Background: Additional strategies are needed to refine the referral for diagnostic testing of symptomatic patients with suspected coronary artery disease (CAD). We aimed to compare various models... Show moreBackground: Additional strategies are needed to refine the referral for diagnostic testing of symptomatic patients with suspected coronary artery disease (CAD). We aimed to compare various models to predict hemodynamically obstructive CAD. Methods and results: Symptomatic patients with suspected CAD who underwent coronary artery calcium scoring (CACS) and sequential coronary computed tomography angiography (CCTA) and [O-15]H2O positron emission tomography (PET) myocardial perfusion imaging were analyzed. Obstructive CAD was defined as a suspected coronary artery stenosis on CCTA with myocardial ischemia on PET (absolute stress myocardial perfusion <= 2.4 mL/g/min in >= 1 segment). Three models were developed to predict obstructive CAD-induced myocardial ischemia using logistic regression analysis: (1) basic model: including age, sex and cardiac symptoms, (2) risk factor model: adding number of risk factors to the basic model, and (3) CACS model: adding CACS to the risk factor model. Model performance was evaluated using discriminatory ability with area under the receiver-operating characteristic curves (AUC). A total of 647 patients (mean age 62 +/- 9 years, 45% men) underwent CACS and sequential CCTA and PET myocardial perfusion imaging. Obstructive CAD with myocardial ischemia on PET was present in 151 (23%) patients. CACS was independently associated with myocardial ischemia (P < .001). AUC for the discrimination of ischemia for the CACS model was superior over the basic model and risk factor model (P < .001). Conclusions: Adding CACS to the model including age, sex, cardiac symptoms and number of risk factors increases the accuracy to predict obstructive CAD with myocardial ischemia on PET in symptomatic patients with suspected CAD. Show less
