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Traditional Chinese medicine for the prevention and treatment of COVID-19
source:Medicine 2022-01-04 [Research]
A protocol for systematic review and network meta-analysis

Wang, Xin MSc∗; Wang, Yafeng PhD; Lu, Hairu MSc; Yan, Luqing MSc

Qinghai Provincial People's Hospital, Xining, Qinghai, China.

∗Correspondence: Xin Wang, 2 Gonghe Road, Chengdong District, Xining, Qinghai, China (e-mail: wangxinwx105@126.com).

 

 

Abstract

Background: 

The coronavirus disease 2019 (COVID-19) pandemic spread to most of the world's countries during its first and subsequent waves, often increasing in an almost exponential trend. Traditional Chinese medicine has played a vital role in this epidemic. Nonetheless, size of effect, certainty of the evidence, optimal therapy regimen, and selection of patients who are likely to benefit most are factors that remain to be evaluated. This study aims to assess and rank where appropriate the relative effects of interventions for the prevention and treatment of COVID-19.

Method: 

This study will follow the Preferred Reporting Items for Systematic Reviews and Meta-analysis Protocols. We will search Chinese electronic database (CBM, Wanfang and CNKI) and international electronic databases (PubMed, Embase, Cochrane Library, and Web of Science) for identify all relevant published studies. Study selection, data collection and assessment of study bias will be conducted independently by a pair of independent reviewers. The Cochrane risk of bias tool will be used for the risk of bias assessment. We will use the advance of GRADE to rate the certainty of network meta-analysis. Data analysis will be performed with R-3.6.1 and WinBUGS software.

Results: 

The results of this study will be published in a peer-reviewed journal.

Conclusion: 

This systematic review and network meta-analysis will use both direct and indirect evidence to compare the differences of all Traditional Chinese medicine treatment for COVID-19 patients, providing decision-makers and clinical practitioners with a complete, high-quality and up-to-date synthesis of evidence.