Evidence map›Paper›PMID 34415962›Full record

SynthesisPloS one2021

Add-on effect of Chinese herbal medicine in the treatment of mild to moderate COVID-19: A systematic review and meta-analysis.

Xuqin Du, Lipeng Shi, Wenfu Cao, Biao Zuo, Aimin Zhou

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 5 pooled it
5.4field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 5 syntheses or guidelines pooled it, 36 citations in OpenAlex.

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  3. Herbal medicine for COVID-19: An overview of systematic reviews and meta-analysis.Phytomedicine : international journal of phytotherapy and phytopharmacology · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Xuqin DuCollege of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, People's Republic of China.
Lipeng ShiCollege of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, People's Republic of China.ORCID 0000-0002-4478-0622
Wenfu CaoCollege of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, People's Republic of China.
Biao ZuoCollege of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, People's Republic of China.
Aimin ZhouDepartment of Cardiovascular U nit, Traditional Chinese medicine hospital Dianjiang Chongqing, Chongqing, People's Republic of China.
First People's Hospital of Chongqing · CNThe Affiliated Yongchuan Hospital of Chongqing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCoronavirus disease 2019 (COVID-19) has emerged as a global pandemic since its outbreak in Wuhan, China. It is an urgent task to prevent and treat COVID-19 effectively early. In China's experience combating the COVID-19 pandemic, Chinese herbal medicine (CHM) has played an indispensable role. A large number of epidemiological investigations have shown that mild to moderate COVID-19 accounts for the largest proportion of cases. It is of great importance to treat such COVID-19 cases, which can help control epidemic progression. Many trials have shown that CHM combined with conventional therapy in the treatment of mild to moderate COVID-19 was superior to conventional therapy alone. This review was designed to evaluate the add-on effect of CHM in the treatment of mild to moderate COVID-19.

methodsEight electronic databases including PubMed, EMBASE, Cochrane Central Register of Controlled Trials, the Clinical Trials.gov website, China National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP), Wanfang Database and China Biology Medicine (CBM) were searched from December 2019 to March 2021 without language restrictions. Two reviewers searched and selected studies, and extracted data according to inclusion and exclusion criteria independently. Cochrane Risk of Bias (ROB) tool was used to assess the methodological quality of the included RCTs. Review Manager 5.3.0 software was used for statistical analysis.

resultsTwelve eligible RCTs including 1393 participants were included in this meta-analysis. Our meta-analyses found that lung CT parameters [RR = 1.26, 95% CI (1.15, 1.38), P<0.00001] and the clinical cure rate [RR = 1.26, 95%CI (1.16, 1.38), P<0.00001] of CHM combined with conventional therapy in the treatment of mild to moderate COVID-19 were better than those of conventional therapy. The rate of conversion to severe cases [RR = 0.48, 95%CI (0.32, 0.73), P = 0.0005], TCM symptom score of fever [MD = -0.62, 95%CI (-0.79, -0.45), P<0.00001], cough cases [RR = 1.43, 95%CI (1.16, 1.75), P = 0.0006], TCM symptom score of cough[MD = -1.07, 95%CI (-1.29, -0.85), P<0.00001], TCM symptom score of fatigue[MD = -0.66, 95%CI (-1.05, -0.28), P = 0.0007], and CRP[MD = -5.46, 95%CI (-8.19, -2.72), P<0.0001] of combination therapy was significantly lower than that of conventional therapy. The WBC count was significantly higher than that of conventional therapy[MD = 0.38, 95%CI (0.31, 0.44), P<0.00001]. Our meta-analysis results were robust through sensitivity analysis.

conclusionChinese herbal medicine combined with conventional therapy may be effective and safe in the treatment of mild to moderate COVID-19. More high-quality RCTs are needed in the future.

Indexed as

COVID-19 Drug TreatmentCoughCOVID-19DiarrheaDrugs, Chinese HerbalFeverHumansLungNauseaTomography, X-Ray ComputedTreatment OutcomeVomitingDrugs, Chinese Herbal

Identifiers

PMID34415962
PMCPMC8378756
OpenAlexW3195815599

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.