The comparison of different acupuncture therapies for post stroke depression: A protocol for a Bayesian network meta-analysis.
Medicine (Baltimore). 2020 Dec 24;99(52):e23456
Authors: Rao C, Liu W, Li Z, Nan X, Yin C, Yang J, Du Y
BACKGROUND: Depression is a common disease which occurs after stroke, affecting approximately one third of stroke survivors at any 1 time after stroke (compared with 5%-13% of adults without stroke), with a cumulative incidence of 55%. Acupuncture, which has a long history in China, is the generic name of different kinds of acupuncture therapies, including manual acupuncture (MA), electroacupuncture (EA), fire needle (FN), dry needling (DN), and so on. Clinical studies have shown that acupuncture has a good therapeutic effect on post stroke depression (PSD), but the evidence-based medicine of it is insufficient. The purpose of this study is to systematically evaluate the efficacy of different kinds of acupuncture therapies in the treatment of PSD, and to provide evidence-based basis for the clinical application of acupuncture in the treatment of PSD.
METHODS: A systematic search will be performed on English databases (PubMed, The Cochrane Library, Medline, Embase) and Chinese databases (China National Knowledge Infrastructure (CNKI), WanFang Data, VIP and Chinese biomedical databases). The retrieval time limit will be from the establishment of the database to August 2020. Two researchers will independently screen the literatures, extract data, and evaluate the quality of the included studies. Bayesian network analysis will be conducted by using STATA V.14.0 and ADDIS V.1.16.7.
RESULTS: In this study, the efficacy of different kinds of acupuncture therapies in the treatment of PSD will be evaluated by the degree of reduction in depression, total numbers of adverse events, quality of life indices, improvement of social and life functions and the expression of nerve cell factors.
CONCLUSIONS: This study will provide reliable evidence-based evidence for the clinical application of acupuncture in PSD.
PMID: 33350728 [PubMed – as supplied by publisher]