Do Patients with Multiple Sclerosis Derive More Benefit from Robot-Assisted Gait Training Compared with Conventional Walking Therapy on Motor Function? A Meta-analysis
To determine whether robot-assisted gait training (RAGT) is more effective in improving mobility, endurance, gait performance, and balance in patients with multiple sclerosis (MS) compared with conventional walking rehabilitation treatment (CWT).
Sources included the Cochrane Library, PubMed, Embase, and Science Direct databases.
All possible articles were retrieved by two independent investigators and relevant articles were gathered. Studies on adult patients (older than 19 years old) suffering from MS were included, regardless the subtype of MS diagnosis. Finally, we identified seven studies that comprised 205 patients with MS.
We identified seven studies comprising 205 patients with MS in our meta-analysis. The pooled mean difference (MD) for the six-minute walk test (6MWT) was 14.25 [95% confidence interval (CI) 3.19 to 25.32, Z = 2.53, P = 0.01, I(2) = 54%], which indicates that RAGT is superior to CWT on improving endurance. No significant improvement on using RAGT was found regarding the Berg Balance Scale (MD = -0.59, 95% CI: -2.7 to 1.52, Z = 0.55, P = 0.58, I(2) = 51%), 10-meter walk test [standard mean difference (SMD) = 0.03, 95% CI: -0.26 to 0.31, Z = 0.18, P = 0.86, I(2) = 48%] timed up and go (TUG) test (MD = -1.04, 95% CI: -8.68 to 6.60, Z = 0.27, P = 0.79), or stride length (SMD = 0.36, 95% CI: -0.13 to 0.85, Z = 0.73, P = 0.15).
We can conclude that RAGT can bring more benefits on improving 6MWT among MS patients, but it is not enough to make a clinically significance conclusion. Considering the limitation of our study, it takes reservations about recommending all MS patients to take RAGT as primary rehabilitation intervention. Unless patients with progressive MS can take conventional rehabilitation in early time, RAGT would be a suitable substitute.
This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 June 2021.
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