Open AccessEfficacy and safety of Lianhua Qingwen in the treatment of patients with moderate COVID-19 infection
Author(s) -
Nanyang Liu,
Tingting Zhang,
Lina Ma,
Huican Wang,
Yu Cao,
Yang Yang,
Hui Peng,
Hao Li
Publication year - 2020
Publication title -
medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 148
eISSN - 1536-5964
pISSN - 0025-7974
DOI - 10.1097/md.0000000000021614
Subject(s) - medicine , cochrane library , meta analysis , medline , publication bias , systematic review , random effects model , forest plot , china , covid-19 , pneumonia , family medicine , disease , political science , infectious disease (medical specialty) , law
Background : As of June 2020, more than 7 million cases of coronavirus disease (COVID-2019) have been reported worldwide. At present, there is no vaccine or antiviral for the novel coronavirus pneumonia. Lianhua Qingwen (LQ), a Chinese medicine formula, has been authorized by the Chinese government for treating COVID-2019. This systematic review and meta-analysis will evaluate the efficacy and safety of LQ on patients with COVID-19. Methods : Two independent reviewers will search the following databases of the China Biology Medicine disc, China National Knowledge Infrastructure, China Science and Technology Periodical Database, Wanfang database, Embase, PubMed, and Cochrane Library from the date of conception to June 1, 2020. We will use the MeSH/Emtree terms, combining free-text words that were properly adjusted for the different databases in all of the search strategies. We will take primary clinical symptoms, total efficacy, and adverse event into consideration for our primary outcomes. As secondary outcomes, we will estimate the chest computed tomography manifestations, the rate of conversion to severe cases, and secondary clinical symptoms. We will evaluate the quality of including studies through the risk of bias assessment tool provided by the Cochrane Collaboration. Fixed-or random-effect model will be utilized to calculate the overall pooled risk estimates. Forest plots will be generated to prove the pooled results. Sensitivity analysis will be carried out to identify sources of heterogeneity. The Begg rank correlation test and Egger linear regression test will be used to explore publication bias. Results : This systematic review and meta-analysis will compare the primary and secondary outcomes at baseline and endpoint in the treatment and control groups to investigate the efficacy and safety of LQ for treatment COVID-2019. Discussion: Data from this study will provide strong evidence for clinical decision if the findings are positive. PROSPERO registration number: CRD42020190757.