Validating the SMART2 Score in a Racially Diverse High‐Risk Nationwide Cohort of Patients Receiving Coronary Artery Bypass Grafting

Abstract

Background We tested the potential of the Secondary Manifestations of Arterial Disease (SMART2) risk score for use in patients undergoing coronary artery bypass grafting. Methods and Results We conducted an external validation of the SMART2 score in a racially diverse high‐risk national cohort (2010–2019) that underwent isolated coronary artery bypass grafting. We calculated the preoperative SMART2 score and modeled the 5‐year major adverse cardiovascular event (cardiovascular mortality+myocardial infarction+stroke) incidence. We evaluated SMART2 score discrimination at 5 years using c‐statistic and calibration with observed/expected ratio and calibration plots. We analyzed the potential clinical benefit using decision curves. We repeated these analyses in clinical subgroups, diabetes, chronic kidney disease, and polyvascular disease, and separately in White and Black patients. In 27 443 (mean age, 65 years; 10% Black individuals) US veterans undergoing coronary artery bypass grafting (2010–2019) nationwide, the 5‐year major adverse cardiovascular event rate was 25%; 27% patients were in high predicted risk (>30% 5‐year major adverse cardiovascular events). SMART2 score discrimination (c‐statistic: 64) was comparable to the original study (c‐statistic: 67) and was best in patients with chronic kidney disease (c‐statistic: 66). However, it underpredicted major adverse cardiovascular event rates in the whole cohort (observed/expected ratio, 1.45) as well as in all studied subgroups. The SMART2 score performed better in White than Black patients. On decision curve analysis, the SMART2 score provides a net benefit over a wide range of risk thresholds. Conclusions The SMART2 model performs well in a racially diverse coronary artery bypass grafting cohort, with better predictive capabilities at the upper range of baseline risk, and can therefore be used to guide secondary preventive pharmacotherapy.

Keywords

• atherosclerotic vascular disease
• coronary artery bypass grafting
• coronary artery disease
• external validation
• myocardial infarction
• risk prediction