Wimmer NJ, Spertus JA, Kennedy KF, Anderson HV, Curtis JP, Weintraub WS, Singh M, Rumsfeld JS, Masoudi FA, Yeh RW
J Am Heart Assoc 2014 Jun;3(3):e000728
PMID: 24938712
Abstract
BACKGROUND: Assessing hospital quality in the performance of carotid endarterectomy (CEA) requires appropriate risk adjustment across hospitals with varying case mixes. The aim of this study was to develop and validate a prediction model to assess the risk of in-hospital stroke or death after CEA that could aid in the assessment of hospital quality.
METHODS AND RESULTS: Patients from National Cardiovascular Data Registry (NCDR)’s Carotid Artery Revascularization and Endarterectomy (CARE) Registry undergoing CEA without acute evolving stroke from 2005 to 2013 were included. In-hospital stroke or death was modeled using hierarchical logistic regression with 20 candidate variables and accounting for hospital-level clustering. Internal validation was achieved with bootstrapping; model discrimination and calibration were assessed. A total of 213 (1.7%) primary end point events occurred during 12 889 procedures. Independent predictors of stroke or death included age, prior peripheral artery disease, diabetes mellitus, prior coronary artery disease, having a symptomatic carotid lesion, having a contralateral carotid occlusion, or having New York Heart Association Class III or IV heart failure. The model was well calibrated and demonstrated moderate discriminative ability (c-statistic 0.65). The NCDR CEA score was then developed to support simple, prospective risk quantification in the clinical setting.
CONCLUSIONS: The NCDR CEA score, comprising 7 clinical variables, predicts in-hospital stroke or death after CEA. This model can be used to estimate hospital risk-adjusted outcomes for CEA and to assist with the assessment of hospital quality.