Development of new risk score for pre-test probability of obstructive coronary artery disease based on coronary CT angiography.

Abstract

Existing methods to calculate pre-test probability of obstructive coronary artery disease (CAD) have been established using selected high-risk patients who were referred to conventional coronary angiography. The purpose of this study is to develop and validate our new method for pre-test probability of obstructive CAD using patients who underwent coronary CT angiography (CTA), which could be applicable to a wider range of patient population. Using consecutive 4137 patients with suspected CAD who underwent coronary CTA at our institution, a multivariate logistic regression model including clinical factors as covariates calculated the pre-test probability (K-score) of obstructive CAD determined by coronary CTA. The K-score was compared with the Duke clinical score using the area under the curve (AUC) for the receiver-operating characteristic curve. External validation was performed by an independent sample of 319 patients. The final model included eight significant predictors: age, gender, coronary risk factor (hypertension, diabetes mellitus, dyslipidemia, smoking), history of cerebral infarction, and chest symptom. The AUC of the K-score was significantly greater than that of the Duke clinical score for both derivation (0.736 vs. 0.699) and validation (0.714 vs. 0.688) data sets. Among patients who underwent coronary CTA, newly developed K-score had better pre-test prediction ability of obstructive CAD compared to Duke clinical score in Japanese population.