Predicting long-term mortality in older patients after non-ST-segment elevation myocardial infarction: the CRUSADE long-term mortality model and risk score.

OBJECTIVES: We sought to develop a long-term mortality risk prediction model and a simplified risk score for use in older patients with non-ST-segment elevation myocardial infarction (NSTEMI). BACKGROUND: Limited data are available regarding long-term mortality rates and concomitant risk predictors after acute myocardial infarction in contemporary community practice. METHODS: From the CRUSADE registry, a total of 43,239 (NSTEMI) patients aged ≥65 years treated at 448 hospitals in the United States from 2003 to 2006 were linked to Centers for Medicare and Medicaid Services data to track longitudinal all-cause mortality (median follow-up 453 days). Cox proportional hazard modeling was used to determine baseline independent demographic, clinical, and laboratory variables associated with long-term mortality. A simplified long-term mortality risk score was subsequently developed from these results. RESULTS: The median age of this population was 77 years, and mortality rates at 1, 2, and 3 years were 24.4%, 33.2%, and 40.3%, respectively. We identified 22 variables independently associated with long-term mortality in a full model (c-statistic 0.754 in the derivation sample and 0.744 in the validation sample). The CRUSADE long-term mortality risk score was limited to the 13 most clinically and statistically significant variables from the full model yet retained comparable discrimination in the derivation and validation samples (c-statistics 0.734 and 0.727, respectively) and had good calibration across the risk spectra. CONCLUSIONS: Older patients face substantial long-term mortality risks after NSTEMI that can be accurately predicted from baseline characteristics. These prognostic estimates may support informed treatment decision-making and comparison of long-term provider outcomes.

Duke Scholars

Author Matthew Todd Roe Medicine, Cardiology

Author Laine Elliott Thomas Biostatistics & Bioinformatics, Division of Biostatistics

Author Karen Patton Alexander Medicine, Cardiology

Author Bradley Gordon Hammill Population Health Sciences

Author Erik Magnus Ohman Medicine, Cardiology