Circulation, Vol 66, 945-953, Copyright © 1982 by American Heart Association
L Goldman, EF Cook, N Mitchell, M Flatley, H Sherman, R Rosati, F Harrell, K Lee and PF Cohn
To determine the incremental value of the exercise test (ETT) for
diagnosing coronary artery disease (CAD), we derived a multivariate
logistic regression model for the pre-ETT prediction of CAD using data from
3840 patients at Duke University. We then applied the model to 324 patients
at the Brigham and Women's Hospital. Using seven clinical factors, the
multivariate model had an 84% overall predictive accuracy on both the
training (Duke) and the validation (Brigham) sets of patients. Three ETT
factors (ST-segment change in patients not taking digitalis, absence of
ST-segment change in patients taking digitalis, ETT stopped because of ECG
or blood pressure changes) had incremental, significant predictive power,
but overall predictive accuracy based on both clinical and ETT factors
improved only to 87%. When the ETT result was important enough to move the
probability of CAD across a potential therapeutic threshold, the direction
of the change in probability was correct only two-thirds of the time. Thus,
the ETT was of limited value in predicting the presence or absence of CAD
after other easily obtainable clinical data were taken into account.
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Incremental value of the exercise test for diagnosing the presence or absence of coronary artery disease
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