Prognostic estimation of coronary artery disease risk with resting perfusion abnormalities and stress ischemia on myocardial perfusion SPECT

Background. The extent and severity of stress ischemia are strong predictors of coronary artery disease (CAD) events. Prognosis associated with myocardial perfusion single photon emission computed tomography (MPS) abnormalities on the resting scan as it relates to stress ischemia has been incompletely described. Methods and Results. The Myoview Prognosis Registry was a prospective consecutive series of 7849 outpatients enrolled from 5 geographically diverse centers. Patients were followed up for the occurrence of CAD events (nonfatal myocardial infarction [MI] or death related to MI, heart failure, or sudden cardiac death). Time to CAD event (n=545) was estimated by use of univariable and multivariable Cox proportional hazards models (risk adjusted by symptoms, risk factors, and comorbid conditions). For patients with no resting defects, overall CAD event rates were 1.2%, 8%, and 10% for patients with 0% ischemic myocardium, 1% to 4.9% ischemic myocardium, and 5% ischemic myocardium or greater, respectively (P<.0001). As the percent myocardium with resting defects worsened, overall CAD event rates increased, such that for patients with 10% or more of the rest myocardium with perfusion defects, cardiovascular death or MI rates ranged from 7% to 44% (P<.0001). In a model including both the percent of the myocardium with resting defects and the percent ischemia, both were highly predictive of CAD events (P<.0001). For every 1% increase in ischemic myocardium, there was a 7% increased risk of CAD events (P<.0001). A 3% increase in risk of CAD events was observed for patients with every 1% of the myocardium with resting defects (P<.0001). Conclusions. The estimation of CAD risk may be optimally estimated by use of a combination of resting MPS, reflecting a patient’s burden of disease, and MPS with provocative ischemia. Partial unrestricted grant support for this project was provided by GE Healthcare.