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J Clin Epidemiol. 1997 Aug;50(8):947-52.

Diagnostic interpretation of electrocardiograms in population-based research: computer program research physicians, or cardiologists?

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  • 1Department of Epidemiology and Biostatistics, Erasmus University Medical School, Rotterdam, Netherlands.

Abstract

We assessed the performance of diagnostic electrocardiogram (ECG) interpretation by the computer program MEANS and by research physicians, compared to cardiologists, in a physician-based study. To establish a strategy for ECG interpretation in health surveys, we also studied the diagnostic capacity of three scenarios: use of the computer program alone (A), computer program and cardiologist (B), and computer program, research physician, and cardiologist (C). A stratified random sample of 381 ECGs was drawn from ECGs collected in the Rotterdam Study (n = 3057), which were interpreted both by a trained research physician using a form for structured clinical evaluation and by MEANS. All ECGs were interpreted independently by two cardiologists; if they disagreed (n = 175) the ECG was judged by a third cardiologist. Five ECG diagnoses were considered: anterior and inferior myocardial infarction (MI), left and right bundle branch block (LBBB and RBBB), and left ventricular hypertrophy (LVH). Overall, sensitivities and specificities of MEANS and the research physicians were high. The sensitivity of MEANS ranged from 73.8% to 92.9% and of the research physician ranged from 71.8% to 96.9%. The specificity of MEANS ranged from 97.5% to 99.8% and of the research physician from 96.3% to 99.6%. To diagnose LVH, LBBB, and RBBB, use of the computer program alone gives satisfactory results. Preferably, all positive findings of anterior and inferior MI by the program should be verified by a cardiologist. We conclude that diagnostic ECG interpretation by computer can be very helpful in population-based research, being at least as good as ECG interpretation by a trained research physician, but much more efficient and therefore less expensive.

PMID:
9291880
[PubMed - indexed for MEDLINE]
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