New Diagnostic Model Predicts Coronary Artery Disease

In heart failure patients, it may reduce the need for invasive diagnostic tests

THURSDAY, Aug. 31 (HealthDay News) -- In heart failure patients with left ventricular dysfunction, a new diagnostic model may provide an accurate baseline assessment of coronary artery disease and reduce the need for invasive tests, according to a study published in the August issue of the American Heart Journal.

David J. Whellan, M.D., of Jefferson Medical College in Philadelphia, and colleagues assessed data on 2,054 patients who underwent echocardiography with an ejection fraction less than 45 percent and subsequently underwent diagnostic cardiac catheterization.

The researchers found that 1,184 patients (58 percent) had coronary artery disease and that the most significant predictors were, in order of importance, history of myocardial infarction, age, diabetes mellitus, Q wave on echocardiogram, male sex and segmental wall motion abnormality.

"This is the first analysis of patients with left ventricular dysfunction to identify a statistical model that can define the pretest likelihood of significant coronary artery disease," the authors write. "The study incorporated clinical variables available to most clinicians at the time of making decisions for their new patients with heart failure regarding management and the need to proceed to diagnostic cardiac catheterization. Although there are clinical similarities between patients with and those without significant coronary artery disease, this study on more than 2,000 patients shows that it is possible to use a composite of findings to predict the likelihood of coronary artery disease with a high sensitivity and specificity."

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