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Chinese medicine for COVID-19: A protocol for systematic review and meta-analysis.
Chen, Huizhen; Xie, Ziyan; Zhu, Yuxia; Chen, Qiu; Xie, Chunguang.
  • Chen H; Chengdu University of Traditional Chinese Medicine.
  • Xie Z; Chengdu University of Traditional Chinese Medicine.
  • Zhu Y; Hospital of Chengdu University of Traditional Chinese Medicine, Jinniu District, Chengdu, China.
  • Chen Q; Hospital of Chengdu University of Traditional Chinese Medicine, Jinniu District, Chengdu, China.
  • Xie C; Hospital of Chengdu University of Traditional Chinese Medicine, Jinniu District, Chengdu, China.
Medicine (Baltimore) ; 99(25): e20660, 2020 Jun 19.
Article in English | MEDLINE | ID: covidwho-607008
ABSTRACT

BACKGROUND:

Coronavirus disease 2019 (COVID-19) is a respiratory illness that can spread from person to person. The virus that causes COVID-19 is a novel coronavirus that was first identified during an investigation into an outbreak in Wuhan, China. The clinical spectrum of SARS-CoV-2 infection appears to be wide, encompassing asymptomatic infection, mild upper respiratory tract illness, and severe viral pneumonia with respiratory failure and even death, with many patients being hospitalised with pneumonia. In China and East Asia, Chinese medicine has been widely used to treat diverse diseases for thousands of years. As an important means of treatment now, Chinese medicine plays a significant role in the treatment of respiratory diseases in China. The aim of this study is to assess the efficacy and safety of Chinese medicine for COVID-19.

METHODS:

We will search the following sources for the identification of trials The Cochrane Library, PubMed, EMBASE, Chinese Biomedical Literature Database (CBM), Chinese National Knowledge Infrastructure Database (CNKI), Chinese Science and Technique Journals Database (VIP), and the Wanfang Database. All the above databases will be searched from the available date of inception until the latest issue. No language or publication restriction will be used. Randomized controlled trials will be included if they recruited participants with COVID-19 for assessing the effect of Chinese medicine vs control (placebo, no treatment, and other therapeutic agents). Primary outcomes will include chest CT and nucleic acid detection of respiratory samples. Two authors will independently scan the articles searched, extract the data from articles included, and assess the risk of bias by Cochrane tool of risk of bias. Disagreements will be resolved by consensus or the involvement of a third party. All analysis will be performed based on the Cochrane Handbook for Systematic Reviews of Interventions. Dichotomous variables will be reported as risk ratio or odds ratio with 95% confidence intervals (CIs) and continuous variables will be summarized as mean difference or standard mean difference with 95% CIs. RESULTS AND

CONCLUSION:

The available evidence of the treatment of COVID-19 with traditional Chinese medicine will be summarized, and evaluation of the efficacy and the adverse effects of these treatments will be made. This review will be disseminated in print by peer-review.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Meta-Analysis as Topic / Coronavirus Infections / Systematic Reviews as Topic / Medicine, Chinese Traditional Type of study: Experimental Studies / Prognostic study / Randomized controlled trials / Reviews / Systematic review/Meta Analysis Topics: Traditional medicine Limits: Humans Language: English Journal: Medicine (Baltimore) Year: 2020 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Meta-Analysis as Topic / Coronavirus Infections / Systematic Reviews as Topic / Medicine, Chinese Traditional Type of study: Experimental Studies / Prognostic study / Randomized controlled trials / Reviews / Systematic review/Meta Analysis Topics: Traditional medicine Limits: Humans Language: English Journal: Medicine (Baltimore) Year: 2020 Document Type: Article