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Optimal dosage ranges of various exercise types for enhancing timed up and go performance in Parkinson's disease patients: a systematic review and Bayesian network meta-analysis.
Yuan, Yuan; Wang, JunYu; Wang, GuoTuan; Wang, Tao; Zhang, HaoYang; Fu, XueYing; Wu, LiHua; Chen, XiaoTian; Xia, Rui; Zhang, Lin; Lin, Shu-Cheng; Yang, Yong.
Afiliação
  • Yuan Y; Department of Physical Education, Kunsan National University, Gunsan-si, Jeollabuk-do, Republic of Korea.
  • Wang J; The School of Exercise and Health, Shanghai University of Sport, Shanghai, China.
  • Wang G; Institute of Physical Education, Henan University, Kaifeng, China.
  • Wang T; School of Physical Education and Health, Krasnoyarsk State Pedagogical University named after V.P., Krasnoyarsk City, Russia.
  • Zhang H; College of Physical Education and Health, Southwest University of Science and Technology, Mianyang, China.
  • Fu X; Institute of Physical Education, Henan University, Kaifeng, China.
  • Wu L; Institute of Physical Education, Henan University, Kaifeng, China.
  • Chen X; The Seventh Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China.
  • Xia R; Second Clinical Medical College, Wenzhou Medical University, Zhejiang, China.
  • Zhang L; Laboratory of Kinesiology and Rehabilitation, School of Physical Education and Sport, Chaohu University, Hefei, China.
  • Lin SC; Department of Rehabilitation, West China Hospital Sichuan University Jintang Hospital, Chengdu, China.
  • Yang Y; Department of Sport, Leisure and Health Management, Tainan University of Technology, Tainan City, Taiwan.
Front Aging Neurosci ; 16: 1399175, 2024.
Article em En | MEDLINE | ID: mdl-38988329
ABSTRACT

Objective:

To examine the dose-response relationship between specific types of exercise for alleviating Timed up and Go (TUG) in Parkinson's disease PD.

Design:

Systematic review and Bayesian network meta-analysis. Data sources PubMed, Medline, Embase, PsycINFO, Cochrane Library, and Web of Science were searched from inception until February 5th, 2024. Study

analysis:

Data analysis was conducted using R software with the MBNMA package. Effect sizes of outcome indicators were expressed as mean deviation (MD) and 95% confidence intervals (95% CrI). The risk of bias in the network was evaluated independently by two reviewers using ROB2.

Results:

A total of 73 studies involving 3,354 PD patients. The text discusses dose-response relationships in improving TUG performance among PD patients across various exercise types. Notably, Aquatic (AQE), Mix Exercise (Mul_C), Sensory Exercise (SE), and Resistance Training (RT) demonstrate effective dose ranges, with AQE optimal at 1500 METs-min/week (MD -8.359, 95% CI -1.398 to -2.648), Mul_C at 1000 METs-min/week (MD -4.551, 95% CI -8.083 to -0.946), SE at 1200 METs-min/week (MD -5.145, 95% CI -9.643 to -0.472), and RT at 610 METs-min/week (MD -2.187, 95% CI -3.161 to -1.278), respectively. However, no effective doses are found for Aerobic Exercise (AE), Balance Gait Training (BGT), Dance, and Treadmill Training (TT). Mind-body exercise (MBE) shows promise with an effective range of 130 to 750 METs-min/week and an optimal dose of 750 METs-min/week (MD -2.822, 95% CI -4.604 to -0.996). According to the GRADE system, the included studies' overall quality of the evidence was identified moderate level.

Conclusion:

This study identifies specific exercise modalities and dosages that significantly enhance TUG performance in PD patients. AQE emerges as the most effective modality, with an optimal dosage of 1,500 METs-min/week. MBE shows significant benefits at lower dosages, catering to patients with varying exercise capacities. RT exhibits a nuanced "U-shaped" dose-response relationship, suggesting an optimal range balancing efficacy and the risk of overtraining. These findings advocate for tailored exercise programs in PD management, emphasizing personalized prescriptions to maximize outcomes.Systematic Review Registration International Prospective Register of Systematic Reviews (PROSPERO) (CRD42024506968).
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article