Chapman Smith Sherita N, Govindarajan Prasanthi, Padrick Matthew M, Lippman Jason M, McMurry Timothy L, Resler Brian L, Keenan Kevin, Gunnell Brian S, Mehndiratta Prachi, Chee Christina Y, Cahill Elizabeth A, Dietiker Cameron, Cattell-Gordon David C, Smith Wade S, Perina Debra G, Solenski Nina J, Worrall Bradford B, Southerland Andrew M
From the Departments of Neurology (S.N.C.S., M.M.P., J.M.L., P.M., C.Y.C., N.J.S., B.B.W., A.M.S.), Public Health Sciences (T.L.M., B.B.W., A.M.S.), and Emergency Medicine (D.G.P.), and Center for Telehealth (B.S.G., D.C.C.-G.), University of Virginia Health System, Charlottesville; Department of Neurology (S.N.C.S., P.M.), Virginia Commonwealth University Health System, Richmond, VA (current); Departments of Emergency Medicine (P.G., B.L.R.) and Neurology (K.K., E.A.C., C.D., W.S.S.), University of California, San Francisco Medical Center; and Department of Emergency Medicine (P.G.), Stanford University Medical Center, Palo Alto, CA (current).
Neurology. 2016 Jul 5;87(1):19-26. doi: 10.1212/WNL.0000000000002799. Epub 2016 Jun 8.
In this 2-center study, we assessed the technical feasibility and reliability of a low cost, tablet-based mobile telestroke option for ambulance transport and hypothesized that the NIH Stroke Scale (NIHSS) could be performed with similar reliability between remote and bedside examinations.
We piloted our mobile telemedicine system in 2 geographic regions, central Virginia and the San Francisco Bay Area, utilizing commercial cellular networks for videoconferencing transmission. Standardized patients portrayed scripted stroke scenarios during ambulance transport and were evaluated by independent raters comparing bedside to remote mobile telestroke assessments. We used a mixed-effects regression model to determine intraclass correlation of the NIHSS between bedside and remote examinations (95% confidence interval).
We conducted 27 ambulance runs at both sites and successfully completed the NIHSS for all prehospital assessments without prohibitive technical interruption. The mean difference between bedside (face-to-face) and remote (video) NIHSS scores was 0.25 (1.00 to -0.50). Overall, correlation of the NIHSS between bedside and mobile telestroke assessments was 0.96 (0.92-0.98). In the mixed-effects regression model, there were no statistically significant differences accounting for method of evaluation or differences between sites.
Utilizing a low-cost, tablet-based platform and commercial cellular networks, we can reliably perform prehospital neurologic assessments in both rural and urban settings. Further research is needed to establish the reliability and validity of prehospital mobile telestroke assessment in live patients presenting with acute neurologic symptoms.
在这项双中心研究中,我们评估了一种低成本、基于平板电脑的移动远程卒中方案用于救护车转运的技术可行性和可靠性,并假设美国国立卫生研究院卒中量表(NIHSS)在远程检查和床边检查之间能够以相似的可靠性进行评估。
我们在弗吉尼亚州中部和旧金山湾区这两个地理区域对移动远程医疗系统进行了试点,利用商业蜂窝网络进行视频会议传输。标准化患者在救护车转运过程中模拟预设的卒中场景,并由独立评估者进行评估,比较床边评估和远程移动远程卒中评估。我们使用混合效应回归模型来确定床边检查和远程检查之间NIHSS的组内相关性(95%置信区间)。
我们在两个地点共进行了27次救护车出诊,并成功完成了所有院前评估的NIHSS,没有出现严重的技术中断。床边(面对面)和远程(视频)NIHSS评分的平均差异为0.25(1.00至 -0.50)。总体而言,床边评估和移动远程卒中评估之间NIHSS的相关性为0.96(0.92 - 0.98)。在混合效应回归模型中,评估方法或地点之间的差异没有统计学上的显著差异。
利用低成本、基于平板电脑的平台和商业蜂窝网络,我们能够在农村和城市环境中可靠地进行院前神经学评估。需要进一步研究以确定院前移动远程卒中评估在出现急性神经症状的真实患者中的可靠性和有效性。