Platelet hyperreactivity and prognosis in survivors of myocardial infarction

N Engl J Med. 1990 May 31;322(22):1549-54. doi: 10.1056/NEJM199005313222201.


We tested the hypothesis that an increase in spontaneous aggregability of platelets in vitro predicts mortality and coronary events in patients who have survived a recent myocardial infarction. A cohort of 149 survivors of infarction entered our study three months after the index infarction and was followed for five years. At entry and at intervals of six months, spontaneous platelet aggregation (SPA) was tested and graded as positive (aggregation within 10 minutes), intermediate (aggregation after 10 to 20 minutes), or negative (no aggregation within 20 minutes). During follow-up, 6.4 percent (6 of 94) of the patients in the SPA-negative group died, as compared with 10.3 percent (3 of 29) in the SPA-intermediate group and 34.6 percent (9 of 26) in the SPA-positive group. As compared with the SPA-negative group, the SPA-intermediate group had a relative risk of death of 1.6 (95 percent confidence interval, 0.5 to 5.5) and the SPA-positive group had a risk of 5.4 (95 percent confidence interval, 2.2 to 13.4). At least one cardiac event (cardiac death or recurrent nonfatal myocardial infarction) occurred in 14.9 percent (14 of 94 patients) of the SPA-negative group, 24.1 percent (7 of 29) of the SPA-intermediate group, and 46.2 percent (12 of 26) of the SPA-positive group. A positive test result continued to have prognostic value throughout the five-year study. We conclude that spontaneous platelet aggregation in vitro is a useful biologic marker for the prediction of coronary events and mortality in this low-risk group of survivors of a myocardial infarction. A causal relation is suggested but not proved by our study.

MeSH terms

  • Biomarkers
  • Cohort Studies
  • Female
  • Humans
  • Male
  • Middle Aged
  • Myocardial Infarction / blood
  • Myocardial Infarction / mortality*
  • Platelet Aggregation*
  • Prognosis
  • Prospective Studies
  • Recurrence
  • Regression Analysis
  • Risk Factors


  • Biomarkers