Feasibility of a 5G-Based Robot-Assisted Remote Ultrasound System for Cardiopulmonary Assessment of Patients With Coronavirus Disease 2019
Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved..
BACKGROUND: 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.
RESEARCH QUESTION: 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.
STUDY DESIGN AND METHODS: 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.
RESULTS: 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.
INTERPRETATION: 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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:159 |
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| Enthalten in: |
Chest - 159(2021), 1 vom: 01. Jan., Seite 270-281 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Ye, Ruizhong [VerfasserIn] |
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| Links: |
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| Themen: |
COVID-19 |
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| Anmerkungen: |
Date Completed 28.01.2021 Date Revised 28.01.2021 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.chest.2020.06.068 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM312302762 |
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| 100 | 1 | |a Ye, Ruizhong |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Feasibility of a 5G-Based Robot-Assisted Remote Ultrasound System for Cardiopulmonary Assessment of Patients With Coronavirus Disease 2019 |
| 264 | 1 | |c 2021 | |
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| 500 | |a Date Completed 28.01.2021 | ||
| 500 | |a Date Revised 28.01.2021 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved. | ||
| 520 | |a BACKGROUND: 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 | ||
| 520 | |a RESEARCH QUESTION: 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 | ||
| 520 | |a STUDY DESIGN AND METHODS: 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 | ||
| 520 | |a RESULTS: 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 | ||
| 520 | |a INTERPRETATION: 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a COVID-19 | |
| 650 | 4 | |a lung diseases | |
| 650 | 4 | |a robotics | |
| 650 | 4 | |a telemedicine | |
| 650 | 4 | |a ultrasound | |
| 700 | 1 | |a Zhou, Xianlong |e verfasserin |4 aut | |
| 700 | 1 | |a Shao, Fei |e verfasserin |4 aut | |
| 700 | 1 | |a Xiong, Linfei |e verfasserin |4 aut | |
| 700 | 1 | |a Hong, Jun |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Haijun |e verfasserin |4 aut | |
| 700 | 1 | |a Tong, Weiwei |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Jing |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Shuangxi |e verfasserin |4 aut | |
| 700 | 1 | |a Cui, Ailin |e verfasserin |4 aut | |
| 700 | 1 | |a Peng, Chengzhong |e verfasserin |4 aut | |
| 700 | 1 | |a Zhao, Yan |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Legao |e verfasserin |4 aut | |
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