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An effectiveness comparison of acupuncture treatments for insomnia disorder: A bayesian network meta-analysis protocol
BACKGROUND: Acupuncture (ACU) is used frequently in the management of insomnia disorder in China. Whereas there is variability in practice regarding the selection of ACU treatments, most choices are made based on personal experience or preference of clinician. This study uses network meta-analysis t...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6392799/ https://www.ncbi.nlm.nih.gov/pubmed/30170419 http://dx.doi.org/10.1097/MD.0000000000012060 |
Sumario: | BACKGROUND: Acupuncture (ACU) is used frequently in the management of insomnia disorder in China. Whereas there is variability in practice regarding the selection of ACU treatments, most choices are made based on personal experience or preference of clinician. This study uses network meta-analysis to compare the effectiveness of different forms of ACU for insomnia and assesses the evidence with the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. METHODS: A comprehensive search for randomized controlled trials (RCTs) of ACU treatments for insomnia disorder will be carried out in PubMed, Embase, Cochrane Library, China BioMedical Literature (CBM), China National Knowledge Infrastructure (CNKI), Chongqing VIP (CQVIP), and Wanfang, from their inceptions to April 2018. The quality of the included RCTs will be evaluated with the risk of bias (ROB) tool and evidence will be evaluated by GRADE. STATA 13.0 and WinBUGS 1.4.3 through the GeMTC package will be used to perform a network meta-analysis to synthesize direct and indirect evidence. RESULTS: The results of this network meta-analysis (NMA) will be submitted to a peer-reviewed journal for publication. CONCLUSION: The results of our study will provide the best possible ACU choice for clinicians, and the best possible strength of the evidence with the GRADE approach. |
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