Twenty-eight day and one-year case fatality after hospitalisation with an acute coronary syndrome: a nationwide data linkage study

Aust N Z J Public Health. 2014 Jun;38(3):216-20. doi: 10.1111/1753-6405.12241.

Abstract

Objectives: To determine 28-day and one-year case fatality in patients hospitalised with acute coronary syndromes (ACS) and identify factors associated with mortality.

Methods: All New Zealand residents admitted with ACS between 2007 and 2009 were followed for one year using individual patient linkage of national hospitalisation and mortality datasets. Deaths from any cause were used to calculate 28-day and one-year case fatality. Cox-proportional hazards models were constructed to identify factors associated with mortality after an ACS hospitalisation.

Results: The cohort included 42,920 ACS patients. Case fatality increased steeply with age. Māori and Pacific peoples had 1.5 times the risk of 28-day, and twice the risk of one-year, mortality as Europeans/Others. Low (compared to high) socioeconomic status was associated with significantly higher mortality at 28 days but not one year. Patients with unstable angina had half the risk of short-term mortality as NSTEMI patients, whereas STEMI patients had double the NSTEMI risk.

Conclusions and implications: The major determinant of increasing case fatality was increasing age. There were also substantial differences in case fatality by ethnicity, deprivation and diagnostic category. Further research is needed to explore the possible mechanisms by which ethnic and deprivation disparities occur and effective strategies to address them.

Keywords: acute coronary syndrome; case fatality; mortality; myocardial infarction.

MeSH terms

  • Acute Coronary Syndrome / ethnology*
  • Acute Coronary Syndrome / mortality*
  • Adult
  • Age Distribution
  • Cause of Death*
  • Data Collection
  • Female
  • Follow-Up Studies
  • Hospitalization / statistics & numerical data*
  • Humans
  • Incidence
  • Male
  • New Zealand / epidemiology
  • Proportional Hazards Models
  • Registries
  • Risk Factors
  • Sex Distribution
  • Socioeconomic Factors
  • Time Factors