Ali Syed F, Viswanathan Anand, Singhal Aneesh B, Rost Natalia S, Forducey Pamela G, Davis Lawrence W, Schindler Joseph, Likosky William, Schlegel Sherene, Solenski Nina, Schwamm Lee H
Massachusetts General Hospital/Harvard Medical School, Boston, MA (S.F.A., A.V., A.B.S., N.S.R., L.H.S.).
INTEGRIS Health, Oklahoma City, OK (P.G.F., L.W.D.).
J Am Heart Assoc. 2014 Jun 23;3(3):e000838. doi: 10.1161/JAHA.114.000838.
Up to 30% of acute stroke evaluations are deemed stroke mimics (SM). As telestroke consultation expands across the world, increasing numbers of SM patients are likely being evaluated via Telestroke. We developed a model to prospectively identify ischemic SMs during Telestroke evaluation.
We analyzed 829 consecutive patients from January 2004 to April 2013 in our internal New England-based Partners TeleStroke Network for a derivation cohort, and 332 cases for internal validation. External validation was performed on 226 cases from January 2008 to August 2012 in the Partners National TeleStroke Network. A predictive score was developed using stepwise logistic regression, and its performance was assessed using receiver-operating characteristic (ROC) curve analysis. There were 23% SM in the derivation, 24% in the internal, and 22% in external validation cohorts based on final clinical diagnosis. Compared to those with ischemic cerebrovascular disease (iCVD), SM had lower mean age, fewer vascular risk factors, more frequent prior seizure, and a different profile of presenting symptoms. The TeleStroke Mimic Score (TM-Score) was based on factors independently associated with SM status including age, medical history (atrial fibrillation, hypertension, seizures), facial weakness, and National Institutes of Health Stroke Scale >14. The TM-Score performed well on ROC curve analysis (derivation cohort AUC=0.75, internal validation AUC=0.71, external validation AUC=0.77).
SMs differ substantially from their iCVD counterparts in their vascular risk profiles and other characteristics. Decision-support tools based on predictive models, such as our TM Score, may help clinicians consider alternate diagnosis and potentially detect SMs during complex, time-critical telestroke evaluations.
高达30%的急性卒中评估被认为是类卒中（SM）。随着远程卒中会诊在全球范围内的扩展，越来越多的类卒中患者可能通过远程卒中进行评估。我们开发了一种模型，用于在远程卒中评估期间前瞻性地识别缺血性类卒中。
我们分析了2004年1月至2013年4月在我们位于新英格兰地区的内部合作伙伴远程卒中网络中的829例连续患者作为推导队列，并分析了332例用于内部验证。对2008年1月至2012年8月在合作伙伴国家远程卒中网络中的226例病例进行了外部验证。使用逐步逻辑回归开发了一个预测评分，并使用受试者操作特征（ROC）曲线分析评估其性能。根据最终临床诊断，推导队列中的类卒中为23%，内部验证队列中的为24%，外部验证队列中的为22%。与缺血性脑血管疾病（iCVD）患者相比，类卒中患者的平均年龄较低，血管危险因素较少，既往癫痫发作更频繁，且症状表现不同。远程卒中类卒中评分（TM评分）基于与类卒中状态独立相关的因素，包括年龄、病史（房颤、高血压、癫痫）、面部无力和美国国立卫生研究院卒中量表>14。TM评分在ROC曲线分析中表现良好（推导队列AUC = 0.75，内部验证AUC = 0.71，外部验证AUC = 0.77）。
类卒中在血管风险特征和其他特征方面与缺血性脑血管疾病患者有很大不同。基于预测模型的决策支持工具，如我们的TM评分，可能有助于临床医生考虑其他诊断，并在复杂、时间紧迫的远程卒中评估中潜在地检测出类卒中。
