Chinese Journal of Tissue Engineering Research ›› 2026, Vol. 30 ›› Issue (24): 6365-6372.doi: 10.12307/2026.167
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Nie Yue1, Song Shuhua1, Zhao Shengting2, Dong Yangyang1, Yang Bingxin3
Received:2025-04-08
Revised:2026-08-06
Online:2026-08-28
Published:2026-02-04
Contact:
Zhao Shengting, Associate chief technician, Department of Rehabilitation Medicine, Kunming Tongren Hospital, Kunming 650033, Yunnan Province, China
About author:Nie Yue, MS candidate, School of Physical Education, Yunnan Normal University, Kunming 650500, Yunnan Province, China
Supported by:CLC Number:
Nie Yue, Song Shuhua, Zhao Shengting, Dong Yangyang, Yang Bingxin. Network meta-analysis of different virtual reality devices for treating upper limb motor dysfunction after stroke[J]. Chinese Journal of Tissue Engineering Research, 2026, 30(24): 6365-6372.
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2.1 文献检索结果 初步检索共获得文献972篇,包括504篇中文文献,467篇英文文献,1篇其他来源文献。经逐层筛选,最终纳入12篇文献。详细筛选流程及排除原因见图2。 2.2 纳入文献的基本特征和质量评价 2.2.1 纳入文献的基本特征 共纳入12篇文献[2,9,14,21-29],571例脑卒中偏瘫患者。其中虚拟现实技术共纳入了6种,包括BioMaster虚拟情景互动训练系统3篇、Kinect体感交互技术3篇、智能手套3篇、Wii虚拟现实游戏1篇、VREX魔迅虚拟康复训练系统1篇、Armeo Spring虚拟康复训练系统1篇。纳入研究的基本特征见表1。 2.2.2 纳入文献的质量评价 12篇文献均使用Cochrane风险偏倚评估工具和方法进行质量评估,具体信息见表2及图3,4。 2.3 Meta分析结果 2.3.1 上肢运动功能(FMA-UE) 包括10篇文献[2,9,14,21-26,28],共477例脑卒中患者采用FMA-UE进行上肢运动功能评定,其中试验组和对照组分别有238例、239例。各文献间异质性小(I2=48%,P≥0.05),采用固定效应模型分析。结果显示,虚拟现实训练组更能改善患者的上肢运动功能(MD=7.29,95%CI:5.60-8.98,P < 0.05),见图5。 调节变量亚组检验结果:通过设置调节变量(年龄、病程、干预周期)对FMA-UE评分的效应量进行亚组分析。结果显示,在年龄方面,2个年龄段的FMA-UE评分均优于对照组(P < 0.05),其中50-59岁的患者干预效果最佳;在病程方面,两段病程的FMA-UE评分均优于对照组(P < 0.05),其中病程为3个月以内的患者干预效果最佳;在干预周期方面,2个周期段的FMA-UE评分均优于对照组(P < 0.05),其中4周以上的患者干预效果最佳。见表3。 2.3.2 上肢动作研究量表(ARAT) 包括2篇文献[28-29],共54例患者采用ARAT量表对其上肢功能的恢复情况进行评估,其中试验组和对照组分别有27例、27例。2篇文献间无异质性(I2=0%,P≥0.05),采用固定效应模型分析。结果显示,虚拟现实训练组更能改善患者的上肢动作协调能力(MD=10.69,95%CI:4.96-16.43,P < 0.05)。见图6。 2.3.3 箱块试验(BBT) 包括2篇文献[25,27],110例患者采用箱块试验进行手部灵巧度评定,其中试验组和对照组分别有50例、60例。2篇文献间异质性小(I2=45%,P≥0.05),采用固定效应模型分析。结果显示,虚拟现实组与"
常规治疗组的BBT得分无明显差异(MD=4.72,95%CI:-1.33-10.78,P > 0.05)。见图7。 2.3.4 改良Barthel指数(MBI) 包括3篇文献[9,14,23],共155例患者采用改良Barthel指数进行生活活动能力评估,其中试验组和分别有76例、79例。各文献间无异质性(I2=0%,P≥0.05),采用固定效应模型分析。结果显示,虚拟现实训练组更能改善患者的日常生活能力(MD=8.25,95%CI:3.38-13.12,P < 0.05)。见图8。 2.4 网状Meta分析 2.4.1 网状证据关系图 各结局指标的证据关系见图9。圆点代表干预措施,圆点大小代表该干预措施所涉及的病例数。圆点之间的连线代表两种干预措施之间存在直接比较的证据,实线越粗,表明直接比较的证据越多,反之越少。 2.4.2 网状Meta分析结果 (1) FMA-UE评分:共10项研究采用了FMA-UE评分[2,9,14,21-26,28],涉及5种虚拟现实设备。在提高FMA-UE方面,智能手套和Kinect体感交互技术优于常规康复治疗,差异有显著性意义(P < 0.05),见表4。 (2) ARAT评分:共2项研究采用了ARAT评分[28-29],涉及2种虚拟现实设备。在提高ARAT方面,Armeo Spring虚拟康复训练系统优于常规康复治疗,差异有显著性意义(P < 0.05),见表5。 (3) BBT评分:共2项研究采用了BBT评分[25,27],涉及2种虚拟现实设备。在提高BBT方面Kinect体感交互技术优于常规康复治疗,差异有显著性意义(P < 0.05),见表6。 (4) MBI评分:共3项研究采用了MBI评分[9,14,23],涉及2种虚拟现实设备。在提高MBI方面VREX魔迅虚拟康复训练系统优于常规康复治疗,差异有显著性意义(P < 0.05),见表7。 2.4.3 累计概率排序结果 在各结局指标种,累计概率图的曲线下面积越大代表疗效越好,累计概率见图10。 ①在FMA-UE评分中,优先概率排名结果为智能手套(86.6%) > Kinect体感交互技术(65.8%) > VREX魔迅虚拟康复训练系统(58.0%) > BioMaster虚拟情景互动训练系统(51.4%) > Wii虚拟现实游戏(27.6%) > 常规康复治疗(10.6%);②在ARAT评分中,优先概率排名为Armeo Spring虚拟康复训练系统(90.1%) >智能手套(53.4%) > 常规康复治疗(6.5%);③在BBT评分中,优先概率排名为Kinect体感交互技术(97.4%) > 常规康复治疗(30.6%) > 智能手套(22.0%);④在MBI评分中,优先概率排名为VREX魔迅虚拟康复训练系统(94.2%) > Kinect体感交互技术(53.3%) > 常规康复治疗(2.5%)。 2.5 敏感性分析 因Wii虚拟现实游戏、VREX魔迅虚拟康复训练系统、Armeo Spring虚拟康复训练系统3个虚拟现实设备所涉及文献仅各1篇,因而此次研究仅对BioMaster虚拟情景互动训练系统、Kinect体感交互技术、智能手套系统进行敏感性分析。通过逐一剔除每项研究的方法,观察剔除后研究异质性的变化。结果显示,在逐步剔除各项研究后,3个虚拟现实设备所涉及研究的异质性无明显变化,表明结果稳定可靠,见图11-13。 2.6 发表偏倚检验 鉴于纳入的文献数量有限,此次研究仅对FMA-UE结局指标进行发表偏倚的评估。分析结果显示,各研究基本以漏斗图中零位线对称,提示文章的发表偏倚风险较低,见图14。"
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