Systematic review and network meta-analysis of robot-assisted gait training on lower limb function in patients with...

This study aimed to evaluate the effectiveness of robot-assisted gait training (RAGT) in treating lower extremity function in patients with cerebral palsy (CP) and compare the efficacy differences between different robotic systems.

PubMed, Web of Science, Cochrane Library, Embase, CNKI, VIP, CBM, and Wanfang databases were searched to collect randomized controlled trials of RAGT for lower extremity dysfunction in patients with CP from the time the databases were created until December 26, 2022. The D and E of Gross Motor Function Measure-88 (GMFM-88) assessed lower limb motor function. Berg Balance Scale (BBS) was used to assess balance function. Walking endurance and speed were assessed using the 6-minute walk test (6MWT) and walking speed. The modified Ashworth Scale (MAS) was used to assess the degree of muscle spasticity in the lower extremities. The Cochrane Risk Assessment Scale and the Physiotherapy Evidence Database (PEDro) scale were used for qualitative assessment in the studies included. RevMan 5.4 was used for data merging and statistical analysis. R 4.2.0 and ADDIS 1.16.8 were used to map the network relationships and to perform the network meta-analysis.

A total of 14 studies were included in the review. The meta-analysis showed that RAGT significantly improved GMFM-88 D and E, BBS, and 6MWT scores in CP patients compared with conventional rehabilitation. However, for walking speed and MAS, the intervention effect of RAGT was insignificant. The network meta-analysis showed that the best probability ranking for the effect of the 3 different robots on the GMFM-88 D score was LokoHelp (P = 0.66) > Lokomat (P = 0.28) > 3DCaLT (P = 0.06) and the best probability ranking for the GMFM-88 E score was LokoHelp (P = 0.63) > 3DCaLT (P = 0.21) > Lokomat (P = 0.16).

RAGT positively affects walking and balance function in patients with CP, while efficacy in improving gait speed and muscle spasticity is unknown. The best treatment among the different robots is LokoHelp. Future high-quality, long-term follow-up studies are needed to explore the clinical efficacy of RAGT in depth.