A Proposed Clinical Model for Efficient Utilization of Invasive Coronary Angiography

Abstract

More than 1/4 of patients who undergo invasive coronary angiography are found to have no visible or nonobstructive (<50% stenosis) coronary artery disease (CAD). With the rapid evolution of noninvasive imaging for CAD diagnosis, avoiding invasive coronary angiography in patients unlikely to require coronary revascularization is desirable. We undertook to develop a clinical prediction tool to identify patients with a low likelihood of obstructive (> or =50% stenosis) CAD. The derivation cohort included 24,637 patients with a diagnosis of "stable angina" or "acute coronary syndrome" referred for first cardiac catheterization in the province of British Columbia, Canada. The model was validated using an external dataset from the province of Alberta and comprised 18,606 patients. Seven variables (female gender, age <50 years, atypical Canadian Cardiovascular Society angina class, absence of ST-segment change on electrocardiogram, lifelong nonsmoking, and absence of diabetes and hyperlipidemia) were associated with the angiographic finding of "no or nonobstructive CAD." The c-statistics for the derivation model were 0.76 and 0.74 using the validation dataset. In conclusion, this simple clinical prediction tool, applied to patients for whom determination of coronary anatomy was clinically indicated, identifies patients who have a low likelihood of obstructive CAD. The patient population identified by this tool may represent a population best suited to a noninvasive diagnostic strategy.