Traditional Chinese Medicine for COVID-19: A Network Meta-Analysis and Systematic Review.

Abstract

To compare the efficacy of different traditional Chinese medicine (TCM) therapies for the treatment of coronavirus disease 2019 (COVID-19) and provide a higher level of evidence in the form of network meta-analysis (NMA) and systematic review. We searched the studies from the following databases: CNKI, VIP, WanFang, SinoMed, PubMed, Embase, and Web of Science from the establishment of the respective database until December 2021. Relevant studies were screened according to the pre-established inclusion criteria. The quality of the included randomized controlled trials (RCTs) and controlled clinical trials (CCTs) were assessed using the risk of bias (ROB) tool and the Methodological Index for Non-Randomized Studies (MINORS), respectively. R software 4.1.1 and Stata 13.1 were used for data analysis and mapping. A total of 34 studies were included in this network meta-analysis that tested 24 TCM interventions and included 3443 patients. Using cluster analysis of time to negative SARS-CoV-2 reverse transcription-polymerase chain reaction (RT-PCR), the length of hospital stay and composite events, we found that Jinyinhua oral liquid (JYH, 120 mL) + conventional Western medicine (CWM) has the highest SUCRA value at 88.64%, 85.61% and 84.24%. The traditional meta-analysis results revealed that Qingfei Paidu decoction + CWM were significantly different compared with CWM alone for the score of clinical symptoms (MD =-0.75, 95% CI [-1.04, -0.47]). Nine studies reported 57 adverse reactions (ADRs) and 3 adverse events (ADEs) in TCM + CWM groups, and eight studies reported 33 ADRs and 8 ADEs in CWM groups. In conclusion, the combination of TCM and CWM approaches may enhance the efficacy of CWM in COVID-19 patients. Based on the NMA result, JYH (120 mL) + CWM may be a more effective treatment and deserves further investigation. However, the differences in many comparisons between TCM interventions did not reach statistical significance; therefore, further high-quality studies are required to validate these findings.