Department of Ultrasound Medicine, Zhejiang Provincial People's Hospital & People's Hospital of Hangzhou Medical College, Hangzhou, Zhejiang, China.
Emergency Center, Hubei Clinical Research Center for Emergency and Resuscitation, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.
Chest. 2021 Jan;159(1):270-281. doi: 10.1016/j.chest.2020.06.068. Epub 2020 Jul 9.
Traditional methods for cardiopulmonary assessment of patients with coronavirus disease 2019 (COVID-19) pose risks to both patients and examiners. This necessitates a remote examination of such patients without sacrificing information quality.
The goal of this study was to assess the feasibility of a 5G-based robot-assisted remote ultrasound system in examining patients with COVID-19 and to establish an examination protocol for telerobotic ultrasound scanning.
Twenty-three patients with COVID-19 were included and divided into two groups. Twelve were nonsevere cases, and 11 were severe cases. All patients underwent a 5G-based robot-assisted remote ultrasound system examination of the lungs and heart following an established protocol. Distribution characteristics and morphology of the lung and surrounding tissue lesions, left ventricular ejection fraction, ventricular area ratio, pericardial effusion, and examination-related complications were recorded. Bilateral lung lesions were evaluated by using a lung ultrasound score.
The remote ultrasound system successfully and safely performed cardiopulmonary examinations of all patients. Peripheral lung lesions were clearly evaluated. Severe cases of COVID-19 had significantly more diseased regions (median [interquartile range], 6.0 [2.0-11.0] vs 1.0 [0.0-2.8]) and higher lung ultrasound scores (12.0 [4.0-24.0] vs 2.0 [0.0-4.0]) than nonsevere cases of COVID-19 (both, P < .05). One nonsevere case (8.3%; 95% CI, 1.5-35.4) and three severe cases (27.3%; 95% CI, 9.7-56.6) were complicated by pleural effusions. Four severe cases (36.4%; 95% CI, 15.2-64.6) were complicated by pericardial effusions (vs 0% of nonsevere cases, P < .05). No patients had significant examination-related complications.
Use of the 5G-based robot-assisted remote ultrasound system is feasible and effectively obtains ultrasound characteristics for cardiopulmonary assessment of patients with COVID-19. By following established protocols and considering medical history, clinical manifestations, and laboratory markers, this system might help to evaluate the severity of COVID-19 remotely.
对 2019 年冠状病毒病(COVID-19)患者进行心肺评估的传统方法对患者和检查者都存在风险。这就需要对这些患者进行远程检查,同时不牺牲信息质量。
本研究的目的是评估基于 5G 的机器人辅助远程超声系统在检查 COVID-19 患者方面的可行性,并为远程机器人超声扫描建立检查方案。
共纳入 23 例 COVID-19 患者,分为非重症组 12 例和重症组 11 例。所有患者均按既定方案接受基于 5G 的机器人辅助远程超声系统的肺部和心脏检查。记录肺部和周围组织病变的分布特征和形态、左心室射血分数、心室面积比、心包积液和与检查相关的并发症。采用肺部超声评分评估双侧肺部病变。
远程超声系统成功、安全地对所有患者进行了心肺检查。外周肺部病变得到了清晰的评估。COVID-19 重症患者的病变区域明显更多(中位数[四分位间距],6.0[2.0-11.0]比 1.0[0.0-2.8]),肺部超声评分更高(12.0[4.0-24.0]比 2.0[0.0-4.0])(均 P<0.05)。1 例非重症患者(8.3%;95%CI,1.5-35.4)和 3 例重症患者(27.3%;95%CI,9.7-56.6)并发胸腔积液。4 例重症患者(36.4%;95%CI,15.2-64.6)并发心包积液(而非重症患者为 0%,P<0.05)。没有患者出现明显的与检查相关的并发症。
使用基于 5G 的机器人辅助远程超声系统是可行的,能够有效地获取 COVID-19 患者心肺评估的超声特征。通过遵循既定方案,并考虑病史、临床表现和实验室标志物,该系统可能有助于远程评估 COVID-19 的严重程度。