Zhang Meng, Liang Zhide, Li Yali, Meng Jun, Jiang Xu, Xu Bichan, Li Haojie, Liu Tao
Postgraduate Department, Xi'an Physical Education University, Xi'an, China.
School of Physical Education, Qingdao University, Qingdao, China.
Front Neurol. 2023 Nov 2;14:1234017. doi: 10.3389/fneur.2023.1234017. eCollection 2023.
Stroke, which is a common clinical cerebrovascular disease, causes approximately 83% of survivors to suffer from balance impairments. Balance and gait training (BGT) is widely used to restore balance in patients with stroke. However, its wide variety presents clinicians with a dilemma when selecting interventions. This study aimed to compare and rank BGT interventions by quantifying information based on randomized controlled trials (RCTs).
We conducted a network meta-analysis (NMA) of non-gait-trained controls and head-to-head RCTs and compared the effects of 12 BGT interventions. A total of nine literature databases, including Medline, Embase, Cochrane Library, Web of Science, Scopus, SPORTDiscus, ClinicalTrials.gov, CNKI, and Chinese biomedical literature databases, were searched from their database inception to August 2023. Two authors independently selected studies and extracted data. The difference in outcomes, which were expressed as standardized mean differences and confidence intervals (CIs) of 95%, were explored in this meta-analysis.
A total of 66 studies with 1,933 participants were included. Effect size estimates showed that not all BGT interventions were more effective than controls, with treadmill training as the least effective for balance test batteries (SMD = -0.41, 95% CI [-1.09, 0.27]) and proactive balance (SMD = -0.50, 95% CI [-1.14, 0.14]). Body-weight-supported treadmill training with external stimulation was most effective for proactive balance and dynamic steady-state balance (SMD = 1.57, 95% CI [-0.03, 3.16]); SMD = 1.18, 95% CI [0.67, 1.68]. Virtual reality gait training (SMD = 1.37, 95% CI [0.62, 2.11]) had the best effect on improving balance test batteries, while dual-task BGT (SMD = 1.64, 95% CI [0.50, 2.78]) had the best effect on static steady-state balance. After analyses for possible impact covariates, the findings through the outcomes did not change substantially. Confidence in the evidence was generally low or very low.
This NMA suggested that virtual reality gait training was the most effective BGT modality for improving balance test batteries. Body-weight support treadmill training with external stimulation was the most effective for improving active and dynamic balance. In addition, dual-task BGT was the best choice for improving static balance. However, balance is a multidimensional concept, and patients' different needs should be considered when selecting BGT.
https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022316057, ID: CRD42022316057.
中风是一种常见的临床脑血管疾病,约83%的幸存者存在平衡障碍。平衡和步态训练(BGT)被广泛用于恢复中风患者的平衡。然而,其种类繁多,给临床医生在选择干预措施时带来了两难困境。本研究旨在通过基于随机对照试验(RCT)量化信息,对BGT干预措施进行比较和排序。
我们对未进行步态训练的对照组和头对头RCT进行了网络荟萃分析(NMA),比较了12种BGT干预措施的效果。从其数据库建立到2023年8月,共检索了9个文献数据库,包括Medline、Embase、Cochrane图书馆、科学网、Scopus、SPORTDiscus、ClinicalTrials.gov、中国知网和中国生物医学文献数据库。两位作者独立选择研究并提取数据。在这项荟萃分析中,探讨了以标准化均数差和95%置信区间(CI)表示的结果差异。
共纳入66项研究,1933名参与者。效应量估计表明,并非所有BGT干预措施都比对照组更有效,跑步机训练对平衡测试组合的效果最差(标准化均数差= -0.41,95%CI[-1.09, 0.27]),对主动平衡的效果也最差(标准化均数差= -0.50,95%CI[-1.14, 0.14])。有外部刺激的体重支持跑步机训练对主动平衡和动态稳态平衡最有效(标准化均数差= 1.57,95%CI[-0.03, 3.16]);标准化均数差= 1.18,95%CI[0.67, 1.68]。虚拟现实步态训练(标准化均数差= 1.37,95%CI[0.62, 2.11])对改善平衡测试组合效果最佳,而双任务BGT(标准化均数差= 1.64,95%CI[0.50, 2.78])对静态稳态平衡效果最佳。在对可能的影响协变量进行分析后,通过结果得出的结论没有实质性变化。证据的可信度普遍较低或非常低。
这项NMA表明,虚拟现实步态训练是改善平衡测试组合最有效的BGT方式。有外部刺激的体重支持跑步机训练对改善主动和动态平衡最有效。此外,双任务BGT是改善静态平衡的最佳选择。然而,平衡是一个多维度概念,在选择BGT时应考虑患者的不同需求。
https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022316057,ID:CRD42022316057。