Zhang Bowei, Zhao Wenbo, Wu Chuanjie, Wu Longfei, Hou Chengbei, Klomparens Kara, Ding Yuchuan, Li Chuanhui, Chen Jian, Duan Jiangang, Zhang Yunzhou, Chang Hong, Ji Xunming
Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China.
Center for Evidence-Based Medicine, Xuanwu Hospital of Capital Medical University, Beijing, China.
Front Neurol. 2021 Feb 16;12:622272. doi: 10.3389/fneur.2021.622272. eCollection 2021.
This study aimed to develop and validate a novel index to predict SAP for AIS patients who underwent endovascular treatment. A study was conducted in an advanced comprehensive stroke center from January 2013 to December 2019 aiming to develop and validate a novel index to predict SAP for AIS patients who underwent endovascular treatment. This cohort consisted of a total of 407 consecutively registered AIS patients who underwent endovascular therapy, which was divided into derivation and validation cohorts. Multiple blood parameters as well as demographic features, vascular risk factors, and clinical features were carefully evaluated in the derivation cohort. The independent predictors were obtained using multivariable logistic regression. The scoring system was generated based on the β-coefficients of each independent risk factor. Ultimately, a novel predictive model: the SDL index (stroke history, dysphagia, lymphocyte count < 1.00 × 10/μL) was developed. The SDL index showed good discrimination both in the derivation cohort (AUROC: 0.739, 95% confidence interval, 0.678-0.801) and the validation cohort (AUROC: 0.783, 95% confidence interval, 0.707-0.859). The SDL index was well-calibrated (Hosmer-Lemeshow test) in the derivation cohort ( = 0.389) and the validation cohort ( = 0.692). We therefore divided our population into low (SDL index = 0), medium (SDL index = 1), and high (SDL index ≥ 2) risk groups for SAP. The SDL index showed good discrimination when compared with two existing SAP prediction models. The SDL index is a novel feasible tool to predict SAP risk in acute ischemic stroke patients post endovascular treatment.
本研究旨在开发并验证一种新型指标，以预测接受血管内治疗的急性缺血性卒中（AIS）患者发生症状性颅内出血（SAP）的风险。2013年1月至2019年12月期间，在一家高级综合卒中中心开展了一项研究，旨在开发并验证一种新型指标，以预测接受血管内治疗的AIS患者发生SAP的风险。该队列共纳入407例连续登记的接受血管内治疗的AIS患者，分为推导队列和验证队列。在推导队列中，仔细评估了多个血液参数以及人口统计学特征、血管危险因素和临床特征。使用多变量逻辑回归获得独立预测因素。基于每个独立危险因素的β系数生成评分系统。最终，开发出一种新型预测模型：SDL指标（卒中病史、吞咽困难、淋巴细胞计数<1.00×10⁹/μL）。SDL指标在推导队列（曲线下面积[AUC]：0.739，95%置信区间，0.678 - 0.801）和验证队列（AUC：0.783，95%置信区间，0.707 - 0.859）中均显示出良好的区分能力。SDL指标在推导队列（ Hosmer-Lemeshow检验P值 = 0.389）和验证队列（ Hosmer-Lemeshow检验P值 = 0.692）中校准良好。因此，我们将研究人群分为SAP低风险组（SDL指标 = 0）、中风险组（SDL指标 = 1）和高风险组（SDL指标≥2）。与现有的两种SAP预测模型相比，SDL指标显示出良好的区分能力。SDL指标是预测血管内治疗后急性缺血性卒中患者SAP风险的一种新型可行工具。
