Evidence Hub

Chinese herbal medicine for coronavirus disease 2019: A systematic review and meta-analysis

Xiong X, Wang P, Su K, Cho WC, Xing Y

Pharmacological research, 2020

2,275 participants · 159 citations

Abstract

Currently, coronavirus disease 2019 (COVID-19), which can lead to severe respiratory failure and death, is now a global pandemic with no specific anti-viral drugs or vaccines. However, It is worth noting that traditional Chinese medicine (TCM), especially Chinese herbal medicine (CHM), has been widely applied in mainland China since outbreak, bringing new hope for the prevention and control of COVID-19. A comprehensive literature searching was conducted in 7 electronic databases from their inception up to June 21, 2020 to evaluate the efficacy and safety of CHM for COVID-19. Eighteen randomized controlled trials (RCTs) involving 2275 patients were enrolled. Most of CHMs were originated from classical Chinese herbal formulas. Liquoric Root (Gancao, Radix Glycyrrhizae), Baical Skullcap Root (Huangqin, Radix Scutellariae Baicalensis), Pinellia Rhizome (Banxia, Rhizoma Pinelliae Tematae), Forsythia Fruit (Lianqiao, Fructus Forsythiae Suspensae), and Bitter Apricot Seed (Kuxingren, Semen Armeniacae Amarum) were most frequently used Chinese herbs. The most commonly used dosage formulation was decoction. Our meta-analyses found that comparing CHM group and conventional western medicine group, CHM group has improvements in several clinical parameters including lung CT, clinical cure rate, ranging from mild to critical cases, length of hospital stay, total score of clinical symptoms, fever reduction time, symptom score of fever, number of cough reduction cases, symptom score of…

How strong is the evidence?

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: 2,275 participants or records.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free