Shao Yanqi, Zhang Zheyu, Jin Bo, Xu Jingsi, Peng Deqing, Geng Yu, Zhang Jungen, Zhang Sheng
Center for Rehabilitation Medicine, Department of Neurology, People's Hospital of Hangzhou Medical College, Zhejiang Provincial People's Hospital, Hangzhou, China.
The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China.
Ther Adv Neurol Disord. 2022 Jun 30;15:17562864221104511. doi: 10.1177/17562864221104511. eCollection 2022.
Rapid recognition of acute stroke and large vessel occlusion (LVO) is essential in prehospital triage for timely reperfusion treatment.
This study aimed to develop and validate a new screening tool for both stroke and LVO in an urban Chinese population.
This study included patients with suspected stroke who were transferred to our hospital by emergency medical services between July 2017 and June 2021. The population was randomly partitioned into training (70%) and validation (30%) groups. The Staring-Hypertension-atrIal fibrillation-sPeech-weakneSs (SHIPS) scale, consisting of both clinical and medical history information, was generated based on multivariate logistic models. The predictive ability of the SHIPS scale was evaluated and compared with other scales using receiver operating characteristic (ROC) curve comparison analysis.
A total of 400 patients were included in this analysis. In the training group ( = 280), the SHIPS scale showed a sensitivity of 90.4% and specificity of 60.8% in predicting stroke and a sensitivity of 75% and specificity of 61.5% in predicting LVO. In the validation group ( = 120), the SHIPS scale was not inferior to Stroke 1-2-0 ( = 0.301) in predicting stroke and was significantly better than the Cincinnati Stroke Triage Assessment Tool (C-STAT; formerly CPSSS) and the Prehospital Acute Stroke Severity scale (PASS) (all < 0.05) in predicting LVO. In addition, including medical history in the scale was significantly better than using symptoms alone in detecting stroke (training group, 0.853 0.818; validation group, 0.814 0.764) and LVO (training group, 0.748 0.722; validation group, 0.825 0.778).
The SHIPS scale may serve as a superior screening tool for stroke and LVO identification in prehospital triage. Including medical history in the SHIPS scale improves the predictive value compared with clinical symptoms alone.
在院前分诊中快速识别急性卒中及大血管闭塞（LVO）对于及时进行再灌注治疗至关重要。
本研究旨在开发并验证一种针对中国城市人群的用于卒中及LVO的新型筛查工具。
本研究纳入了2017年7月至2021年6月期间由紧急医疗服务转运至我院的疑似卒中患者。将该人群随机分为训练组（70%）和验证组（30%）。基于多变量逻辑模型生成了包含临床和病史信息的凝视-高血压-心房颤动-言语-虚弱（SHIPS）量表。使用受试者操作特征（ROC）曲线比较分析评估SHIPS量表的预测能力，并与其他量表进行比较。
本分析共纳入400例患者。在训练组（n = 280）中，SHIPS量表预测卒中的灵敏度为90.4%，特异度为60.8%；预测LVO的灵敏度为75%，特异度为61.5%。在验证组（n = 120）中，SHIPS量表在预测卒中方面不劣于Stroke 1-2-0（P = 0.301），在预测LVO方面显著优于辛辛那提卒中分诊评估工具（C-STAT；原CPSSS）和院前急性卒中严重程度量表（PASS）（均P < 0.05）。此外，在量表中纳入病史在检测卒中（训练组，0.853对0.818；验证组，0.814对0.764）和LVO（训练组，0.748对0.722；验证组，0.825对0.778）方面明显优于仅使用症状。
SHIPS量表可作为院前分诊中用于识别卒中和LVO的一种更优筛查工具。与仅使用临床症状相比，在SHIPS量表中纳入病史可提高预测价值。
