Efficacy of rehabilitation robots on lower limb motor function in patients with cerebral palsy: a Meta-analysis

doi:10.12307/2025.654

Abstract

Abstract: OBJECTIVE: To systematically evaluate the clinical effectiveness of rehabilitation robots in treating lower limb motor dysfunction in patients with cerebral palsy, and to compare the differences in therapeutic effects among different robots.
METHODS: PubMed, Web of Science, Embase, Cochrane Library, CNKI, CBM, VIP and WanFang databases were searched to collect randomized controlled trials on rehabilitation robotics for the treatment of motor dysfunction in patients with cerebral palsy, published from database inception to April 10, 2024. The main outcome indicators included muscle strength, muscle tension, balance function, step speed, step frequency, step length, walking endurance, lower limb motor function, and activities of daily living. The above indicators were coded according to the International Classification of Functioning, Disability and Health. Meta-analysis was performed to evaluate the clinical efficacy and compare the therapeutic efficacy of different rehabilitation robots. Literature search and screening were performed by two researchers, and the quality of the included literature was evaluated using the Cochrane 5.1.0 risk of bias assessment tool. Meta-analysis was performed using RevMan 5.4 software and Stata 16.0 software.
RESULTS: (1) Fifteen articles were finally included, involving 512 patients with 260 in the experimental group and 252 in the control group. (2) The Meta-analysis results showed that rehabilitation robots could improve body structure and function [standardized mean difference=0.41, 95% confidence interval (CI): 0.24-0.58, P < 0.05], activities (standardized mean difference=0.53, 95% CI: 0.41-0.65, P < 0.05) and participation ability (mean difference=7.86, 95% CI: 1.54-14.18, P < 0.05). In particular, the rehabilitation robot improved lower limb muscle strength, balance function, step speed, walking endurance, lower limb gross motor function, and activities of daily living in patients with cerebral palsy, but showed insignificant effects on step frequency, step length, and muscle tension.
(3) The network Meta-analysis results showed that: step speed: Innowalkpro > Gait Trainer > Lokomat > 3DCalt; 6-minute walk test score: Gait Trainer > Lokomat > Lokohelp > Innowalkro; Gross Motor Function Measure-88D score: Lokohelp > Lokomat > KidGo > Innowalkpro > 3DCalt; Gross Motor Function Measure-88E score: Lokomat > Lokohelp > KidGo > 3DCalt > Innowalkpro.
CONCLUSION: Based on the International Classification of Functioning, Disability, and Health, rehabilitation robot training can improve the lower limb motor function and activities of daily living in patients with cerebral palsy. The Innowalkpro robot was more effective in improving step speed; the Gait trainer robot was more effective in improving 6-minute walk test scores; the Lokohelp robot was more effective in improving Gross Motor Function Measure-88D zone scores; and the Lokomat robot was more effective in improving Gross Motor Function Measure-88E zone scores.

中国组织工程研究杂志出版内容重点：组织构建；骨细胞；软骨细胞；细胞培养；成纤维细胞；血管内皮细胞；骨质疏松；组织工程

Key words: cerebral palsy, rehabilitation robot, lower limb motor function, walking, gait, activities of daily living, system evaluation, network Meta-analysis, engineered rehabilitation

CLC Number:

Liu Xingzhao, Hu Tong, Ma Yan, Wang Qian, Wei Xiaohui, Chang Wanpeng, Yu Shaohong. Efficacy of rehabilitation robots on lower limb motor function in patients with cerebral palsy: a Meta-analysis[J]. Chinese Journal of Tissue Engineering Research, 2025, 29(18): 3925-3933.

Figures/Tables 8

2.3 文献质量评价所纳入15篇文献中9篇报告了具体随机方法[27-28，30-33，35，37，40]，如随机数字表法和随机抽签法(低风险)；3篇文献仅报告随机分配[29，39，41]，未提供具体随机方法(中风险)；3篇文献按照治疗类型、治疗方法和招募时间分配(高风险) [34，36，38]。2篇文献对研究使用分配隐藏(低风险) [40-41]；7篇文献对结果测评使用了盲法(低风险) [28，30-32，39-41]；15篇文献结果数据完整、无选择性报道、其他偏倚风险情况均不清楚[27-41]。具体评价见图3，4。 2.4 Meta分析结果 2.4.1 两组肌力差异 2篇文献共70例患者进行下肢肌肉力量评定[27，33]，各研究间异质性不显著(I2=0%，P > 0.1)，采用固定效应模型，两组肌力评分具有显著差异(SMD=0.38，95%CI：0.10-0.65，P < 0.05)，见表4。 2.4.2 两组MAS评分差异 4篇文献共109例患者采用MAS评分进行肌张力评定[30，32，37，41]。各研究间异质性不显著(I2=0%，P > 0.1)，采用固定效应模型，两组MAS评分差异无显著性意义(MD=-0.08，95%CI：-0.28-0.11，P > 0.05)，见表4。 2.4.3 两组平衡功能差异 6篇文献共338例患者采用BBS或PBS进行平衡功能评定[27-28，30，33，36，41]。各研究间异质性不显著(I2=0%，P > 0.1)，采用固定效应模型，两组平衡功能评分具有显著差异(SMD=0.73，95%CI：0.46-0.99，P < 0.05)，见表4。 2.4.4 两组步速差异 6篇文献共160例患者采用10MWT或步态速度进行步速评定[31，35-37，39-40]。各研究间异质性不显著(I2=20%，P > 0.1)，采用固定效应模型，两组步速评分具有显著差异(SMD=0.52，95%CI：0.22-0.82，P < 0.05)，见表4。 2.4.5 两种步频差异 2篇文献共53例患者进行步频评定[35，37]。各研究间异质性不显著(I2=4%，P > 0.1)，采用固定效应模型，两组步频差异无显著性意义(MD=-3.67，95%CI：-11.99-4.66，P > 0.05)，见表4。 2.4.6 两组步长差异 3篇文献共88例患者进行步长评定[35，37，39]。各研究间异质性不显著(I2=0%，P > 0.1)，采用固定效应模型，两组步长差异无显著性意义(MD=0.02，95%CI：-0.02-0.05，P > 0.05)，见表4。 2.4.7 两组FAC评分差异 2篇文献共53例患者采用FAC评分进行步行功能评定[30-31]。各研究间异质性不显著(I2=34%，P > 0.1)，采用固定效应模型，两组FAC评分具有显著差异(MD=0.47，95%CI：0.05-0.90，P=0.05)，见表4。"

2.4.8 两组6MWT评级差异 5篇文献共114例患者采用6MWT评级进行步行距离评定[30-31，36，38，40]。各研究间异质性不显著(I2=0%，P > 0.1)，采用固定效应模型，两组6MWT评级具有显著差异(MD=29.43，95%CI：20.65-38.20，P < 0.05)，见表4。 2.4.9 两组粗大运动功能(站立) GMFM-D评分差异 9篇文献共329例患者采用GMFM-D评分进行粗大运动功能(站立)评定[28-29，31，33-38]。各研究间异质性显著(I2=59%，P < 0.1)，采用随机效应模型，两组GMFM-D评分具有显著差异(SMD=0.67，95%CI：0.31-1.04，P < 0.05)。根据年龄进行亚组分析，1篇文献不符合年龄要求[34]，共8篇文献纳入亚组分析。学龄前期(3-6岁)组：异质性不显著(I2=0%，P > 0.1)，两组GMFM-D评分高于对照组(SMD=1.17，95%CI：0.83-1.52，P < 0.05)；学龄期(6-15岁)组：异质性不显著(I2=41%，P > 0.1)，两组GMFM-D评分差异无显著性意义(SMD=0.27，95%CI：-0.09-0.62，P > 0.05)，见表4。 2.4.10 两组粗大运动功能(行走与跑跳)GMFM-E评分差异 9篇文献共329例患者采用GMFM-E评分进行粗大运动功能(行走与跑跳)评定[28-29，31，33-38]。各研究间异质性不显著(I2=45%，P < 0.1)，采用固定效应模型，两组GMFM-E评分差异有显著性意义(SMD=0.65，95%CI：0.42-0.87，P < 0.05)。根据年龄进行亚组分析，1篇文献不符合年龄要求[34]，共8篇文献纳入亚组分析。学龄前期(3-6岁)组：异质性不显著(I2=16%，P > 0.1)，试验组GMFM-E评分高于对照组(SMD=1.02，95%CI：0.68-1.35，P < 0.05)；学龄期(6-15岁)组：异质性不显著(I2=25%，P > 0.1)，试验组GMFM-E评分高于对照组(SMD=0.37，95%CI：0.02-0.73，P < 0.05)，见表4。 2.4.11 两组身体结构与功能差异 8篇文献共297例患者进行身体结构与功能水平评定[27-28，30，32-33，36-37，41]。各研究间异质性不显著(I2=35%，P < 0.1)，采用固定效应模型，两组身体结构与功能水平具有显著差异(SMD=0.41，95%CI：0.24-0.58，P < 0.05)。根据年龄进行亚组分析，2篇文献不符合年龄要求[30，32]，共6篇文献纳入亚组分析。学龄前期(3-6岁)组：异质性不显著(I2=11%，P > 0.1)，试验组身体结构与功能评分高于对照组(SMD=0.57，95%CI：0.36-0.78，P <0.05)；学龄期(6-15岁)组：异质性不显著(I2=0%，P > 0.1)，两组差异无显著性意义(SMD=0.13，95%CI：-0.27-0.52， P > 0.05)，见表4。 2.4.12 两组活动水平差异 12篇文献共405例患者进行活动水平评定[28-31，33-40]。各研究间异质性不显著(I2=49%，P < 0.1)，采用固定效应模型，两组活动水平具有显著差异(SMD=0.53，95%CI：0.41-0.65，P < 0.05)。根据年龄进行亚组分析，2篇文献不符合年龄要求[30，34]，共10篇文献纳入亚组分析。学龄前期(3-6岁)组：异质性不显著(I2=0%，P > 0.1)，试验组活动水平优于对照组(SMD=1.09，95%CI：0.85-1.33，P < 0.05)；学龄期(6-15岁)组：异质性不显著(I2=4%，P > 0.1)，试验组活动水平优于对照组(SMD=0.31，95%CI：0.15-0.47，P < 0.01)，见表4。 2.4.13 两组参与水平差异(WeeFim) 3篇文献共74例患者采用WeeFim进行日常生活能力评定[33，40-41]。各研究间异质性不显著(I2=0%，P > 0.1)，采用固定效应模型，两组WeeFim评分具有显著差异(MD=7.86，95%CI：1.54-14.18，P < 0.05)，见表4。 2.5 网状Meta分析结果 2.5.1 采用与下肢运动功能密切相关的GMFM-88D、GMFM-88E、6MWT和步速来比较不同机器人的疗效不同干预措施的网状关系见图5。不同圆点代表不同干预措施，圆点越大，表明此干预措施病例数越多。两圆点之间相连的实线代表二者之间存在直接比较的证据，实线越粗，表明直接比较证据越多。由网状关系图可知，不同干预措施之间不存在三角形闭环，因此无需进行不一致性检验。 2.5.2 概率排名 ①在改善步速方面，不同机器人最佳概率排序为：Innowalkpro (66.9%) > Gait trainer (58.0%) > Lokomat (55.6%) > 3DCalt (45.7%) > 常规康复治疗(23.9%)。②在改善6MWT评级方面，不同机器人最佳概率排序为：Gait trainer(60.8%) > Lokomat(58.1%) > Lokohelp(56.9%) > Innowalkro(45.9%) >常规康复治疗(28.3%)。③在改善GMFM-88D区评分方面，不同机器人最佳概率排序为：Lokohelp(96.3%) > Lokomat(73.3%) > KidGo(55.1%) > 常规康复治疗(26.5%) > Innowalkpro (24.5%) > 3DCalt(24.4%)。④在改善GMFM-88E区评分方面，不同机器人最佳概率排序为：Lokomat (71.2%) > Lokohelp(66.1%) > KidGo(52.6%) > 3DCalt(46.1%) > Innowalkpro(37.4%) > 常规康复治疗(26.7%)。网状Meta分析累计概率见图6。 2.6 不良反应一项研究报道，少数患者在佩戴机器人装置后，因摩擦大腿内根部皮肤而产生轻微不适，休息后缓解，不影响第2天的治疗[30]。另一项研究报道机器人的耐受性良好，除小腿擦伤等小问题外，无不良事件发生[34]。在其他研究中未发现不良反应。"

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