Clinical study: myocardial infarction
Development and validation of the ontario acute myocardial infarction mortality prediction rules

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Abstract

OBJECTIVES

To develop and validate simple statistical models that can be used with hospital discharge administrative databases to predict 30-day and one-year mortality after an acute myocardial infarction (AMI).

BACKGROUND

There is increasing interest in developing AMI “report cards” using population-based hospital discharge databases. However, there is a lack of simple statistical models that can be used to adjust for regional and interinstitutional differences in patient case-mix.

METHODS

We used linked administrative databases on 52,616 patients having an AMI in Ontario, Canada, between 1994 and 1997 to develop logistic regression statistical models to predict 30-day and one-year mortality after an AMI. These models were subsequently validated in two external cohorts of AMI patients derived from administrative datasets from Manitoba, Canada, and California, U.S.

RESULTS

The 11-variable Ontario AMI mortality prediction rules accurately predicted mortality with an area under the receiver operating characteristic (ROC) curve of 0.78 for 30-day mortality and 0.79 for one-year mortality in the Ontario dataset from which they were derived. In an independent validation dataset of 4,836 AMI patients from Manitoba, the ROC areas were 0.77 and 0.78, respectively. In a second validation dataset of 112,234 AMI patients from California, the ROC areas were 0.77 and 0.78 respectively.

CONCLUSIONS

The Ontario AMI mortality prediction rules predict quite accurately 30-day and one-year mortality after an AMI in linked hospital discharge databases of AMI patients from Ontario, Manitoba and California. These models may also be useful to outcomes and quality measurement researchers in other jurisdictions.

Abbreviations

AMI
acute myocardial infarction
ICD
International Classification of Diseases
OMID
Ontario Myocardial Infarction Database
OR
odds ratio
ROC
receiver operating characteristic
TECH
Technological Change in Health Care

Cited by (0)

Supported in part by an operating grant from the Canadian Institutes of Health Research, the National Institute on Aging, TECH grant AG17154, and the Heart and Stroke Foundation of Manitoba. Dr. Tu is supported by a Canada Research Chair in Health Services Research.