Comparative efficacy of gait training for balance outcomes in patients with stroke: A systematic review and network meta-analysis

• Published in: Frontiers in neurology 2023-04, Vol.14, p.1093779-1093779
• Main Authors: Lyu, Tianyi, Yan, Kang, Lyu, Jiaxuan, Zhao, Xirui, Wang, Ruoshui, Zhang, Chaoyang, Liu, Meng, Xiong, Chao, Liu, Chengjiang, Wei, Yulong
• Format: Article
• Language: English
• Subjects: balance outcomes; gait training; network meta-analysis; Neurology; randomized controlled trials; stroke
• ISSN: 1664-2295; 1664-2295
• DOI: 10.3389/fneur.2023.1093779

Growing evidence suggests that gait training can improve stroke patients' balance outcomes. However, it remains unclear which type of gait training is more effective in improving certain types of balance outcomes in patients with stroke. Thus, this network meta-analysis (NMA) included six types of gait training (treadmill, body-weight-supported treadmill, virtual reality gait training, robotic-assisted gait training, overground walking training, and conventional gait training) and four types of balance outcomes (static steady-state balance, dynamic steady-state balance, proactive balance, and balance test batteries), aiming to compare the efficacy of different gait training on specific types of balance outcomes in stroke patients and determine the most effective gait training. We searched PubMed, Embase, Medline, Web of Science, and Cochrane Library databases from inception until 25 April 2022. Randomized controlled trials (RCTs) of gait training for the treatment of balance outcomes after stroke were included. RoB2 was used to assess the risk of bias in the included studies. Frequentist random-effects network meta-analysis (NMA) was used to evaluate the effect of gait training on four categories of balance outcomes. A total of 61 RCTs from 2,551 citations, encompassing 2,328 stroke patients, were included in this study. Pooled results showed that body-weight-support treadmill (SMD = 0.30, 95% CI [0.01, 0.58]) and treadmill (SMD = 0.25, 95% CI [0.00, 0.49]) could improve the dynamic steady-state balance. Virtual reality gait training (SMD = 0.41, 95% CI [0.10, 0.71]) and body-weight-supported treadmill (SMD = 0.41, 95% CI [0.02, 0.80]) demonstrated better effects in improving balance test batteries. However, none of included gait training showed a significant effect on static steady-state balance and proactive balance. Gait training is an effective treatment for improving stroke patients' dynamic steady-state balance and balance test batteries. However, gait training had no significant effect on static steady-state balance and proactive balance. To achieve maximum efficacy, clinicians should consider this evidence when recommending rehabilitation training to stroke patients. Considering body-weight-supported treadmill is not common for chronic stroke patients in clinical practice, the treadmill is recommended for those who want to improve dynamic steady-state balance, and virtual reality gait training is recommended for those who want to improve balance te