Predictive values of acute coronary syndrome discharge diagnoses differed in the Danish National Patient Registry

J Clin Epidemiol. 2009 Feb;62(2):188-94. doi: 10.1016/j.jclinepi.2008.03.005. Epub 2008 Aug 22.


Objective: To investigate the predictive value of acute coronary syndrome (ACS) diagnoses, including unstable angina pectoris, myocardial infarction, and cardiac arrest, in the Danish National Patient Registry.

Study design and setting: We identified all first-time ACS diagnoses in the Danish National Patient Registry among participants in the Danish cohort study "Diet, Cancer and Health" through the end of 2003. We retrieved and reviewed medical records based on current European Society of Cardiology criteria for ACS.

Results: We reviewed hospital medical records of 1,577 out of 1,654 patients (95.3%) who had been hospitalized with a first-time ACS diagnosis. The overall positive predictive value for ACS was 65.5% (95% confidence interval [CI]=63.1-67.9%). Stratification by sub-diagnosis and hospital department produced significantly higher positive predictive values for myocardial infarction diagnoses (81.9%; 95% CI=79.5-84.2%) and among patients who received an ACS diagnosis in a ward (80.1%; 95% CI=77.7-82.3%).

Conclusion: The ACS diagnoses contained in hospital discharge registries should be used with caution. If validation is not possible, restricting analyses to patients with myocardial infarction and/or patients discharged from wards might be a useful alternative.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Acute Coronary Syndrome / diagnosis*
  • Acute Coronary Syndrome / epidemiology
  • Angina, Unstable / diagnosis*
  • Angina, Unstable / epidemiology
  • Cohort Studies
  • Denmark / epidemiology
  • Female
  • Heart Arrest / diagnosis*
  • Heart Arrest / epidemiology
  • Hospitalization
  • Humans
  • Male
  • Medical Audit
  • Medical Records
  • Middle Aged
  • Myocardial Infarction / diagnosis*
  • Myocardial Infarction / epidemiology
  • Predictive Value of Tests
  • Registries