Trends in survival of hospitalized myocardial infarction patients between 1970 and 1985. The Minnesota Heart Survey

Circulation. 1992 Jan;85(1):172-9. doi: 10.1161/01.cir.85.1.172.

Abstract

Background: The Minnesota Heart Survey is a population-based study designed to monitor and explain trends in cardiovascular mortality, morbidity, and risk factors. As part of this effort, a 50% sample of patients hospitalized for myocardial infarction (MI) in the seven-county Twin Cities (Minneapolis and St. Paul) metropolitan area was reviewed in 1970, 1980, and 1985. Those with a validated definite MI were followed for 4-year mortality. The purpose was to determine whether the improved survival observed between 1970 and 1980 was extended to the 1980-1985 period.

Methods and results: Crude 28-day mortality in men changed from 18% in 1970 to 12% in 1980 to 13% in 1985; in women it changed from 27% in 1970 to 22% in 1980 to 18% in 1985. After adjustment for severity factors (e.g., age, previous MI, and admission heart rate and systolic blood pressure), 28-day mortality was significantly lower in 1980 than in 1970 in men (RR, 0.66; 95% CI, 0.47, 0.92) and in women (RR, 0.69; 95% CI, 0.46, 1.04), but no change occurred from from 1980 to 1985 (p greater than 0.25). After adjustment for severity indicators, 4-year survival was better in 1980 than in 1970 for men (RR, 0.67; 95% CI, 0.54, 0.83) and for women (RR, 0.72; 95% CI, 0.54, 0.98), but there was no significant change from 1980 to 1985 (p greater than 0.25).

Conclusions: These results suggest that improvements in survival among hospitalized MI patients contributed to the overall decline in coronary heart disease mortality in the Twin Cities area between 1970 and 1980 but not between 1980 and 1985.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Aged
  • Cohort Studies
  • Delivery of Health Care / trends
  • Health Surveys*
  • Hospitalization*
  • Humans
  • Middle Aged
  • Minnesota
  • Myocardial Infarction / mortality*
  • Proportional Hazards Models
  • Sex Factors
  • Survival Analysis
  • Time Factors