Xue Tao, Yan Zeya, Meng Jiahao, Wang Wei, Chen Shujun, Wu Xin, Gu Feng, Tao Xinyu, Wu Wenxue, Chen Zhouqing, Bai Yutong, Wang Zhong, Zhang Jianguo
Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.
Department of Neurosurgery, The First Affiliated Hospital of Soochow University, Suzhou 215006, China.
J Clin Med. 2022 Oct 19;11(20):6162. doi: 10.3390/jcm11206162.
Neurostimulations for the post-stroke recovery of upper extremity function has been explored in previous research, but there remains a controversy about the superiority of different neurostimulations.
Randomized controlled trials (RCTs) were searched in MEDLINE, Embase, Cochrane Library and ClinicalTrials.gov, from 1 January 2000 to 1 June 2022. A conventional pair-wise meta-analysis with a random-effect model was used to evaluate direct evidence. Bayesian random effect models were used for network meta-analysis. The grading of the recommendations assessment, development and evaluation (GRADE) approach was applied to assess the clinical quality of the results.
A total of 88 RCTs, which enrolled 3491 participants, were included. For the Fugl-Meyer Assessment-Upper Extremity score change from the baseline to the longest follow-up, the following interventions showed a significant difference: VNS (MD = 4.12, 95%CrI: 0.54 to 7.80, moderate certainty), cNMES (MD = 3.98, 95%CrI: 1.05 to 6.92, low certainty), FES (MD = 7.83, 95%CrI: 4.42 to 11.32, very low certainty), drTMS (MD = 7.94, 95%CrI: 3.71 to 12.07, moderate certainty), LFrTMS (MD = 2.64, 95%CrI: 1.20 to 4.11, moderate certainty), HFrTMS (MD = 6.73, 95%CrI: 3.26 to 10.22, moderate certainty), and iTBS combined with LFrTMS (MD = 5.41, 95%CrI: 0.48 to 10.35, moderate certainty).
The neurostimulations above the revealed significant efficacy for improving the upper limb function after stroke eased the suffering of the patient.
先前的研究已对神经刺激用于中风后上肢功能恢复进行了探索，但不同神经刺激的优越性仍存在争议。
检索了2000年1月1日至2022年6月1日期间MEDLINE、Embase、Cochrane图书馆和ClinicalTrials.gov中的随机对照试验（RCT）。采用随机效应模型的传统成对荟萃分析来评估直接证据。贝叶斯随机效应模型用于网状荟萃分析。应用推荐评估、制定与评价（GRADE）方法对结果的临床质量进行评估。
共纳入88项RCT，涉及3491名参与者。对于从基线到最长随访期的Fugl-Meyer上肢评估评分变化，以下干预措施显示出显著差异：迷走神经刺激（MD = 4.12，95%CrI：0.54至7.80，中等确定性）、常规神经肌肉电刺激（MD = 3.98，95%CrI：1.05至6.92，低确定性）、功能性电刺激（MD = 7.83，95%CrI：4.42至11.32，极低确定性）、重复经颅磁刺激（MD = 7.94，95%CrI：3.71至12.07，中等确定性）、低频重复经颅磁刺激（MD = 2.64，95%CrI：1.20至4.11，中等确定性）、高频重复经颅磁刺激（MD = 6.73，95%CrI：3.26至10.22，中等确定性），以及间歇性θ波爆发刺激联合低频重复经颅磁刺激（MD = 5.41，95%CrI：0.48至10.35，中等确定性）。
上述神经刺激对改善中风后的上肢功能显示出显著疗效，减轻了患者的痛苦。
