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Effects of Ten Different Exercise Interventions on Motor Function in Parkinson’s Disease Patients—A Network Meta-Analysis of Randomized Controlled Trials
Objective: The aim of this study was to evaluate ten exercise interventions (YOGA: yoga training, RT: resistance training, AQU: aquatic training, TAI: Taiji Qigong training, TRD: treadmill training, VR: virtual reality training, DANCE: musical dance training, WKT: walking training, CYC: cycling trai...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9221238/ https://www.ncbi.nlm.nih.gov/pubmed/35741584 http://dx.doi.org/10.3390/brainsci12060698 |
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author | Hao, Zikang Zhang, Xiaodan Chen, Ping |
author_facet | Hao, Zikang Zhang, Xiaodan Chen, Ping |
author_sort | Hao, Zikang |
collection | PubMed |
description | Objective: The aim of this study was to evaluate ten exercise interventions (YOGA: yoga training, RT: resistance training, AQU: aquatic training, TAI: Taiji Qigong training, TRD: treadmill training, VR: virtual reality training, DANCE: musical dance training, WKT: walking training, CYC: cycling training, BDJ: Baduanjin Qigong training) on motor function in Parkinson’s disease (PD) patients. Design: Through searching PubMed, Embase, Cochrane Library, Web of Science, and CNKI, only randomized controlled trials (RCTs) were collected to study the effects of the ten exercise interventions on motor function in patients with Parkinson’s disease. The included studies were evaluated for methodological quality by the Cochrane bias risk assessment tool. Results: The RCTs were collected between the earliest available date and April 2022. Sixty RCTs were included and the total sample size used in the study was 2859. The results of the network meta-analysis showed that DANCE can significantly improve patients’ Berg Balance Scale (BBS) (SUCRA = 78.4%); DANCE can significantly decline patients’ Unified Parkinson’s Disease Rating Scale score (UPDRS) (SUCRA = 72.3%) and YOGA can significantly decline patients’ Timed-Up-and-Go score (TUGT) (SUCRA = 78.0%). Conclusion: Based on the network meta-analysis and SUCRA ranking, we can state that dance, yoga, virtual reality training and resistance training offers better advantages than other exercise interventions for patients’ motor function. |
format | Online Article Text |
id | pubmed-9221238 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-92212382022-06-24 Effects of Ten Different Exercise Interventions on Motor Function in Parkinson’s Disease Patients—A Network Meta-Analysis of Randomized Controlled Trials Hao, Zikang Zhang, Xiaodan Chen, Ping Brain Sci Systematic Review Objective: The aim of this study was to evaluate ten exercise interventions (YOGA: yoga training, RT: resistance training, AQU: aquatic training, TAI: Taiji Qigong training, TRD: treadmill training, VR: virtual reality training, DANCE: musical dance training, WKT: walking training, CYC: cycling training, BDJ: Baduanjin Qigong training) on motor function in Parkinson’s disease (PD) patients. Design: Through searching PubMed, Embase, Cochrane Library, Web of Science, and CNKI, only randomized controlled trials (RCTs) were collected to study the effects of the ten exercise interventions on motor function in patients with Parkinson’s disease. The included studies were evaluated for methodological quality by the Cochrane bias risk assessment tool. Results: The RCTs were collected between the earliest available date and April 2022. Sixty RCTs were included and the total sample size used in the study was 2859. The results of the network meta-analysis showed that DANCE can significantly improve patients’ Berg Balance Scale (BBS) (SUCRA = 78.4%); DANCE can significantly decline patients’ Unified Parkinson’s Disease Rating Scale score (UPDRS) (SUCRA = 72.3%) and YOGA can significantly decline patients’ Timed-Up-and-Go score (TUGT) (SUCRA = 78.0%). Conclusion: Based on the network meta-analysis and SUCRA ranking, we can state that dance, yoga, virtual reality training and resistance training offers better advantages than other exercise interventions for patients’ motor function. MDPI 2022-05-27 /pmc/articles/PMC9221238/ /pubmed/35741584 http://dx.doi.org/10.3390/brainsci12060698 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Systematic Review Hao, Zikang Zhang, Xiaodan Chen, Ping Effects of Ten Different Exercise Interventions on Motor Function in Parkinson’s Disease Patients—A Network Meta-Analysis of Randomized Controlled Trials |
title | Effects of Ten Different Exercise Interventions on Motor Function in Parkinson’s Disease Patients—A Network Meta-Analysis of Randomized Controlled Trials |
title_full | Effects of Ten Different Exercise Interventions on Motor Function in Parkinson’s Disease Patients—A Network Meta-Analysis of Randomized Controlled Trials |
title_fullStr | Effects of Ten Different Exercise Interventions on Motor Function in Parkinson’s Disease Patients—A Network Meta-Analysis of Randomized Controlled Trials |
title_full_unstemmed | Effects of Ten Different Exercise Interventions on Motor Function in Parkinson’s Disease Patients—A Network Meta-Analysis of Randomized Controlled Trials |
title_short | Effects of Ten Different Exercise Interventions on Motor Function in Parkinson’s Disease Patients—A Network Meta-Analysis of Randomized Controlled Trials |
title_sort | effects of ten different exercise interventions on motor function in parkinson’s disease patients—a network meta-analysis of randomized controlled trials |
topic | Systematic Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9221238/ https://www.ncbi.nlm.nih.gov/pubmed/35741584 http://dx.doi.org/10.3390/brainsci12060698 |
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