Exercise electrocardiography for pre-test assessment of the likelihood of coronary artery disease

Objectives: To develop a tool including exercise electrocardiography (ExECG) for patient-specific clinical likelihood estimation of patients with suspected obstructive coronary artery disease (CAD). Methods: An ExECG-weighted clinical likelihood (ExECG-CL) model was developed in a training cohort of patients with suspected obstructive CAD undergoing ExECG. Next, the ExECG-CL model was applied in a CAD validation cohort undergoing ExECG and clinically driven invasive coronary angiography and a prognosis validation cohort and compared with the risk factor-weighted clinical likelihood (RF-CL) model for obstructive CAD discrimination and prognostication, respectively. In the CAD validation cohort, obstructive CAD was defined as >50% diameter stenosis on invasive coronary angiography. For prognosis, the endpoint was non-fatal myocardial infarction and death. Results: The training cohort consisted of 1214 patients. In the CAD (N=408; mean age 55 years, 53% males) and prognosis validation cohorts, 11.8% patients had obstructive CAD and 4.4% met the endpoint. In the CAD validation cohort, discrimination of obstructive CAD was similar between the ExECG-CL and RF-CL models: area under the receiver-operating characteristic curves 83.1% versus 80.7%, p=0.14. In the ExECG-CL model, more patients had very low clinical likelihood of obstructive CAD compared with the RF-CL where obstructive CAD prevalence and event risk remained low. Conclusions: ExECG incorporated into a clinical likelihood model improves reclassification of patients to a very low clinical likelihood group with very low prevalence of obstructive CAD and favourable prognosis.