BACKGROUND: Robotic rehabilitation, which provides a high-intensity, high-frequency therapy to improve neuroplasticity, is gaining traction. However, its effectiveness for upper extremity stroke rehabilitation remains uncertain. This study comprehensively reviewed meta-analyses on the effectiveness of upper extremity robot-assisted therapy in patients with stroke. METHODS: We combined results from 396 randomized controlled trials (RCTs) in 16 meta-analyses and conducted a new meta-analysis using nonoverlapping RCTs and 6 additional RCTs published after 2024. Duplicate studies were removed, all data were from RCTs, and a random-effects model resolved heterogeneity. Effects were analyzed by comparing robot-assisted therapy with conventional therapy at the same dose and as an add-on to conventional therapy. RESULTS: Compared with conventional therapy, the effect of robot-assisted therapy on the Fugl-Meyer assessment was summarized as a significant standardized mean difference (SMD) of 0.29 (95% CI, 0.14–0.44; number of individual RCTs reanalyzed, 100 RCTs), and the additional effect of robot-assisted therapy was an SMD of 0.42 (95% CI, 0.23–0.61; 16 RCTs). However, these Fugl-Meyer assessment improvements did not meet the minimum clinically important difference thresholds identified in previous studies: 12.4 for subacute and 3.5 for chronic stroke. For activities of daily living, only the additional effect was significant by SMD of 0.35 (95% CI, 0.17–0.54; 26 RCTs), muscle strength was significant by SMD of 0.46 (95% CI, 0.22–0.70; 31 RCTs), and spasticity was not significant by SMD of −0.25 (95% CI, −0.55 to 0.06; 25 RCTs). CONCLUSIONS: Robot-assisted therapy shows statistically significant improvements in motor recovery as measured by the Fugl-Meyer assessment in patients with stroke, both at the same dose and as an add-on to conventional therapy; however, these improvements do not meet the minimum clinically important difference. These benefits are consistent across different stages of stroke recovery, different types of robotic devices, duration of intervention, and training sites. However, the heterogeneity of included studies in patient population, stroke severity, intervention protocol, and robot type limits generalizability. High-quality trials are needed to better define the value of robot-assisted therapy across various devices and strategies.

Spinal cord injury (SCI) rehabilitation emphasizes locomotion. Robotic-assisted gait training (RAGT) is widely used in clinical settings because of its benefits; however, its efficacy remains controversial. We conducted a systematic review and meta-analysis to investigate the efficacy of RAGT in patients with SCI. We searched international and domestic databases for articles published until April 18, 2024. The meta-analysis employed a random effects model to determine the effect size as either mean difference (MD) or standardized MD (SMD). Evidence quality was evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Twenty-three studies with a total of 690 participants were included in the final analysis. The overall pooled effect size for improvement in activities of daily living was 0.24, with SMD (95% confidence interval [95% CI], 0.04–0.43; GRADE: high) favoring RAGT over conventional rehabilitation. Muscular strength (MD, 0.23; 95% CI, 0.02–0.44; GRADE: high), walking index for SCI (MD, 0.31; 95% CI, 0.07–0.55; GRADE: moderate) and 6 min walk test distance (MD, 0.38; 95% CI, 0.14–0.63; GRADE: moderate) showed significant improvement in the robot group. Subgroup analysis revealed that subacute patients and intervention periods >2 months were more effective. This meta-analysis revealed that RAGT significantly improved activities of daily living, muscular strength, and walking abilities. Additional studies are needed to identify the optimal treatment protocol and specific patient groups for which the protocol is most effective.

Lee K, et al. Yonsei Med J. 2024 Oct;65:e77. https://doi.org/10.3349/ymj.2024.0089

Introduction: Coronavirus disease 2019 (COVID-19), a global pandemic, has infected approximately 10% of the world’s population. This comprehensive review aimed to determine the prevalence of various neurological disorders in COVID-19 without overlapping meta-analysis errors. Methods: We searched for meta-analyses on neurological disorders following COVID-19 published up to March 14, 2023. We obtained 1,184 studies, of which 44 meta-analyses involving 9,228,588 COVID-19 patients were finally included. After confirming the forest plot of each study and removing overlapping individual studies, a re-meta-analysis was performed using the random-effects model. Results: The summarized combined prevalence of each neurological disorder is as follows: stroke 3.39% (95% confidence interval, 1.50–5.27), dementia 6.41% (1.36–11.46), multiple sclerosis 4.00% (2.50–5.00), epilepsy 5.36% (−0.60–11.32), Parkinson’s disease 0.67% (−1.11–2.45), encephalitis 0.66% (−0.44–1.77), and Guillain-Barré syndrome 3.83% (−0.13–7.80). In addition, the mortality risk of patients with comorbidities of COVID-19 is as follows: stroke OR 1.63 (1.23–2.03), epilepsy OR 1.71 (1.00–2.42), dementia OR 1.90 (1.31–2.48), Parkinson’s disease OR 3.94 (−2.12–10.01). Conclusion: Our results show that the prevalence and mortality risk may increase in some neurological diseases during the COVID-19 pandemic. Future studies should elucidate the precise mechanisms for the link between COVID-19 and neurological diseases, determine which patient characteristics predispose them to neurological diseases, and consider potential global patient management.

Yoon SY, et al. Brain Neurorehabil. 2023 Jul;16(2):e16. https://doi.org/10.12786/bn.2023.16.e16

Park JM, et al. Yonsei Med J. 2025 Jul;66:e67. https://doi.org/10.3349/ymj.2024.0409