title: Predictors of long-term (10-year) mortality postmyocardial infarction: age-related differences. Soroka Acute Myocardial Infarction (SAMI) Project.
abstract: BACKGROUND
  Cardiovascular diseases are the leading cause of death in elderly people. Over the past decades medical advancements in the management of patients with acute myocardial infarction (AMI) led to improved survival and increased life expectancy. As short-term survival from AMI improves, more attention is being shifted toward understanding and improving long-term outcomes.
  
  
  OBJECTIVE
  To evaluate age-associated variations in the long-term (up to 10 years) prognostic factors following AMI in "real world" patients, focusing on improving risk stratification of elderly patients.
  
  
  METHODS
  A retrospective analysis of 2763 consecutive AMI patients according to age groups: ≤65 years (n=1230) and >65 years (n=1533). Data were collected from the hospital's computerized systems. The primary outcome was 10-year postdischarge all-cause mortality.
  
  
  RESULTS
  Higher rates of women, non-ST-elevation AMI, and most comorbidities were found in elderly patients, while the rates of invasive treatment were lower. During the follow-up period, mortality rate was higher among the older versus the younger group (69.7% versus 18.6%). Some of the parameters included in the interaction multivariate model had stronger association with the outcome in the younger group (hyponatremia, anemia, alcohol abuse or drug addiction, malignant neoplasm, renal disease, previous myocardial infarction, and invasive interventions) while others were stronger predictors in the elderly group (higher age, left main coronary artery or three-vessel disease, and neurological disorders). The c-statistic values of the multivariate models were 0.75 and 0.74 in the younger and the elder groups, respectively, and 0.86 for the interaction model.
  
  
  CONCLUSIONS
  Long-term mortality following AMI in young as well as elderly patients can be predicted from simple, easily accessible clinical information. The associations of most predictors and mortality were stronger in younger patients. These predictors can be used for optimizing patient care aiming at mortality reduction.
authors.affiliation: Nursing Research Unit, Soroka University Medical Center, Beer-Sheva, Israel; Recanati School for Community Health Professions, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel. Electronic address: Plakht@exchange.bgu.ac.il.
authors.forename: Ygal
authors.initials: Y
authors.lastname: Plakht
authors.affiliation: Department of Internal Medicine E, Rabin Medical Center, Beilinson Hospital, Petah-Tikva, Israel.
authors.forename: Arthur
authors.initials: A
authors.lastname: Shiyovich
authors.affiliation: Department of Cardiology, Soroka University Medical Center, Beer-Sheva, Israel.
authors.forename: Harel
authors.initials: H
authors.lastname: Gilutz
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002423:Cause of Death; D015897:Comorbidity; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009203:Myocardial Infarction / Q000401:mortality*; D012189:Retrospective Studies; D012307:Risk Factors; D012737:Sex Factors; D016019:Survival Analysis; D013997:Time Factors
keywords: Acute myocardial infarction; Age-related differences; All-cause mortality; Long-term risk stratification; Prediction