Supplementary Material for: Development and validation of a prediction model for failure of the transfemoral approach of endovascular treatment for large vessel occlusion acute ischemic stroke.

Introduction: Extracranial vascular characteristics determine the accessibility of the large vessel intracranial occlusion for endovascular treatment (EVT) in acute ischemic stroke. We developed and validated a prediction model for failure of the transfemoral approach to aid clinical decision making regarding EVT.
Methods: A prediction model was developed from data of patients included in the Dutch multicenter MR CLEAN Registry (March 18th 2014 until June 15th 2016) with penalized logistic regression. Predictor variables were available prior to the EVT procedure and included age, hypertension and extracranial vascular characteristics assessed on baseline CTA. The prediction model was internally validated, temporally validated within a second MR CLEAN Registry cohort (June 15th 2016 until November 1st 2017) and updated by re-estimating the coefficients using the combined cohort.
Results: Failure of the transfemoral approach occurred in 7% of patients, in both cohorts (derivation cohort: n=887, median age 71 years, interquartile range [IQR] 60-80, 52% men; validation cohort: n=1111, median age 73 years, IQR 62-81, 51% men). The prediction model had a c-statistic of 0.81 (95%CI: 0.76-0.86) in the derivation cohort, 0.69 (95%CI: 0.62-0.75) at temporal validation, and 0.75 (95%CI: 0.71-0.79) in the final prediction model, with the following penalized β-coefficients for predictors age (per decade): 0.26, hypertension: -0.16, severe aortic arch elongation: 1.45, bovine aortic arch: 0.44, elongation of the supra-aortic arteries: 0.72, cervical ICA elongation: 0.44, and high-grade stenosis of the cervical ICA: 0.78.
Conclusion: Our prediction model showed good performance for prediction of failure to reach the intracranial occlusion by the transfemoral approach.

引言：颅外血管特征决定了急性缺血性卒中患者大血管颅内闭塞病变行血管内治疗（endovascular treatment, EVT）的操作可行性。本研究开发并验证了一款用于预测经股动脉入路失败的预测模型，以辅助EVT相关临床决策制定。
方法：本研究基于荷兰多中心MR CLEAN注册研究（2014年3月18日至2016年6月15日）纳入的患者数据，采用惩罚逻辑回归方法开发预测模型。预测变量均在EVT操作前即可获取，包括年龄、高血压以及基线CT血管造影（CTA）评估的颅外血管特征。该预测模型首先接受内部验证，随后在第二组MR CLEAN注册研究队列（2016年6月15日至2017年11月1日）中接受时间验证，并通过合并队列重新估计模型系数完成更新。
结果：两个队列中均有7%的患者出现经股动脉入路失败：建模队列共887例，中位年龄71岁，四分位距（interquartile range, IQR）60~80岁，男性占比52%；验证队列共1111例，中位年龄73岁，IQR 62~81岁，男性占比51%。建模队列中，该预测模型的C统计量为0.81（95%置信区间（confidence interval, CI）：0.76~0.86）；时间验证阶段的C统计量为0.69（95%CI：0.62~0.75）；最终更新后的预测模型C统计量为0.75（95%CI：0.71~0.79）。各预测变量对应的惩罚β系数如下：年龄（每增加10岁）：0.26，高血压：-0.16，重度主动脉弓延长：1.45，牛型主动脉弓：0.44，主动脉弓上动脉延长：0.72，颈段颈内动脉（ICA）延长：0.44，颈段颈内动脉重度狭窄：0.78。
结论：本研究开发的预测模型对经股动脉入路无法到达颅内闭塞病变的预测性能良好。