Design and Validation of a Novel Evaluation Scale to Predict Inpatient Large Vessel Occlusion Strokes: Clinical Assessment Stroke Severity for Inpatient Scale

医学 接收机工作特性 冲程(发动机) 逻辑回归 心房颤动 曲线下面积 预测值 试验预测值 比例(比率) 急诊医学 闭塞 内科学 心脏病学 地图学 地理 工程类 机械工程
作者
Kai Qiu,Ke Wei,Zhenyu Jia,Sheng Liu
出处
期刊:Journal of Computer Assisted Tomography [Lippincott Williams & Wilkins]
卷期号:47 (5): 806-810
标识
DOI:10.1097/rct.0000000000001476
摘要

A large quantity of ischemic stroke events occur in patients hospitalized for non-stroke-related reason. No scale has been developed to identify the large vessel occlusion (LVO) among inpatient stroke alerts. We aimed to develop a novel evaluation scale to predict LVO from in-hospital stroke alerts.Data from consecutive in-hospital stroke alerts were analyzed at a single high volume stroke center between January 2016 and October 2020. We developed a predictive scale based on the first half of patients (training group) using multivariate logistic regression and evaluated it in the remaining half of patients (validation group) adopting receiver operating curve. Receiver operating characteristics of the scale were analyzed to evaluate its value for the detection of LVO.A total of 243 patients were enrolled for further study, among them, 94 (38.7%) had confirmed LVO. Three risk factors independently predicted the presence of LVO: recent cardiac or pulmonary procedure (1 point), neurological deficit scale (≥1: 2 points), and history of atrial fibrillation (1 point). The CAPS scale was generated based on predictive factors and demonstrated highly effective discrimination in identifying the presence of LVO in the training group (area under curve = 0.956) and the validation group (area under curve = 0.940). When the score ≥2, CAPS scale showed 97.9% sensitivity, 79.2% specificity, 74.8% positive predictive value, and 98.3% negative predictive value for discriminating LVO.CAPS scale was developed for identifying LVO among inpatient stroke alerts with high sensitivity and specificity, which may help to quickly prompt responses by appropriate stroke teams.
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