The use of radionuclide angiography in the diagnosis of coronary artery disease--a logistic regression analysis.

Abstract

We applied logistic regression analysis to a group of 736 patients with chest pain to determine which radionuclide angiographic (RNA) parameters were most useful in the diagnosis of significant coronary artery disease. The most useful parameters were exercise ejection fraction, exercise heart rate, "ischemia score," and the presence of a regional wall motion abnormality at exercise. Ten clinical variables were used in one logistic regression model to estimate each patient's pretest probability of disease. A second logistic regression model considered these clinical variables and the four important RNA parameters to estimate each patient's posttest probability. These models were applied prospectively to a group of 76 patients with chest pain who did not have a high pretest probability of disease. Twenty-four patients (32%) could be diagnosed with 90% probability; 32 patients (42%) could be diagnosed with 85% probability. RNA testing is therefore helpful in the noninvasive diagnosis of coronary artery disease. However, a majority of patients who do have a low or intermediate pretest probability of disease will require additional testing for a definitive diagnosis.