title: Predicting long-term mortality in older patients after non-ST-segment elevation myocardial infarction: the CRUSADE long-term mortality model and risk score.
abstract: OBJECTIVE
  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.
authors.affiliation: Duke Clinical Research Institute, Durham, NC, USA. matthew.roe@duke.edu
authors.forename: Matthew T
authors.initials: MT
authors.lastname: Roe
authors.forename: Anita Y
authors.initials: AY
authors.lastname: Chen
authors.forename: Laine
authors.initials: L
authors.lastname: Thomas
authors.forename: Tracy Y
authors.initials: TY
authors.lastname: Wang
authors.forename: Karen P
authors.initials: KP
authors.lastname: Alexander
authors.forename: Bradley G
authors.initials: BG
authors.lastname: Hammill
authors.forename: W Brian
authors.initials: WB
authors.lastname: Gibler
authors.forename: E Magnus
authors.initials: EM
authors.lastname: Ohman
authors.forename: Eric D
authors.initials: ED
authors.lastname: Peterson
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D001145:Arrhythmias, Cardiac / Q000503:physiopathology; D005260:Female; D006299:Health Services for the Aged / Q000706:statistics & numerical data*; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D006278:Medicare; D015233:Models, Statistical; D009026:Mortality; D009203:Myocardial Infarction / Q000401:mortality* / Q000503:physiopathology; D016016:Proportional Hazards Models; D012042:Registries; D015203:Reproducibility of Results; D012307:Risk Factors; D014481:United States / Q000453:epidemiology