Predictors of long-term (10-year) mortality postmyocardial infarction: Age-related differences. Soroka Acute Myocardial Infarction (SAMI) Project

AbstractBackgroundCardiovascular 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.AimTo 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.MethodsA 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.ResultsHigher 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.ConclusionsLong-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