Specific comorbidity risk adjustment was a better predictor of 5-year acute myocardial infarction mortality than general methods

Abstract 

Objective

To compare methods of risk adjustment in a population of individuals with acute myocardial infarction (AMI), in order to assist clinicians in assessing patient prognosis.

Study Design and Setting

A historical inception cohort design was established, with follow-up of ≤5 years. A province-wide population-based administrative dataset from British Columbia, Canada, was used to select the cohort and construct variables. All individuals aged ≥66 years who had an AMI in 1994 or 1995 were selected (n = 4,874). The three risk-adjustment methods were the Ontario AMI prediction rule (OAMIPR), the D'Hoore adaptation of the Charlson Index, and the total number of distinct comorbidities. Logistic regression models were built including each of the adjustment methods, age, sex, socioeconomic status, previous AMI, and cardiac procedures at time of AMI.

Results

The OAMIPR had the highest C-statistic and R².

Conclusion

Clinicians are advised to consider the specific comorbidities that are present, not merely their number, and those that emerge over time, not merely those present at the time of the infarct.

Keywords: Cardiovascular disease, Cohort studies, Logistic models, Risk adjustment, ROC curve, Comorbidity