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大型颅内血管闭塞对于血管内治疗（EVT）在急性缺血性卒中中的可及性。本研究开发并验证了一种预测模型，以预测股动脉入路失败，辅助临床决策关于EVT的实施。方法：从荷兰多中心MR CLEAN登记注册（2014年3月18日至2016年6月15日）的患者数据中，采用惩罚性逻辑回归方法开发了一种预测模型。预测变量在EVT手术前可用，包括年龄、高血压和基线CTA评估的颅外血管特征。预测模型进行了内部验证，并在第二个MR CLEAN登记注册队列（2016年6月15日至2017年11月1日）中进行时间验证，并通过重新估计系数来更新模型。结果：在两个队列中，股动脉入路失败的发生率均为7%（衍生队列：n=887，中位年龄71岁，四分位数间距[IQR] 60-80，男性52%；验证队列：n=1111，中位年龄73岁，IQR 62-81，男性51%）。在衍生队列中，预测模型的c统计量为0.81（95%CI：0.76-0.86），时间验证时为0.69（95%CI：0.62-0.75），最终预测模型为0.75（95%CI：0.71-0.79），预测变量的惩罚β系数如下：年龄（每十年）：0.26，高血压：-0.16，严重主动脉弓延长：1.45，牛型主动脉弓：0.44，上主动脉动脉延长：0.72，颈内动脉延长：0.44，颈内动脉高等级狭窄：0.78。结论：我们的预测模型在预测通过股动脉入路无法达到颅内闭塞方面表现出良好的性能。