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dc.contributor.authorLuo, Xufei et al.
dc.description.abstractBackground: Chinese herbal medicine (CHM) is thought to be a potential intervention in the treatment of coronavirus disease (COVID-19). Purpose: This study aimed to investigate the efficacy and safety of CHM or CHM combination therapy for COVID-19. Study design: Systematic review and meta-analysis Methods: We searched for relevant studies in the CNKI, CBM, Wanfang Data, PubMed, Cochrane Library, Embase, and other resources from their inception to April 15, 2020. Randomized controlled trials, cohort studies, and case-control studies on CHM or CHM combination therapy for COVID-19 were included. Meta-analysis was performed according to the Cochrane Handbook. Results: Overall, 19 studies with 1474 patients were included. Meta-analysis showed that the overall clinical effectiveness (OR = 2.67, 95% CI 1.83-3.89, I2 = 0%), improvement in the CT scan (OR = 2.43, 95% CI 1.80-3.29, I2 = 0%), percentage of cases turning to severe/critical (OR = 0.40, 95% CI 0.24-0.67, I2 = 17.1%), reverse transcription-polymerase chain reaction (RT-PCR) negativity rate (OR = 2.55, 95% CI 1.06-6.17, I2 = 56.4%) and disappearance rate of symptoms (fever, cough, and fatigue) were superior by combined CHM treatment of COVID-19. However, there was no statistical difference between the two groups in terms of length of hospital stay (WMD = -0.46, 95% CI -3.87 - 2.95, I2 = 99.5%), and rate of adverse effects (OR = 1.21, 95% CI 0.48-3.07, I2 = 43.5%). The quality of evidence was very low to low. Conclusion: The combined treatment of COVID-19 with Chinese and Western medicine may be effective in controlling symptoms and reducing the rate of disease progression due to low quality evidence.en_US
dc.subjectHerbal Medicineen_US
dc.subjectSystematic Reviewen_US
dc.titleThe add-on effect of Chinese herbal medicine on COVID-19: A systematic review and meta-analysisen_US
eihealth.categoryCandidate therapeutics RDen_US
eihealth.typePublished Articleen_US
eihealth.maincategorySave Lives / Salvar Vidasen_US

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