Toujie Quwen for COVID-19

BackgroundChinese herbal medicine (CHM) formulas played an important role during the pandemic of coronavirus disease 2019 (COVID-19). Many randomized controlled trials (RCTs) on CHM for COVID-19 were quickly published. Concerns have been raised about their quality. In addition, inadequate detailed information on CHM formula intervention may arouse suspicion about their effectiveness. We aim to assess the most recent evidence of the methodological reporting quality of these RCTs with strict randomization, and the precise reporting of the CHM formula intervention.MethodsRCTs on CHM formulas for COVID-19 were searched from nine databases. The CONSORT 2010, CONSORT-CHM Formulas 2017, and risk of bias were the guidelines used to assess the included RCTs. The checklist of sub-questions based on CONSORT-CHM Formulas 2017 was used to evaluate the precise reporting of CHM formula intervention. A comparison was made between RCTs that enrolled participants during and after the first wave of the pandemic (defined here as December 2019 to March 2020).ResultsThe average score for 66 studies evaluated based on three guidelines, the CONSORT 2010, the CONSORT-CHM Formulas 2017, and the checklist of sub-questions based on the CONSORT-CHM Formulas 2017, is 16.4, 15.2, and 17.2, respectively. The reporting rate of sample size calculation, allocation concealment, and blinding is less than 30%. The checklist of sub-questions based on the CONSORT-CHM formulas 2017 can help report and assess CHM formula intervention more precisely. Most studies assessed an “unclear risk of bias” due to insufficient information. RCTs published in English and recruited subjects during the first wave of the pandemic have a higher risk of participant blinding bias than the studies recruited subjects after that (P < 0.05).ConclusionThe methodological reporting quality in strictly randomized RCTs on CHM formulas for COVID-19 is inadequate—the reporting of sample size calculation, allocation concealment, and blinding need to improve especially. The checklist of sub-questions based on CONSORT-CHM formulas 2017 can help report and assess CHM formula intervention more precisely. The methodological reporting quality of RCTs published in English and enrolled participants during the first wave of the pandemic is worse than the studies that recruited subjects after the first wave of the pandemic.

Big data was utilized to analyze the network of biological systems and multi-target drug signal nodes, and despite traditional Chinese medicine proving effective against COVID-19 since the 2019 outbreak, the complexity and challenging actions of network pharmacology are essential for in-depth analysis. Objective: To present an overview of the literature on the mechanism of traditional Chinese medicine (TCM) in the treatment of COVID-19 based on network pharmacology. Methods: A succinct explanation of the data sources: Twenty items in all were found after browsing the English and Chinese data websites. Following screening, data synthesis techniques and the remaining eight publications were located. Results: This study contained eight publications, including network pharmacology investigations on the mechanisms of action of eight prescription TCM medications. Many prescription drugs and specialty treatments from traditional Chinese medicine, including astragalus membranaceus-atractylodes rhizoma, LHQW, TJQWG, ephedra and glycyrrhiza, Yinqiao powder, rhizoma polygonati, MXSGD, and HSBDF, have been utilized in the clinical treatment of COVID-19. Their primary modes of action entail several components working on many targets and pathways related to immune modulation, organ protection, antiviral, and anti-inflammatory properties. Conclusion: This study reviewed eight Chinese herbal formulas used for treating COVID-19 and found they all contain quercetin, a compound that may reduce lung damage, and target at least one of TNF, IL-2, or IL-6, potentially decreasing inflammation and boosting immunity. All these traditional Chinese medicine (TCM) treatments were effective against COVID-19, offering valuable insights and inspiration for future drug research.