Division of Cardiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
J Am Coll Cardiol. 2012 Oct 23;60(17):1617-22. doi: 10.1016/j.jacc.2012.07.026. Epub 2012 Sep 19.
We developed and internally validated a risk score to predict in-hospital stroke or death after carotid artery stenting (CAS).
A tool that accurately assesses CAS risk could aid clinical decision making and improve patient selection.
Patients undergoing CAS without acute evolving stroke from April 2005 through June 2011 as part of the NCDR Carotid Artery Revascularization and Endarterectomy (CARE) Registry were included. In-hospital stroke or death was modeled using logistic regression with 35 candidate variables. Internal validation was achieved with bootstrapping, and model discrimination and calibration were assessed.
A total of 271 (2.4%) primary endpoint events occurred during 11,122 procedures. Independent predictors of stroke or death included impending major surgery, previous stroke, age, symptomatic lesion, atrial fibrillation, and absence of previous ipsilateral carotid endarterectomy. The model was well calibrated with moderate discriminatory ability (C-statistic: 0.71) overall, and within symptomatic (C-statistic: 0.68) and asymptomatic (C-statistic: 0.72) subgroups. The inclusion of available angiographic variables did not improve model performance (C-statistic: 0.72, integrated discrimination improvement 0.001; p = 0.21). The NCDR CAS score was developed to support prospective risk quantification.
The NCDR CAS score, comprising 6 clinical variables, predicts in-hospital S/D after CAS. This tool may be useful to assist clinicians in evaluating optimal management, share more accurate pre-procedural risks with patients, and improve patient selection for CAS.
我们开发并内部验证了一种风险评分模型，用于预测颈动脉支架置入术（CAS）后住院期间的卒中或死亡风险。
一种能够准确评估 CAS 风险的工具可以辅助临床决策，并改善患者选择。
我们纳入了 2005 年 4 月至 2011 年 6 月期间作为 NCDR 颈动脉血管重建和内膜切除术（CARE）登记研究一部分的、接受 CAS 治疗且未发生急性进展性卒中的患者。使用逻辑回归对 35 个候选变量进行了住院期间卒中或死亡的建模。采用自举法进行内部验证，并评估了模型的区分度和校准度。
在 11122 例手术中，共有 271 例（2.4%）患者发生主要终点事件。卒中或死亡的独立预测因素包括即将进行的重大手术、既往卒中、年龄、症状性病变、心房颤动和同侧颈动脉内膜切除术的既往史。该模型总体上具有良好的校准度和中度的区分能力（C 统计量：0.71），在症状性（C 统计量：0.68）和无症状性（C 统计量：0.72）亚组中也是如此。纳入可用的血管造影变量并未改善模型性能（C 统计量：0.72，综合判别改善 0.001；p = 0.21）。NCDR CAS 评分旨在支持前瞻性风险量化。
NCDR CAS 评分由 6 个临床变量组成，可预测 CAS 后住院期间的 S/D 事件。该工具可能有助于辅助临床医生评估最佳治疗方案，与患者更准确地分享术前风险，并改善 CAS 的患者选择。
