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J Am Coll Cardiol, 2004; 44:783-789, doi:10.1016/j.jacc.2004.05.045 © 2004 by the American College of Cardiology Foundation |
,*







* TIMI Study Group
Cardiovascular Division, Brigham and Women's Hospital, Boston, Massachusetts, USA
Ovation Research, Seattle, Washington, USA
Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
Manuscript received October 22, 2003; revised manuscript received May 12, 2004, accepted May 18, 2004.
* Reprint requests and correspondence: Dr. Stephen D. Wiviott, TIMI Study Group, Brigham and Women's Hospital, Cardiovascular Division, 75 Francis Street, Boston, Massachusetts 02115 (Email: swiviott{at}partners.org).
| Abstract |
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BACKGROUND: A simple risk index based on age and vital signs (heart rate x [age/10]2/systolic blood pressure) developed from patients with STEMI accurately predicts mortality in clinical trials of fibrinolysis. The application of such a tool in an unselected population is necessary to evaluate its utility in clinical practice.
METHODS: To evaluate the Thrombolysis In Myocardial Infarction (TIMI) risk index for routine practice, we tested it in the National Registry of Myocardial Infarction (NRMI)-3 and -4. The risk index was evaluated as a continuous variable in patients with STEMI from NRMI and in subgroups based on age and reperfusion status.
RESULTS: A total of 153,486 patients with STEMI were eligible. As anticipated, STEMI patients in NRMI had a higher risk index profile, as compared with those in the clinical trial (median 26.9 vs. 20, p < 0.0001). Classification of NRMI patients with STEMI into risk groups revealed a significant graded relationship with mortality (0.9% to53.2%, ptrend < 0.0001, c statistic 0.79). The discriminatory capacity of the risk index was particularly strong in the 81,679 patients receiving reperfusion therapy (0.6% to60%, ptrend < 0.0001, c statistic 0.81). For the 71,807 patients not receiving reperfusion therapy, a strong graded relationship remained (1.9% to 52.2%, ptrend < 0.0001, c statistic 0.71). Among the elderly, although the distribution of scores was shifted toward higher risk, the performance remained (0% to 53.1%, ptrend< 0.0001, c statistic 0.71).
CONCLUSIONS: A simple risk index from baseline clinical variables routinely obtained at the first patient encounter predicted mortality in a large unselected heterogeneous group of patients with STEMI.
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An early in-hospital evaluation may assist with decisions regarding level of care and monitoring. Patients who are at high risk of adverse outcomes may benefit from initial triage or early transfer to tertiary care centers (17). A prehospital evaluation of patients with myocardial infarction (MI) may be strengthened by risk assessment to assist with triage decisions (18,19). A simple, generalizable, and practical risk index for the rapid evaluation of patients with MI could therefore prove valuable. Such a tool does not need to capture all available prognostic information, but should provide an accurate preliminary estimate of risk.
The risk index, calculated using the equation: (heart rate [HR] x [age/10]2/systolic blood pressure [SBP]) (20), was derived from 13,253 patients enrolled in the Intravenous nPA for Treatment of Infarcting Myocardium Early (InTIME-II) trial (21), a randomized trial of lanoteplase versus alteplase as reperfusion therapy (RT) for ST-segment elevation myocardial infarction (STEMI), and validated in a second clinical trial data set (20). The risk index offered strong discrimination of mortality risk at 24 h, hospital discharge, and 30 days in the derivation set.
We sought to evaluate the performance of the Thrombolysis In Myocardial Infarction (TIMI) risk index in a real-world setting. We therefore applied the TIMI risk index to a nationally representative sample of patients presenting to U.S. hospitals with STEMI in the National Registry of Myocardial Infarction (NRMI)-3 and -4 (22,23).
| Methods |
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Patients with ST-segment elevation or presumed new left bundle branch block were classified with STEMI. Patients were further classified as having received reperfusion therapy (STEMI-RT), including fibrinolytic or primary PCI. To test for a difference in the performance of the index among those who received reperfusion, a logistic regression model was created with terms for the risk index, reperfusion status, and the interaction of these two variables. As in the InTIME-II trial, patients with complete data and a HR between 50 and 150 beats/min were included. Among nontransfer patients with STEMI, 81% were eligible (8.4% were excluded for a nondiagnostic electrocardiogram, 4.9% for HR <50 or >150 beats/min, 1.9% for cardiogenic shock, and 1.7% for missing SBP, HR, or age).
The risk index was modeled as a continuous variable, and 10-point ranges are presented for reference. The prognostic discriminatory capacity of the risk index was expressed as the c statistic, representing the area under the receiver operator characteristics curve for prediction of in-hospital death (24). Differences in event rates across risk index ranges were assessed using the chi-square test for trend. To further evaluate the generalizability of the risk index, each component of the risk index was examined individually and in combination in both the InTIME-II trial and the NRMI, using logistic regression. A two-tailed p value <0.05 was considered significant. Statistical analyses were performed using SAS version 8.02 (SAS Institute, Cary, North Carolina).
| Results |
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There were different risk index distributions among the study groups (Fig. 1). The clinical trial had a median of 20 (interquartile range [IQR] 14 to 27). The median risk index was higher in the registry patients (26.9 [IQR 17.5 to 40.4]), especially those who did not receive immediate RT (36.1 [IQR 24.5 to 50]) and the elderly (37.1 [IQR 28.2 to 49.3]). In addition to higher median risks, the patients who did not receive RT were more likely to be in the highest risk groups, with 42% of patients having an index >40, compared with 11% of patients who received early RT. However, among NRMI patients who did receive RT (21 [IQR 14.7 to 30.3]), the median value and distribution were similar to those in the InTIME-II trial (Fig. 1).
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| Discussion |
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Performance of the risk index in NRMI. Multiple classification schemes have been developed and validated for the purpose of risk stratification among patients with MI (28,10,13,20). Efforts have incorporated physiologic, laboratory, and demographic data into integrative risk scores, including the TIMI risk scores for STEMI (8), unstable angina/nonST-segment elevation MI (10), the PREDICT score (4), and models derived from the Global Utilization of Streptokinase and TPA for Occluded arteries(GUSTO) trial (6,7) and Platelet IIb/IIIa Underpinning the Receptor for Suppression of Unstable Ischemia Trial (PURSUIT) (12).
In some cases, application of these tools requires detailed medical evaluation, testing, and expertise to assess hemodynamic, demographic, and laboratory features. Models that include presenting data, specific laboratory testing, and co-morbid illness are expected to have an increased discriminatory capacity (26). However, these models may not be practical for use in all situations, including initial in-hospital assessment or prehospital triage. The TIMI risk index has the advantage that it retains much of the predictive capacity of more complex systems, but can also be applied by both medical and paramedical personnel with a minimum of demographic (age) and physiologic information (HR and SBP). Additional data, including laboratory studies and physical examination, may be used later to update and refine this initial risk assessment.
This index was initially derived and validated from clinical trial data (20). Patients who are enrolled in clinical trials may have important differences from patients who are either ineligible or not enrolled (27,28). These differences result in greater heterogeneity among patients in clinical practice than among subjects in clinical trials. As would be expected, there was a greater range of risk index values seen among the NRMI participants than among subjects in the InTIME-II trial. For this reason, the risk index has been updated in this analysis, using the index as a continuous variable with a nomogram to estimate risk in clinical practice (Table 2). This updated version of the index continues to perform well in the clinical trial population and has an expanded range to better capture the range of patients in a clinical population. Nonparticipants in clinical trials tend to be at higher risk of adverse outcomes than participants. Our analysis from NRMI supports this important observation. Specifically, patients in NRMI database were more likely to experience in-hospital death than those enrolled in the InTIME-II trial (12.3% vs. 5.4%). However, when stratified by baseline risk, mortality rates were remarkably similar between patients enrolled in the clinical trial and those receiving RT in the community registry (Fig. 2). The strong discriminatory performance and excellent calibration of the index among patients treated with reperfusion in NRMI indicate that it is likely to be useful in a "real-world" population. In patients managed without RT, the risk index maintains reasonable discriminatory performance (c statistic 0.71); however, the event rates are higher than observed in patients receiving RT. This difference has been observed previously in the assessment of other risk prediction rules and appears to be related to the therapeutic impact of RT, as well as the effects of co-morbidities that impact eligibility for RT (25).
A previous analysis of this index using data from the Cardiovascular Cooperative Project (CCP) suggested that it did not perform as well from a discriminatory perspective in a population of elderly patients (29). However, when modeled as a continuous variable (which helps to minimize the inherent restriction introduced by including only elderly patients) in CCP, the index performed reasonably well (c statistic 0.71) (29), as observed in our present analysis. In addition, the index revealed a significant graded relationship with mortality across the risk groups.
Important differences exist between the populations studied (CCP, NRMI, InTIME-II), which may help to explain some of the dissimilarity between these analyses. In CCP, patients were restricted to those over age 65 years. As a result, the population was a considerably older population (median age 76 years), as compared with the InTIME-II trial (median age 61 years) or NRMI (67.6 years). In addition, a minority of patients (36%) in the CCP analysis received RTsignificantly less than either the InTIME-II trial or the nationally representative NRMI (56%). Our analysis from the large NRMI registry addresses these two important issues. Second, stratified by the use of RT, there was, in fact, strong concordance between the observed event rates in the elderly versus the general population across each risk index group. Although the discriminatory capacity of the risk index was modestly attenuated in the elderly, it is not surprising that a three-component risk score with one of the variables limited to the highest range performed less well in discriminating among this specific subgroup than among the entire population in NRMI. We believe that this limitation is acceptable in the context of using the simple risk index as a tool for the initial rapid categorization of risk, to be followed by updated risk assessment as additional information becomes available.
Finally, there were differences in design between our study and the CCP analysis. The CCP is a retrospective analysis of charts of patients identified with MI by the International Classification of Diseases-Ninth Revision-Clinical Modification codes (1994 to 1996). Data abstracted from billing records may misidentify patients with MI, and retrospective chart analysis is limited by what is available in a medical chart, compared with prospective identification of information, as performed in a clinical trial (InTIME-II), as well as the identification of patients by medical professionals and the recording of information either during or after hospitalization in a registry (NRMI).
An interesting observation from the application of the TIMI risk index to NRMI population was the striking differences in the proportion of patients receiving RT. Patients in the higher risk index groups (>40) were only 40% as likely to receive RT as those in the lower risk groups. There are likely multiple factors that explain this discrepancy, including medical co-morbidities and patient preference. We have observed previously that patients in NRMI who did not receive RT were more likely to have multiorgan failure, chronic renal failure, uncertainty regarding the diagnosis of MI, and bleeding risk (25). These factors partly accounted for the higher mortality among patients who did not receive RT. In the present analysis, performance of the risk index is also compared between the InTIME-II trial and the NRMI. It is expected that these same factors contribute to the higher mortality observed in patients in NRMI treated without RT. However, it is noteworthy that it is this group with the highest mortality that may derive the greatest absolute benefit from reperfusion, yet receive it the least.
Study limitations. The strengths of this analysis are the large number of patients and that NRMI reflects varying practice patterns in the U.S. The level of detail of reporting co-morbid illness in this very large database is, by necessity, less than that available in a smaller clinical trial or in clinical practice. The TIMI risk index was designed to provide a preliminary risk assessment during the first patient encounter. It does not integrate the effects of treatment, care setting, co-morbid illnesses (including those potentially involved in reperfusion eligibility), or baseline medications on outcome. Such information may be added to the risk assessment to update the initial evaluation. The index is based on initial inpatient data in both data sets. Although the findings of our analysis are likely generalizable to the prehospital setting, this application merits direct evaluation. The present analysis was not designed to assess the mechanism by which the index predicts mortality in these distinct patient populations. The risk index likely integrates baseline risk (age) with the hemodynamic effects of MI (HR and SBP). Additional evaluation in data sets in which more detailed information is available regarding ventricular function, the extent of coronary artery disease, and the cause of death may help to elucidate the mechanisms by which the index predicts mortality.
Conclusions. A simple risk index that can be calculated from age and vital signs is predictive of in-hospital mortality in a diverse group of patients presenting to U.S. hospitals with MI. This risk index could be used as a practical tool to rapidly risk-stratify patients with MI and could be applied by paramedical personnel in the prehospital setting or at the time of hospital presentation. Additional research to focus on the interaction between the TIMI risk index and treatment response in STEMI could advance the utility of this measure.
| Footnotes |
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