ABSTRACT
Background
Viral pneumonia (VP) is becoming a persistent and pervasive burden of disease. Traditional Chinese medicine Injections (TCMIs) have been proved effective in the treatment of patients with VP, which are now widely used in China. The evidence of TCMIs for VP is evolving rapidly. This study aims to assess the comparative efficacy and safety of TCMIs to provide more evidence and sights for the treatment selection of VP.
Research design and methods
Seven databases were searched from their inception up to 16 March 2022. Only randomized controlled trials (RCTs) are included to compare the efficacy and safety of antiviral TCMIs for the treatment of viral pneumonia. Clinical efficacy and rate of adverse events were considered as primary outcomes.
Results
A total of 76 RCTs with eight TCMIs comprising 7925 patients were included in the NMA. According to NMA, Reduning Injection combined with conventional antiviral drugs (CAD) produced superior effects in the effective outcomes and reduced the adverse event incidence rate of VP.
Conclusions
This study indicated that TCMIs combined with CAD was more effective and safer than CAD monotherapy and compared different TCMIs therapies, which provided guidance and reference for the selection of clinical treatment medication.
Declaration of interest
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
Reviewer disclosures
Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.
Author contributions
All authors should have substantially contributed to the conception and design of the review article. Meng-Ting Li had full access to all of the data in the study, performed writing-original drafts and conceptualization, and took responsibility for the integrity of the data, and the accuracy of the data analysis. Ji-Sheng Chen and Zhi-Kun Qiu made the final decision to submit for publication. Meng-Ting Li, Jia Wang, and Jia Hu contributed to data acquisition, analysis, and interpretation.
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/14787210.2022.2142119