Abstract
A major diagnostic challenge for cardiologists is to distinguish cardiac syndrome X (CSX) from obstructive coronary artery disease in women with typical angina and a positive exercise tolerance test (ETT). We performed this study to develop a scoring system that more accurately predicts CSX in this patient population. Data on 976 women with typical angina and a positive ETT who underwent coronary angiography at our center were randomly divided into derivation and validation datasets. We developed a backward stepwise logistic regression model that predicted the presence of CSX, and a scoring system was derived from it. The derivation dataset (809 patients) was calibrated by uing a Hosmer-Lemeshow goodness-of-fit test (8 degrees of freedom; χ(2)=12.9; P=0.115), and the area under the curve was 0.758. The validation dataset (167 patients) was calibrated in the same way (8 degrees of freedom; χ(2)=9.0; P=0.339), and the area under the curve was 0.782. Independent predictors of CSX were age <55 years; negative histories of smoking, diabetes mellitus, hyperlipidemia, hypertension, or familial premature coronary artery disease; and highly positive ETTs. A total score >9.5 was the optimal cutoff point for differentiating CSX from obstructive coronary artery disease. Our proposed scoring system is a simple, objective, and accurate system for distinguishing CSX from obstructive coronary artery disease in women with typical angina and positive ETTs. It may help determine which of these patients need invasive coronary angiograms or noninvasive tests like computed tomographic coronary angiography.