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Systematic review and network meta-analysis of robot-assisted gait training on lower limb function in patients with cerebral palsy
OBJECTIVE: This study aimed to evaluate the effectiveness of robot-assisted gait training (RAGT) in treating lower extremity function in patients with cerebral palsy (CP) and compare the efficacy differences between different robotic systems. METHODS: PubMed, Web of Science, Cochrane Library, Embase...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10570202/ https://www.ncbi.nlm.nih.gov/pubmed/37495708 http://dx.doi.org/10.1007/s10072-023-06964-w |
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author | Wang, Yueying Zhang, Peipei Li, Chao |
author_facet | Wang, Yueying Zhang, Peipei Li, Chao |
author_sort | Wang, Yueying |
collection | PubMed |
description | OBJECTIVE: This study aimed to evaluate the effectiveness of robot-assisted gait training (RAGT) in treating lower extremity function in patients with cerebral palsy (CP) and compare the efficacy differences between different robotic systems. METHODS: PubMed, Web of Science, Cochrane Library, Embase, CNKI, VIP, CBM, and Wanfang databases were searched to collect randomized controlled trials of RAGT for lower extremity dysfunction in patients with CP from the time the databases were created until December 26, 2022. The D and E of Gross Motor Function Measure-88 (GMFM-88) assessed lower limb motor function. Berg Balance Scale (BBS) was used to assess balance function. Walking endurance and speed were assessed using the 6-minute walk test (6MWT) and walking speed. The modified Ashworth Scale (MAS) was used to assess the degree of muscle spasticity in the lower extremities. The Cochrane Risk Assessment Scale and the Physiotherapy Evidence Database (PEDro) scale were used for qualitative assessment in the studies included. RevMan 5.4 was used for data merging and statistical analysis. R 4.2.0 and ADDIS 1.16.8 were used to map the network relationships and to perform the network meta-analysis. RESULTS: A total of 14 studies were included in the review. The meta-analysis showed that RAGT significantly improved GMFM-88 D and E, BBS, and 6MWT scores in CP patients compared with conventional rehabilitation. However, for walking speed and MAS, the intervention effect of RAGT was insignificant. The network meta-analysis showed that the best probability ranking for the effect of the 3 different robots on the GMFM-88 D score was LokoHelp (P = 0.66) > Lokomat (P = 0.28) > 3DCaLT (P = 0.06) and the best probability ranking for the GMFM-88 E score was LokoHelp (P = 0.63) > 3DCaLT (P = 0.21) > Lokomat (P = 0.16). CONCLUSION: RAGT positively affects walking and balance function in patients with CP, while efficacy in improving gait speed and muscle spasticity is unknown. The best treatment among the different robots is LokoHelp. Future high-quality, long-term follow-up studies are needed to explore the clinical efficacy of RAGT in depth. |
format | Online Article Text |
id | pubmed-10570202 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-105702022023-10-14 Systematic review and network meta-analysis of robot-assisted gait training on lower limb function in patients with cerebral palsy Wang, Yueying Zhang, Peipei Li, Chao Neurol Sci Review Article OBJECTIVE: This study aimed to evaluate the effectiveness of robot-assisted gait training (RAGT) in treating lower extremity function in patients with cerebral palsy (CP) and compare the efficacy differences between different robotic systems. METHODS: PubMed, Web of Science, Cochrane Library, Embase, CNKI, VIP, CBM, and Wanfang databases were searched to collect randomized controlled trials of RAGT for lower extremity dysfunction in patients with CP from the time the databases were created until December 26, 2022. The D and E of Gross Motor Function Measure-88 (GMFM-88) assessed lower limb motor function. Berg Balance Scale (BBS) was used to assess balance function. Walking endurance and speed were assessed using the 6-minute walk test (6MWT) and walking speed. The modified Ashworth Scale (MAS) was used to assess the degree of muscle spasticity in the lower extremities. The Cochrane Risk Assessment Scale and the Physiotherapy Evidence Database (PEDro) scale were used for qualitative assessment in the studies included. RevMan 5.4 was used for data merging and statistical analysis. R 4.2.0 and ADDIS 1.16.8 were used to map the network relationships and to perform the network meta-analysis. RESULTS: A total of 14 studies were included in the review. The meta-analysis showed that RAGT significantly improved GMFM-88 D and E, BBS, and 6MWT scores in CP patients compared with conventional rehabilitation. However, for walking speed and MAS, the intervention effect of RAGT was insignificant. The network meta-analysis showed that the best probability ranking for the effect of the 3 different robots on the GMFM-88 D score was LokoHelp (P = 0.66) > Lokomat (P = 0.28) > 3DCaLT (P = 0.06) and the best probability ranking for the GMFM-88 E score was LokoHelp (P = 0.63) > 3DCaLT (P = 0.21) > Lokomat (P = 0.16). CONCLUSION: RAGT positively affects walking and balance function in patients with CP, while efficacy in improving gait speed and muscle spasticity is unknown. The best treatment among the different robots is LokoHelp. Future high-quality, long-term follow-up studies are needed to explore the clinical efficacy of RAGT in depth. Springer International Publishing 2023-07-26 2023 /pmc/articles/PMC10570202/ /pubmed/37495708 http://dx.doi.org/10.1007/s10072-023-06964-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Review Article Wang, Yueying Zhang, Peipei Li, Chao Systematic review and network meta-analysis of robot-assisted gait training on lower limb function in patients with cerebral palsy |
title | Systematic review and network meta-analysis of robot-assisted gait training on lower limb function in patients with cerebral palsy |
title_full | Systematic review and network meta-analysis of robot-assisted gait training on lower limb function in patients with cerebral palsy |
title_fullStr | Systematic review and network meta-analysis of robot-assisted gait training on lower limb function in patients with cerebral palsy |
title_full_unstemmed | Systematic review and network meta-analysis of robot-assisted gait training on lower limb function in patients with cerebral palsy |
title_short | Systematic review and network meta-analysis of robot-assisted gait training on lower limb function in patients with cerebral palsy |
title_sort | systematic review and network meta-analysis of robot-assisted gait training on lower limb function in patients with cerebral palsy |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10570202/ https://www.ncbi.nlm.nih.gov/pubmed/37495708 http://dx.doi.org/10.1007/s10072-023-06964-w |
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