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Am J Med. 1997 Apr;102(4):350-6.

Development and validation of a clinical score to estimate the probability of coronary artery disease in men and women presenting with suspected coronary disease.

Author information

1
Department of Medicine, West Virginia University School of Medicine, Morgantown 26506, USA.

Abstract

PURPOSE:

Guidelines for the management of patients with suspected coronary disease have emphasized stratification into groups with low, intermediate, and high probability of significant coronary disease. Previously derived clinical prediction rules have been difficult to apply in clinical settings. The purpose of this study was to develop and validate a clinical score that facilitates this stratification process.

PATIENTS AND METHODS:

We performed a retrospective analysis of prospectively acquired data from 915 patients with suspected coronary disease and normal resting electrocardiograms who presented for exercise testing at a university hospital. All patients subsequently underwent coronary angiography. Analysis included logistic regression with significant coronary disease (> or = 1 vessel with a > or = 50% lesion) presence as the dependent variable and clinical variables as independent variables. From this analysis, a coronary disease score was developed to estimate prevalence of coronary disease from clinical variables. Validation of this score was performed in a separate prospectively acquired cohort of 348 patients.

RESULTS:

For the entire validation group, the prevalence of significant coronary disease was 16% (10/63) in the low probability group, 44% (86/195) in the intermediate probability group, and 69% (62/90) in the high probability group. Both men and women were stratified equally well into the 3 probability groups.

CONCLUSION:

The clinical score is an easily memorized and accurate method for categorizing patients with suspected but not proven coronary disease and normal resting electrocardiograms into clinically meaningful probability groups upon which decisions concerning appropriate diagnostic test selection could potentially be based.

PMID:
9217616
DOI:
10.1016/s0002-9343(97)00086-7
[Indexed for MEDLINE]

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