Risk Stratification of ACS Patients. Frans Van de Werf, MD, PhD University of Leuven, Belgium

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1 Risk Stratification of ACS Patients Frans Van de Werf, MD, PhD University of Leuven, Belgium

2 Which type of ACS patients are we talking about to day? 4/14/2011

3 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, (2010),

4 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, (2010)

5 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, (2010)

6 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, (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!

7 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:

8 What is a myocardial infarction nowadays? 4/14/2011

12 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:

13 The classical risk models 4/14/2011

14 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 -----------------------------------

15 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 (3 df) 275 (2 df) 143 (2 df) (4 df) (2 df) 15 (3 df) *Indicates the independent contribution of each variable after adjustment for all other factors in the list. The first 10 factors are significant with P< ; 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

16 Predictors of 30 Day Mortality in > STEMI patients (GUSTO) Lee, K. L. et al. Circulation 1995;91:

17 GUSTO-I : Observed 30-Day Mortality vs 30-Day Mortality Predicted by Regression Model Lee et al. Circulation 1995

18 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 (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

19 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 (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)

20 Simplified GRACE Risk Model for Death in ACS at 6 Months

21 Simplified GRACE Risk Model for Death/MI in ACS at 6 Months

22 GRACE Risk Nomogram for Death at 6 Months (simplified model)

23 GRACE Risk Nomogram for Death/MI at 6 Months (simplified model)

24 GRACE Risk Nomogram for Death at 6 Months (Simplified Model)

25 GRACE Risk Nomogram for Death/MI at 6 Months (Simplified Model)

26 26

27 GRACE PDA Software 27

28 TIMI Risk Score: Independent Predictors of 30-Day Mortality in InTIME-II Morrow et al. Circulation 2000

29 Morrow et al. Circulation 2000 TIMI Risk Score for STEMI

30 TIMI Risk Score for UA/Non-STEMI

31 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:

32 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

33 Event rates after an ACS 4/14/2011

34 Cumulative death rates in 3721 ACS patients from UK and Belgium at ± 5 year (GRACE) % 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

35 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?

78-year-old female patient with 6 mm STsegment elevation in anterior leads,

8 mg/dl), never smoked, Killip class II on admission vs 42-year-old male patient

36 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

37 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

endpoint Risk models/scores tend to underestimate the risk in patients who did not participate in randomized trials Risk

38 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

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