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SYSTEMATIC REVIEW article

Front. Neurol.
Sec. Artificial Intelligence in Neurology
Volume 15 - 2024 | doi: 10.3389/fneur.2024.1469079
This article is part of the Research Topic AI's Transformative Role in Neuro-Intervention: Enhancing Diagnosis and Treatment Strategies View all 3 articles

Meta-analysis of the Effectiveness of Virtual Reality Technology on Early Mobility in Adult Critically Ill Patients： A System review

Provisionally accepted
Sha Yan He Sha Yan He 1,2Hua Lei Hua Lei 2,3*Qin Yang Qin Yang 2,3*Xia Xiao Dai Xia Xiao Dai 2*Tian Chen Tian Chen 2*Huan Wu Huan Wu 2*Jie Kun Li Jie Kun Li 2*Qiong Shi Zhu Qiong Shi Zhu 1,3*Lin Yan Liu Lin Yan Liu 1*
  • 1 Chongzhou People's Hospital, Chengdu, China
  • 2 University of Electronic Science and Technology of China, Chengdu, Sichuan Province, China
  • 3 Sichuan Provincial People's Hospital, Chengdu, Sichuan, China, Chengdu, China

The final, formatted version of the article will be published soon.

    Objective: To explore the effects of virtual reality (VR) technology on motor function rehabilitation in critically ill patients. Methods: Adhering to the PRISMA systematic evaluation method to develop the literature ranking criteria and search strategy, the databases including PubMed, Embase, Web of Science, Cochrane Library, CNKI, WanFang, Chinese Medical Journal Full Text Database, SinoMed Database were systematically searched. The search focused on the impact of virtual reality technology on limb function rehabilitation in critically ill patients, covering the period from the database's inception to September 2, 2024. To evaluate the quality of the included studies, the risk of bias assessment tool, RevMan 5.4. Results: Eleven RCTs published over 10 years were included, with 880 critically ill adult patients: 435 in the experimental group and 445 in the control group. The metaanalysis showed that, compared with the control group, virtual reality technology significantly improved the Berg Balance Scale (BBS) scores of adult critically ill patients (MD = 3.95, 95% CI: 3.19, 4.70, P < 0.05), Functional Independence Measure (FIM) score (MD = 0.21, 95% CI: -1.35, 1.76, P > 0.05), Functional Ambulation Category (FAC) score (MD=0.72, 95% CI: 0.49, 0.94, P<0.05), upper limb motor function (Fugl-Meyer Assessment, FMA) score (MD=5.08, 95% CI: 3.46, 6.69, P<0.05), and lower limb motor function (Fugl-Meyer Assessment FMA) scores (MD = 2.83, 95% CI: 1.99, 3.67, P < 0.05).Compared with traditional conventional rehabilitation techniques, virtual reality technology has a better overall effect in improving motor rehabilitation in critically ill patients, which can improve balance, functional walking, and upper and lower limb motor function in critically ill patients. However, the effect of enhancing functional independence of limbs is not yet evident, and it still needs to be further confirmed by high-quality, multicenter, and large-sample clinical trial studies.

    Keywords: Prospero register No.: CRD42024546409 Virtual reality, VR, critically ill patients, Motor function, Meta-analysis, System review

    Received: 23 Jul 2024; Accepted: 30 Dec 2024.

    Copyright: © 2024 He, Lei, Yang, Dai, Chen, Wu, Li, Zhu and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Hua Lei, Sichuan Provincial People's Hospital, Chengdu, Sichuan, China, Chengdu, China
    Qin Yang, Sichuan Provincial People's Hospital, Chengdu, Sichuan, China, Chengdu, China
    Xia Xiao Dai, University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan Province, China
    Tian Chen, University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan Province, China
    Huan Wu, University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan Province, China
    Jie Kun Li, University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan Province, China
    Qiong Shi Zhu, Chongzhou People's Hospital, Chengdu, China
    Lin Yan Liu, Chongzhou People's Hospital, Chengdu, China

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