Predictive Score of Adverse Events After Carotid Endarterectomy: The NSQIP Registry Carotid Endarterectomy Scale

Abstract

Background The goal of this study was to create a comprehensive, integer‐weighted predictive scale of adverse events after carotid endarterectomy ( CEA ), which may augment risk stratification and patient counseling. Methods and Results The targeted carotid files from the prospective NSQIP (National Surgical Quality Improvement Program) registry (2011–2013) comprised the derivation population. Multivariable logistic regression evaluated predictors of a 30‐day adverse event (stroke, myocardial infarction, or death), the effect estimates of which were used to build a weighted predictive scale that was validated using the 2014 to 2015 NSQIP registry release. A total of 10 766 and 8002 patients were included in the derivation and the validation populations, in whom 4.0% and 3.7% developed an adverse event, respectively. The NSQIP registry CEA scale included 14 variables; the highest points were allocated for insulin‐dependent diabetes mellitus, high‐risk cardiac physiological characteristics, admission source other than home, an emergent operation, American Society of Anesthesiologists’ classification IV to V, modified Rankin Scale score ≥2, and presentation with a stroke. NSQIP registry CEA score was predictive of an adverse event (concordance=0.67), stroke or death (concordance=0.69), mortality (concordance=0.76), an extended hospitalization (concordance=0.73), and a nonroutine discharge (concordance=0.83) in the validation population, as well as among symptomatic and asymptomatic subgroups ( P <0.001). In the validation population, patients with an NSQIP registry CEA scale score >8 and 17 had 30‐day stroke or death rates >3% and 6%, the recommended thresholds for asymptomatic and symptomatic patients, respectively. Conclusions The NSQIP registry CEA scale predicts adverse outcomes after CEA and can risk stratify patients with both symptomatic and asymptomatic carotid stenosis using different thresholds for each population.