Predicting one-year mortality among elderly survivors of hospitalization for an acute myocardial infarction: results from the Cooperative Cardiovascular Project

J Am Coll Cardiol. 2001 Aug;38(2):453-9. doi: 10.1016/s0735-1097(01)01395-x.


Objectives: We sought to develop a model based on information available from the medical record that would accurately stratify elderly patients who survive hospitalization with an acute myocardial infarction (AMI) according to their risk of one-year mortality.

Background: Prediction of the risk of mortality among older survivors of an AMI has many uses, yet few studies have determined the prognostic importance of demographic, clinical and functional data that are available on discharge in a population-based sample.

Methods: In a cohort of patients aged > or = 65 years who survived hospitalization for a confirmed AMI from 1994 to 1995 at acute care, nongovernmental hospitals in the U.S., we developed a parsimonious model to stratify patients by their risk of one-year mortality.

Results: The study sample of 103,164 patients, with a mean age of 76.8 years, had a one-year mortality of 22%. The factors with the strongest association with mortality were older age, urinary incontinence, assisted mobility, presence of heart failure or cardiomegaly any time before discharge, presence of peripheral vascular disease, body mass index <20 kg/m2, renal dysfunction (defined as creatinine >2.5 mg/dl or blood urea nitrogen >40 mg/dl) and left ventricular dysfunction (left ventricular ejection fraction <40%). On the basis of the coefficients in the model, patients were stratified into risk groups ranging from 7% to 49%.

Conclusions: We demonstrate that a simple risk model can stratify older patients well by their risk of death one year after discharge for AMI.

Publication types

  • Evaluation Study

MeSH terms

  • Aged
  • Cohort Studies
  • Female
  • Forecasting
  • Hospitalization
  • Humans
  • Male
  • Myocardial Infarction / mortality*
  • Prognosis
  • Proportional Hazards Models*
  • Retrospective Studies
  • Risk Factors
  • Survivors