Department of Neurology, National Center for Neurological Disorders, National Clinical Research Centre for Aging and Medicine, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China.
South Western Sydney Clinical School, University of New South Wales, Liverpool, Australia.
CNS Neurosci Ther. 2022 Apr;28(4):531-539. doi: 10.1111/cns.13729. Epub 2021 Sep 24.
The aim of the study was to develop a simple and objective score using clinical variables and quantified perfusion measures to identify embolic stroke with large vessel occlusions.
Eligible patients from five centers participating in the International Stroke Perfusion Imaging Registry were included in this study. Patients were split into a derivation cohort (n = 213) and a validation cohort (n = 116). A score was developed according to the coefficients of independent predictors of embolic stroke from stepwise logistic regression model in the derivation cohort. The performance of the score was validated by assessing its discrimination and calibration.
The independent predictors of embolic stroke made up the Chinese Embolic Stroke Score (CHESS). There were: history of atrial fibrillation (3 points), non-hypertension history (2 points), and delay time>6 s volume/delay time>3 s volume on perfusion imaging ≥0.23 (2 points). The AUC of CHESS in the derivation cohort and validation cohort were 0.87 and 0.79, respectively. Patients with a CHESS of 0 could be identified as low-risk of embolic stroke, with a CHESS of 2-4 could be identified as medium-risk and with a CHESS of 5-7 could be regarded as high-risk. The observed rate of embolic stroke of each risk group was well-calibrated with the predicted rate.
CHESS could reliably and independently identify embolic stroke as the cause of large vessel occlusion.
本研究旨在利用临床变量和量化灌注指标开发一种简单且客观的评分，以识别伴有大血管闭塞的栓塞性卒中。
本研究纳入了来自参与国际卒中灌注成像登记研究的 5 个中心的合格患者。患者被分为推导队列（n=213）和验证队列（n=116）。根据推导队列中逐步逻辑回归模型中栓塞性卒中独立预测因子的系数，制定了评分。通过评估评分的判别能力和校准度来验证其性能。
构成中国栓塞性卒中评分（CHESS）的栓塞性卒中独立预测因子为：心房颤动史（3 分）、无高血压史（2 分）和灌注成像上延迟时间>6 s 容积/延迟时间>3 s 容积≥0.23（2 分）。推导队列和验证队列中 CHESS 的 AUC 分别为 0.87 和 0.79。CHESS 得分为 0 的患者可被识别为低风险栓塞性卒中，CHESS 得分为 2-4 可被识别为中风险，CHESS 得分为 5-7 可被视为高风险。每个风险组的观察到的栓塞性卒中发生率与预测率具有良好的校准度。
CHESS 可可靠且独立地识别大血管闭塞引起的栓塞性卒中。
