Usefulness of the TIMI Risk Index in Predicting Short- and Long-Term Mortality in Patients With Acute Coronary Syndromes

Usefulness of the TIMI Risk Index in Predicting Short- and Long-Term Mortality in Patients With Acute Coronary Syndromes Leonard Ilkhanoff, MDa, Christopher J. O’Donnell, MD, MPHb,g, Carlos A. Camargo, MD, DrPHc,f, T. David O’Halloran, MDd, Robert P. Giugliano, MD, SMe, and Donald M. Lloyd-Jones, MD, SMh,* In a cohort of 710 patients with acute coronary syndromes (ACSs), we demonstrated that the Thrombolysis In Myocardial Infarction Risk Index—a predictor of 30-day mortality in clinical trial patients with ST-elevation myocardial infarction (STEMI)—is a strong predictor of short- and long-term mortality with good discrimination ability (c statistics 0.77 to 0.79) among all subtypes of ACSs (STEMI, non-STEMI, and unstable angina pectoris). These results verify the utility of the Risk Index in unselected patients with STEMI, broaden its application to other types of ACSs, and extend its utility to stratification of long-term mortality risk. © 2005 Elsevier Inc. All rights reserved. (Am J Cardiol 2005;96:773–777) Of the independent clinical predictors of adverse outcomes in patients with ST-elevation myocardial infarction (STEMI), the patient’s age, heart rate, and systolic blood pressure at presentation have consistently been among the strongest, with age and heart rate having direct, and systolic blood pressure having inverse, associations with mortality risk.1– 4 Derived from a cohort of patients in a thrombolysis trial,5 and subsequently validated in the Thrombolysis In Myocardial Infarction (TIMI) 9A and 9B trial samples,6,7 the TIMI Risk Index combines age, heart rate, and systolic blood pressure. It was shown to be a strong, independent predictor of in-hospital and 30-day mortality in patients with STEMI.8 Before widespread adoption in general practice, the Risk Index requires additional validation in other patient cohorts. In the present study, we sought to test whether the use of the TIMI Risk Index can be extended to predict mortality in an unselected population of patients presenting to the emergency department; across the spectrum of low-, medium-, and high-risk patients with all manifestations of acute coronary syndromes (ACSs); and in the short and long term among these patients. •••

The details of patient inclusion have been published elsewhere.9,10 In brief, between October 1, 1991, and September 30, 1992, a total of 1,016 patients presented to the emera

Cardiovascular Division, Department of Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania; bDivision of Cardiology and Departments of cEmergency Medicine and dMedicine, Massachusetts General Hospital, Boston, Massachusetts; eCardiovascular Division and fChanning Laboratory, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts; gNational Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts; and hDepartment of Preventive Medicine and Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois. Manuscript received December 14, 2004; revised manuscript received and accepted April 25, 2005. * Corresponding author: Tel.: 312-503-0196; fax: 312-908-9588. E-mail address: [email protected] (D.M. Lloyd-Jones). 0002-9149/05/$ – see front matter © 2005 Elsevier Inc. All rights reserved. doi:10.1016/j.amjcard.2005.04.059

gency department and were hospitalized at our institution with suspected ACSs. From the 1,016 patients in the database, we excluded 51 who were transferred from outside hospitals, 26 with elevations of myocardial enzymes unrelated to ACSs (e.g., normal coronary arteries at angiography and biopsy-proved myocarditis), 176 with elevations of cardiac enzymes occurring ⬎24 hours after presentation, and 3 with missing charts. Of these 760 patients, we excluded an additional 26 patients who did not have presentation heart rate or blood pressure data available from the emergency department records. Another 24 patients were excluded because their heart rate was low (⬍50 beats/min, n ⫽ 16) or high (⬎150 beats/min, n ⫽ 8). These latter exclusion criteria were used because they were also used as exclusion criteria in the derivation set for the TIMI Risk Index,8 because patients with these extreme values often require more individualized care. Thus, a total of 710 patients were included in the sample for the present analysis. The data were collected from the first point of contact in the emergency department. In our institution, vital signs were generally documented by a triage nurse, or, if not collected at that time, recorded by the nurse or physician first caring for the patient, before any major medical interventions. The medical records of the patient population were reviewed by 6 trained physician abstractors, using prespecified variable definitions. Data were collected on baseline demographics, cardiovascular disease risk factors, presenting clinical characteristics, and hospital course. Computerized laboratory records were available for 100% of patients; complete hospital charts were available for 98%. The agreement among the chart abstractors was assessed for several key variables; inter-rater agreement ranged from 88% to 91% (␬ 0.74 to 0.81; all p ⬍0.0001). To derive the TIMI Risk Index, a patient’s age (in years) is divided by 10; this figure is then squared, multiplied by the patient’s presenting heart rate (in beats per minute) and divided by the patient’s systolic blood pressure (in millimewww.AJConline.org

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Table 1 Characteristics of the study sample (n ⫽ 710) Age (yrs) Heart rate at presentation (beats/min) Systolic blood pressure at presentation (mm Hg) Women Current smoker Diabetes mellitus Previous myocardial infarction Previous coronary revascularization Aspirin therapy before presentation ␤-blocker therapy before presentation Serum creatinine ⬎1.5 mg/dl Congestive heart failure at presentation Type of acute coronary syndrome Unstable angina pectoris Non–STEMI STEMI In hospital Recurrent angina pectoris Development of new Q waves on electrocardiogram Aspirin therapy within 24 h Heparin therapy within 24 h Thrombolytic therapy Coronary revascularization

68 ⫾ 13 85.8 ⫾ 21.4 159.2 ⫾ 33.1 255 (35.9%) 160 (22.7%) 199 (28.2%) 300 (42.4%) 216 (30.5%) 242 (34.2%) 213 (30.1%) 145 (20.4%) 218 (30.7%) 162 (22.8%) 432 (60.9%) 116 (16.3%) 209 (29.4%) 82 (11.8%) 511 (72.3%) 430 (60.6%) 70 (9.9%) 169 (23.8%)

ters of mercury).8 The patients were stratified into 5 groups (quintiles) according to their TIMI Risk Index score, using the cutpoints from the initial study by Morrow et al8: ⬍12.5, 12.5 to 17.5, 17.5 to 22.5, 22.5 to 30, and ⬎30. Patients were also stratified by the ACS subtype based on the presenting electrocardiographic findings and serologic results within the first 24 hours of presentation into the following groups9,10: unstable angina pectoris (UAP), non–STEMI, and STEMI. The primary outcomes of interest were 30-day, 1-year, and long-term mortality. The 30-day end point was chosen to be consistent with the end point used for the derivation of the TIMI Risk Index.8 Mortality data were obtained first from hospital records. When the mortality status remained uncertain, we searched the Massachusetts Death Registry and Social Security Death Index ⱕ10 years after presentation. At 1 year after presentation, we interviewed patients with incomplete mortality follow-up by mail and telephone. This research was approved by the Subcommittee on Human Studies at our institution. All statistical analyses were performed using Stata statistical software, version 8SE (Stata, College Station, Texas). We first examined the mortality rates by point score and quintile of TIMI Risk Index for all patients. The mor-

Figure 1. Distributions of (A) age, (B) heart rate, (C) systolic blood pressure, and (D) TIMI Risk Index of 710 patients with suspected acute myocardial infarction.

Coronary Artery Disease/TIMI Risk Index in ACS

Figure 2. Mortality rates at 30 days (white bars), 1 year (hatched bars), and long-term (median 9.6 years) (black bars) according to TIMI Risk Index at presentation considered as (A) continuous variable and (B) in quintiles, using quintile cutpoints derived from Morrow et al.8

tality rates across quintiles of TIMI Risk Index were compared using nonparametric trend tests based on the Wilcoxon rank-sum test. In secondary analyses, we compared the mortality rates according to TIMI Risk Index stratified by ACS subtype and age at presentation at all 3 mortality time points. The prognostic discriminatory capacity of the Risk Index was expressed as the c statistic, representing the area under the receiver-operating characteristics curve for the prediction of death. A c statistic of 0.5 suggests no discriminative ability, c statistics of 0.7 to 0.8 are considered acceptable, and 0.8 and 0.9, excellent.11 In separate analyses, we used the logistic regression method to examine the risks of 30-day mortality and Cox proportional hazards models to derive hazards ratios for the 1-year and long-term mortality associated with TIMI Risk Index treated as a continuous variable and examined the c statistic for the Risk Index in these models. Proportional hazards assumptions were evaluated and were consistent. Goodness-of-fit and

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calibration of the risk index were also assessed and found to be appropriate. The statistical significance level for all analyses was defined as 2-tailed p ⱕ0.05. A total of 710 patients were included in the study sample (Table 1). The mean age was 68 ⫾ 13 years, and 36% were women. Figure 1 shows the age, heart rate, and systolic blood pressure distributions for the study sample, as well as the distribution of TIMI Risk Index scores. The mean TIMI Risk Index score was 27.3 ⫾ 15.0 (median 24.1, range 3.4 to 135.3). Patients were followed for a median of 9.6 years (interquartile range 3.1 to 10.1) after their presentation with an ACS. The 30-day, 1-year, and long-term mortality rates are displayed in Figure 2, according to the TIMI Risk Index at presentation, with the Risk Index considered as a continuous variable (Figure 2) or in quintiles (Figure 2), using the quintile cutpoints derived from Morrow et al.8 At all time points, the mortality rates increased substantially and in a stepwise fashion, with an increasing TIMI Risk Index (p for trend ⬍0.01 for all time points). When the Risk Index was considered as a continuous variable, a 1-point increase in the TIMI Risk Index was associated with a 3.4% increase (95% confidence interval 2.4% to 4.4%) in risk for 30-day mortality, 3.5% increase (95% confidence interval 2.8% to 4.2%) in risk for 1-year mortality, and 3.6% increase (95% confidence interval 3.1% to 4.2%) in risk for long-term mortality. For the 3 different mortality end points (30 days, 1 year, and long term), the c statistic (areas under the receiver-operating characteristic curves) for the models predicting mortality using the TIMI Risk Index was 0.79, 0.77, and 0.77, respectively. Mortality rates by quintile of TIMI Risk Index are listed in Table 2, stratified by ACS subtype. With the exception of patients with UAP at 30 days (for whom the mortality rate was very low overall, n ⫽ 1 death), the mortality rates for patients with each ACS subtype increased significantly with increasing TIMI Risk Index quintile at all time points (all p for trend ⱕ0.05). The c statistics for models with the Risk Index as a continuous variable predicting mortality at the different time points are given at the bottom of Table 2 for patients with UAP, non–STEMI, and STEMI, respectively. The Risk Index discriminated risk best among patients with STEMI, and progressively less well with decreasing intensity of ACS type in the short term, but with increasing ability in the long term. Patients by TIMI Risk Index and age at presentation (⬍65 vs ⱖ65 years; Table 3), we observed significant increasing trends in mortality with increasing TIMI Risk Index quintile in younger and older patients. Among the younger patients, the c statistics for the Risk Index were 0.88 at 30 days, 0.75 at 1 year, and 0.63 for the long term;

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Table 2 Mortality rates, stratified by quintile of Thrombolysis In Myocardial Infarction Risk Index and type of acute coronary syndrome at presentation Quintile

Q1 (n ⫽ 78) Q2 (n ⫽ 112) Q3 (n ⫽ 126) Q4 (n ⫽ 149) Q5 (n ⫽ 245) Overall C statistic for TIMI Risk Index

TIMI Risk Index

Mortality Rate (%) 30 Day (n ⫽ 53)

⬍12.5 12.5–17.5 17.5–22.5 22.5–30 ⬎30

1 Year (n ⫽ 109)

Long-term (n ⫽ 410)

UAP

Non–STEMI*

STEMI*

UAP†

Non–STEMI*

STEMI*

UAP*

Non–STEMI*

STEMI*

0 0 0 3.1 0 0.6 0.65

0 0 1.5 10.9 18.4 10.2 0.75

0 0 0 12.0 18.5 6.9 0.85

4.2 0 5.9 15.6 10.3 7.4 0.67

2.9 1.7 4.5 20.7 34.7 19.9 0.76

5.3 0 0 12.0 25.9 9.5 0.81

20.8 27.3 41.2 68.8 69.2 47.5 0.73

17.1 45.8 41.8 70.7 87.2 65.3 0.79

31.6 20.0 32.0 60.0 66.7 44.0 0.70

* p ⬍0.01; † p ⫽ 0.05 for test of trend across quintiles within acute coronary syndrome subtype at given time point. Table 3 Mortality rates, stratified by quintile of Thrombolysis In Myocardial Infarction Risk Index and age at presentation Quintile

Q1 (n ⫽ 78) Q2 (n ⫽ 112) Q3 (n ⫽ 126) Q4 (n ⫽ 149) Q5 (n ⫽ 245) Overall C statistic for TIMI Risk Index

TIMI Risk Index

⬍12.5 12.5–17.5 17.6–22.5 22.6–30 ⬎30

Mortality Rate (%) 30 Day (n ⫽ 53)

1 Year (n ⫽ 109)

Long-term (n ⫽ 410)

Age ⬍65* (n ⫽ 285)

Age ⱖ65* (n ⫽ 425)

Age ⬍65* (n ⫽ 285)

Age ⱖ65* (n ⫽ 425)

Age ⬍65* (n ⫽ 285)

Age ⱖ65* (n ⫽ 425)

0 0 1.3 8.8 13.3 2.1 0.88

— 0 0 9.6 15.7 11.1 0.71

2.6 0 2.6 14.7 20.0 4.2 0.75

— 3.6 6.0 19.1 30.4 22.8 0.68

19.7 29.8 31.6 52.9 60.0 31.9 0.63

— 53.6 52.0 73.0 83.5 75.1 0.68

* p ⬍0.01 for test of trend across quintiles within age group at given time point.

for patients ⱖ65 years of age, the c statistics were 0.71 at 30 days, 0.68 at 1 year, and 0.68 for the long term. •••

In this study, we have demonstrated that the TIMI Risk Index,8 derived from a sample of patients with STEMI selected for enrollment in a clinical trial, is a simple and rapid method of assigning risk in patients presenting across the spectrum of ACSs. We have validated the utility of the Risk Index in an unselected sample of patients with acute STEMI, and we have broadened the use of the Risk Index to include unselected patients with non–STEMI and UAP. We have also demonstrated that the Risk Index is a strong predictor of short-term mortality and can be extended to predict long-term (median 9.6 years) mortality risk in patients presenting with ACS. By using simply obtainable information at the first encounter with the patient, the TIMI Risk Index affords rapid clinical assessment and risk stratification to providers of patients with ACS in the emergency department. The Risk Index was able to discriminate mortality risk using the patients’ presenting age, heart rate, and blood pressure, before complete data on cardiac markers would have been available, and thus before the time at which the final diagnosis of the patient’s subtype of non–ST-elevation ACS

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myocardial infarction: an InTIME II substudy. Lancet 2001;358: 1571–1575. Lloyd-Jones DM, Camargo CA Jr, Giugliano RP, Walsh CR, O’Donnell CJ. Characteristics and prognosis of patients with suspected acute myocardial infarction and elevated MB relative index but normal total creatine kinase. Am J Cardiol 1999;84:957–962. Lloyd-Jones DM, Camargo CA Jr, Allen LA, Giugliano RP, O’Donnell CJ. Predictors of long-term mortality following hospitalization for primary unstable angina and non-ST-elevation myocardial infarction. Am J Cardiol 2003;92:1155–1159. Hosmer DW, Lemeshow S. Applied Logistic Regression, 2nd Ed. New York: John Wiley & Sons, 2000:162. Ryan TJ. The Thrombolysis In Myocardial Infarction Risk Index: a formula with a future. J Am Coll Cardiol 2004;44:790 –792.