Wimmer Neil J, Spertus John A, Kennedy Kevin F, Anderson H Vernon, Curtis Jeptha P, Weintraub William S, Singh Mandeep, Rumsfeld John S, Masoudi Frederick A, Yeh Robert W
Brigham and Women's Hospital and Harvard Medical School, Boston, MA (N.J.W.).
Saint Luke's Mid-America Heart Institute, Kansas City, MO (J.A.S., K.F.K.).
J Am Heart Assoc. 2014 Jun 17;3(3):e000728. doi: 10.1161/JAHA.113.000728.
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.
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.
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.
评估颈动脉内膜切除术（CEA）的医院质量需要对病例组合不同的医院进行适当的风险调整。本研究的目的是开发并验证一种预测模型，以评估CEA术后院内发生卒中或死亡的风险，从而有助于评估医院质量。
纳入2005年至2013年在国家心血管数据注册库（NCDR）的颈动脉血运重建和内膜切除术（CARE）注册库中接受CEA且无急性进展性卒中的患者。采用分层逻辑回归对20个候选变量进行建模，并考虑医院层面的聚类，以分析院内卒中或死亡情况。通过自抽样法进行内部验证；评估模型的辨别力和校准情况。在12889例手术中，共发生213例（1.7%）主要终点事件。卒中或死亡的独立预测因素包括年龄、既往外周动脉疾病、糖尿病、既往冠状动脉疾病、有症状的颈动脉病变、对侧颈动脉闭塞或纽约心脏协会III或IV级心力衰竭。该模型校准良好，具有中等辨别能力（c统计量为0.65）。随后开发了NCDR CEA评分，以支持临床环境中简单的前瞻性风险量化。
包含7个临床变量的NCDR CEA评分可预测CEA术后院内卒中或死亡情况。该模型可用于估计CEA的医院风险调整后结局，并协助评估医院质量。
