Evidence map›Paper›PMID 33350728›Full record

ArticleMedicine2020

The comparison of different acupuncture therapies for post stroke depression: A protocol for a Bayesian network meta-analysis.

Chang Rao, Wei Liu, Zefang Li, Xi Nan, Chunsheng Yin, Jipeng Yang, Yuzheng Du

Abstract readComparative Study
In one paragraph

Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Chang RaoFirst Teaching Hospital of Tianjin University of Traditional Chinese Medicine, National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China.ORCID 0000-0003-0798-1756
Wei Liu
Zefang Li
Xi Nan
Chunsheng Yin
Jipeng Yang
Yuzheng Du

Funding

National Key Research and Development Project 2019YFC0840709National Natural Science Foundation of China 81904093
6 · The paper itself

Abstract

backgroundDepression 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.

methodsA 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.

resultsIn 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.

conclusionsThis study will provide reliable evidence-based evidence for the clinical application of acupuncture in PSD.

Indexed as

Research DesignAcupuncture TherapyBayes TheoremDepressionHumansNetwork Meta-Analysis as TopicStroke

Identifiers

PMID33350728
PMCPMC7769370

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