I : Observed 30-Day Mortality vs 30-Day Mortality Predicted by Regression Model Lee et al. Circulation 1995
GRACE: Predictors of 6 Month Mortality Predictors Χ 2 HR (95%CI) Age (per 10 year increase) Medical History Congestive heart failure Hypertension Peripheral vascular disease PCI 505.7 34.2 8.8 21.8 8.3 1.8 (1.68 to 1.84) 1.5 (1.32 to 1.73) 1.2 (1.05 to 1.33) 1.4 (1.21 to 1.62) 0.8 (0.64 to 0.93) 4/14/2011
GRACE: Predictors of 6 Month Mortality Predictors Χ 2 HR (95%CI) Presentation characteristics Pulse (per 30 bpm ) Systolic blood pressure (20 mmhg ) Killip class Initial serum creatinine (per 88 µmol/l ) Initial cardiac markers or enzymes Cardiac arrest Findings on electrocardiography ST segment deviation LBBB No of leads with ST segment deviation 44.3 152 142.8 135.3 63.0 58.5 46.8 10.0 20.1 1.2 (1.16 to 1.31) 1.2 (1.22 to 1.30) 1.5 (1.41 to 1.62) 1.2 (1.19 to 1.29) 1.6 (1.42 to 1.78) 2.6 (2.00 to 3.32) 1.6 (1.41 to 1.88) 1.3 (1.10 to 1.60) 1.2 (1.10 to 1.33)
Simplified GRACE Risk Model for Death in ACS at 6 Months
Simplified GRACE Risk Model for Death/MI in ACS at 6 Months
GRACE Risk Nomogram for Death at 6 Months (simplified model)
GRACE Risk Nomogram for Death/MI at 6 Months (simplified model)
GRACE Risk Nomogram for Death at 6 Months (Simplified Model)
GRACE Risk Nomogram for Death/MI at 6 Months (Simplified Model)
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GRACE PDA Software 27
TIMI Risk Score: Independent Predictors of 30-Day Mortality in InTIME-II Morrow et al. Circulation 2000
Morrow et al. Circulation 2000 TIMI Risk Score for STEMI
TIMI Risk Score for UA/Non-STEMI
TIMI Risk Score and all-cause mortality, MI, and severe recurrent ischemia calculated for enoxaparin and UFH in TIMI11B and ESSENCE Antman, E. M. et al. JAMA 2000;284:835-842
A recent case: Women, 66 y, chest pain, troponins negative, cholesterol : 266 mg/dl ST segment depression in II, III, avf and V6 enrolled in a NSTE-ACS study, coronary angiography: negative! 4/14/2011
Event rates after an ACS 4/14/2011
Cumulative death rates in 3721 ACS patients from UK and Belgium at ± 5 year (GRACE) 25 20 15 19% TOTAL 14% % CV 22% TOTAL 16% CV 17% TOTAL 13% CV 10 65% after discharge 83% after discharge 95% after discharge 5 0 n=1403 n=1107 n=850 STEMI Non-STEMI UA Fox K et al. Eur Heart J 2010
Who Can/Should Use the Risk Models/Scores? Risk models/scores can/should be used by clinicians to : for triage decisions To determine risk of an adverse event or co-morbidity to delineate treatment options Risk models/scores can/should be used by guidelines committees to : to determine relative treatment benefit/harm of certain therapies in different risk categories
Do (Good!) Clinicians Really need these Risk Models/ Scores? Estimated 30 day mortality 20% or 30% Estimated 30 day mortality 1% or 2% 78-year-old female patient with 6 mm STsegment elevation in anterior leads, history of hypertension, type 2 DM, renal failure (serum creatinine of 1.8 mg/dl), never smoked, Killip class II on admission vs 42-year-old male patient with 1 mm STsegment elevation in inferior leads, no hypertension, no DM, heavy smoker (1.5 packet /day), Killip class I on admission
Do Guidelines Committees Use these Risk Models/Scores? Yes,to a certain extent but the usual conclusion is that there is uncertainty and that new prospective and randomized studies are needed in specific risk categories such as eg the elderly, diabetics, renal failure, hypertensive pts etc
Conclusions Risk models/scores for cardiac risk stratification in ACS patients perform well in populations similar to the one from which they were obtained Risk models/scores for mortality alone provide better discrimination than those for a composite endpoint Risk models/scores tend to underestimate the risk in patients who did not participate in randomized trials Risk models/scores for longterm outcome are lacking The usefulness of these risk models/scores in daily clinical practice has not been demonstrated