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Drug treatments for covid-19: living systematic review and network meta-analysis

R. Siemieniuk, J. Bartoszko, L. Ge, D. Zeraatkar, A. Izcovich, H. Pardo-Hernandez, B. Rochwerg, F. Lamontagne et al.

British medical journal, 2020

1,000 participants · 719 citations

Abstract

Abstract Objective To compare the effects of treatments for coronavirus disease 2019 (covid-19). Design Living systematic review and network meta-analysis. Data sources US Centers for Disease Control and Prevention COVID-19 Research Articles Downloadable Database, which includes 25 electronic databases and six additional Chinese databases to 20 July 2020. Study selection Randomised clinical trials in which people with suspected, probable, or confirmed covid-19 were randomised to drug treatment or to standard care or placebo. Pairs of reviewers independently screened potentially eligible articles. Methods After duplicate data abstraction, a bayesian random effects network meta-analysis was conducted. Risk of bias of the included studies was assessed using a modification of the Cochrane risk of bias 2.0 tool, and the certainty of the evidence using the grading of recommendations assessment, development and evaluation (GRADE) approach. For each outcome, interventions were classified in groups from the most to the least beneficial or harmful following GRADE guidance. Results 23 randomised controlled trials were included in the analysis performed on 26 June 2020. The certainty of the evidence for most comparisons was very low because of risk of bias (lack of blinding) and serious imprecision. Glucocorticoids were the only intervention with evidence for a reduction in death compared with standard care (risk difference 37 fewer per 1000 patients, 95% credible interval 63 fewer to…

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Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 1,000 participants or records.

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