最终卒中量表(USS)的验证:一种自动化大血管闭塞筛查的标准化工具。

IF 2.1 4区 医学 Q4 CLINICAL NEUROLOGY
Sachin A Kothari, Rami Z Morsi, Elena Badillo Goicoechea, Harsh Desai, Archit Baskaran, Ahmad Chahine, Matthew Smith, Ahmad Sweid, Olivia A Kozel, Sonam Thind, Scott J Mendelson, Rachel Mehendale, Elisheva R Coleman, Ali Mansour, James E Siegler, Shyam Prabhakaran, Tareq Kass-Hout
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引用次数: 0

摘要

院前卒中大血管闭塞(LVOs)筛查因机构而异。这项研究比较了手动中风量表计算和使用终极中风量表(USS)的电子计算得分,最终中风量表(USS)是一种自动化多个筛选量表的软件,这些量表来自改良的美国国立卫生研究院中风量表(NIHSS)。USS旨在通过同时计算多个有效的中风量表来简化筛选,以提高预测价值。方法应用脑卒中筛查量表(NIHSS;平衡,眼睛,脸,手臂,语言和时间;视力,失语,忽视;洛杉矶汽车量表(LAMS);面部、手臂、言语、时间、眼睛偏差和否认/忽视;紧急医疗服务快速动脉闭塞评估[EMS RACE]3项行程量表[3-ISS];院前急性卒中严重程度[PASS])到2021年1月至2023年12月期间的199例卒中激活。在这项前瞻性的外部验证研究中,数据来自先前发表的对LVO和中度血管闭塞的多个LVO量表的头对头比较,这些量表是手动收集的。我们使用USS重新计算这些量表,并评估一致性(Kendall τ)和诊断准确性(ROC曲线)。结果通过Kendall τ相关系数在0.549 ~ 0.931之间(均为p
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Validation of the Ultimate Stroke Scale (USS): A standardized tool for automated large vessel occlusion screening.

BackgroundPrehospital stroke screening for large vessel occlusions (LVOs) varies across institutions. This study compares manual stroke scale calculations against e-calculated scores using the Ultimate Stroke Scale (USS), a software automating multiple screening scales from a modified National Institutes of Health Stroke Scale (NIHSS) with a hand grip. The USS aims to streamline screening by computing multiple validated stroke scales simultaneously to enhance predictive value.MethodsWe applied eight stroke screening scales (NIHSS; Balance, Eyes, Face, Arms, Speech, and Time [BE-FAST]; Vision, Aphasia, Neglect; Los Angeles Motor Scale [LAMS]; Face, Arm, Speech, Time, Eye Deviation and Denial/Neglect [FAST-ED]; Emergency Medical Services Rapid Arterial oCclusion Evaluation [EMS RACE]; 3-Item Stroke Scale [3-ISS]; and Prehospital Acute Stroke Severity [PASS]) to 199 stroke activations between January 2021 and December 2023. In this prospective, external validation study, data were utilized from a previously published head-to-head comparison of multiple LVO scales for both LVOs and medium vessel occlusions which collected scales manually. We recalculated these scales using the USS and evaluated agreement (Kendall's τ) and diagnostic accuracy (ROC curves).ResultsThe USS showed strong to moderate agreement with manual calculations across all scales displayed by Kendall's τ correlation coefficients ranging from 0.549 to 0.931 (all p < 0.001). The BE-FAST had the lowest agreement (τ = 0.549), while PASS had the highest (τ = 0.931), followed by LAMS (τ = 0.894) and FAST-ED (τ = 0.864). Diagnostic accuracy was comparable between manual methods (area under the curve [AUC]: 0.590-0.743) and the USS (AUC: 0.575-0.758). The BE-FAST had the lowest AUC for both, LAMS had the highest for manual, and FAST-ED had the highest from the USS.ConclusionThe USS demonstrates potential as a reliable tool for automated stroke screening with consistent performance compared to manual methods.

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来源期刊
Interventional Neuroradiology
Interventional Neuroradiology CLINICAL NEUROLOGY-RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
CiteScore
3.60
自引率
11.80%
发文量
192
审稿时长
6-12 weeks
期刊介绍: Interventional Neuroradiology (INR) is a peer-reviewed clinical practice journal documenting the current state of interventional neuroradiology worldwide. INR publishes original clinical observations, descriptions of new techniques or procedures, case reports, and articles on the ethical and social aspects of related health care. Original research published in INR is related to the practice of interventional neuroradiology...
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