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Efficacy of robot-assisted gait training on lower extremity function in subacute stroke patients: a systematic review and meta-analysis.
- Source :
-
Journal of NeuroEngineering & Rehabilitation (JNER) . 9/19/2024, Vol. 21 Issue 1, p1-15. 15p. - Publication Year :
- 2024
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Abstract
- Background: Robot-Assisted Gait Training (RAGT) is a novel technology widely employed in the field of neurological rehabilitation for patients with subacute stroke. However, the effectiveness of RAGT compared to conventional gait training (CGT) in improving lower extremity function remains a topic of debate. This study aimed to investigate and compare the effects of RAGT and CGT on lower extremity movement in patients with subacute stroke. Methods: Comprehensive search was conducted across multiple databases, including PubMed, Web of Science, Cochrane Library, EBSCO, Embase, Scopus, China National Knowledge Infrastructure, Wan Fang, SinoMed and Vip Journal Integration Platform. The database retrieval was performed up until July 9, 2024. Meta-analysis was conducted using RevMan 5.4 software. Results: A total of 24 RCTs were included in the analysis. The results indicate that, compared with CGT, RAGT led to significant improvements in the Fugl-Meyer Assessment for Lower Extremity [MD = 2.10, 95%CI (0.62, 3.59), P = 0.005], Functional Ambulation Category[MD = 0.44, 95%CI (0.23, 0.65), P < 0.001], Berg Balance Scale [MD = 4.55, 95%CI (3.00, 6.11), P < 0.001], Timed Up and Go test [MD = −4.05, 95%CI (−5.12, −2.98), P < 0.001], and 6-Minute Walk Test [MD = 30.66, 95%CI (22.36, 38.97), P < 0.001] for patients with subacute stroke. However, it did not show a significant effect on the 10-Meter Walk Test [MD = 0.06, 95%CI (−0.01, 0.14), P = 0.08]. Conclusions: This study provides evidence that RAGT can enhance lower extremity function, balance function, walking ability, and endurance levels compared to CGT. However, the quality of evidence for improvements in gait speed remains low. [ABSTRACT FROM AUTHOR]
- Subjects :
- *WALKING speed
*HINDLIMB
*STROKE
*STROKE patients
*DATABASES
Subjects
Details
- Language :
- English
- ISSN :
- 17430003
- Volume :
- 21
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Journal of NeuroEngineering & Rehabilitation (JNER)
- Publication Type :
- Academic Journal
- Accession number :
- 179738284
- Full Text :
- https://doi.org/10.1186/s12984-024-01463-1