BACKGROUND: The incidence of stroke has been found in an increasing trend worldwide, resulting in significant negative effects and severe impairments to survivors in terms of motor function and activities of daily living. Acupuncture therapy has been widely used in the clinical treatment of stroke for a long time, meanwhile, the efficacy has been confirmed by many studies. However, the optimal intervention time-point of acupuncture in stroke is controversial. Therefore, the purpose of our study is to provide scientific evidence and reasonable suggestions for this issue. METHODS: A computer-based retrieval will be employed in 7 electronic databases: EMBASE Database, PubMed, the Cochrane Library, China National Knowledge Infrastructure (CNKI), Wan Fang databases, Chinese Scientific Journals Database (VIP) and China Biological Medicine Database (CBM), from the establishment date of each database throughout October 2020. Only randomized controlled trials of acupuncture for stroke will be recruited and language is limited to English or Chinese. The outcomes we focus on include the Fugl-Meyer Assessment score and the Barthel Index. Additionally, safety assessments such as adverse events and drop-out cases may also be taken into consideration. The network meta-analysis will be performed based on the Bayesian framework and literature selection will be conducted by 2 trained reviewers. All data analysis will be calculated by Revman5.3, WinBUGS 1.4.3, Stata13.0, and R software 3.6.1. The Assessment of heterogeneity, inconsistency, subgroup, sensitivity, and publication bias will also be done under the guidelines of Cochrane Collaboration's tool. RESULTS: The results of this study will be submitted to a peer-reviewed journal for publication. CONCLUSION: This network meta-analysis will provide evidence-based references to evaluate the efficacy of different acupuncture intervention time-points during the treatment of stroke. Furthermore, it will help the clinicians to formulate appropriate medical plans and improve clinical efficacy. TRIALS REGISTRATION NUMBER: INPLASY2020120060.
BACKGROUND: The incidence of stroke has been found in an increasing trend worldwide, resulting in significant negative effects and severe impairments to survivors in terms of motor function and activities of daily living. Acupuncture therapy has been widely used in the clinical treatment of stroke for a long time, meanwhile, the efficacy has been confirmed by many studies. However, the optimal intervention time-point of acupuncture in stroke is controversial. Therefore, the purpose of our study is to provide scientific evidence and reasonable suggestions for this issue. METHODS: A computer-based retrieval will be employed in 7 electronic databases: EMBASE Database, PubMed, the Cochrane Library, China National Knowledge Infrastructure (CNKI), Wan Fang databases, Chinese Scientific Journals Database (VIP) and China Biological Medicine Database (CBM), from the establishment date of each database throughout October 2020. Only randomized controlled trials of acupuncture for stroke will be recruited and language is limited to English or Chinese. The outcomes we focus on include the Fugl-Meyer Assessment score and the Barthel Index. Additionally, safety assessments such as adverse events and drop-out cases may also be taken into consideration. The network meta-analysis will be performed based on the Bayesian framework and literature selection will be conducted by 2 trained reviewers. All data analysis will be calculated by Revman5.3, WinBUGS 1.4.3, Stata13.0, and R software 3.6.1. The Assessment of heterogeneity, inconsistency, subgroup, sensitivity, and publication bias will also be done under the guidelines of Cochrane Collaboration's tool. RESULTS: The results of this study will be submitted to a peer-reviewed journal for publication. CONCLUSION: This network meta-analysis will provide evidence-based references to evaluate the efficacy of different acupuncture intervention time-points during the treatment of stroke. Furthermore, it will help the clinicians to formulate appropriate medical plans and improve clinical efficacy. TRIALS REGISTRATION NUMBER: INPLASY2020120060.
Authors: Milo A Puhan; Holger J Schünemann; Mohammad Hassan Murad; Tianjing Li; Romina Brignardello-Petersen; Jasvinder A Singh; Alfons G Kessels; Gordon H Guyatt Journal: BMJ Date: 2014-09-24
Authors: G Gosman-Hedström; L Claesson; U Klingenstierna; J Carlsson; B Olausson; M Frizell; B Fagerberg; C Blomstrand Journal: Stroke Date: 1998-10 Impact factor: 7.914
Authors: Lin Lu; Xiao-guang Zhang; Linda L D Zhong; Zi-xian Chen; Yan Li; Guo-qing Zheng; Zhao-xiang Bian Journal: Sci Rep Date: 2016-01-20 Impact factor: 4.379