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1000 Titel
  • Traditional Chinese herbal medicine for treating novel coronavirus (COVID-19) pneumonia: protocol for a systematic review and meta-analysis
1000 Autor/in
  1. Li, Yuxi |
  2. Liu, Xiaobo |
  3. Guo, Liuxue |
  4. Li, Juan |
  5. Zhong, Dongling |
  6. Zhang, Yonggang |
  7. Clarke, Mike |
  8. Jin, Rongjiang |
1000 Erscheinungsjahr 2020
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2020-04-08
1000 Erschienen in
1000 Quellenangabe
  • 9:75
1000 Copyrightjahr
  • 2020
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1186/s13643-020-01343-4 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7138957/ |
1000 Ergänzendes Material
  • https://systematicreviewsjournal.biomedcentral.com/articles/10.1186/s13643-020-01343-4#Sec18 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • BACKGROUND: A new type of coronavirus, novel coronavirus (COVID-19), is causing an increasing number of cases of pneumonia and was declared a Public Health Emergency of International Concern by the World Health Organization on 30 January 2020. The virus first appeared in Wuhan, China, in late December 2019, and traditional Chinese herbal medicine is being used for its treatment. This systematic review and meta-analysis will assess studies of the effects of traditional Chinese herbal medicine in COVID-19 pneumonia. METHODS: We will search electronic databases including PubMed, Embase, the Cochrane Central Register of Controlled Trials (CENTRAL), Chinese Biomedical Literature Database (CBM), China National Knowledge Infrastructure (CNKI), Chinese Science and Technology Periodical Database (VIP), and Wanfang database using keywords related to COVID-19 and traditional Chinese herbal medicine. Reference lists of relevant trials and reviews will be searched. We will manually search gray literature, such as conference proceedings and academic degree dissertations, and trial registries. Two independent reviewers will screen studies (XL and DZ), extract data (YL and LG), and evaluate risk of bias (YL and DZ). Data analysis will be conducted using the Review Manager software (version 5.3.5) and R software (version 3.6.1). Statistical heterogeneity will be assessed using a standard chi-square test with a significance level of P < 0.10. Biases associated with study size (e.g., publication bias) will be investigated using funnel plots, Egger’s test and Begg’s test, and Trim and Fill analysis. DISCUSSION: This study will provide a high-quality synthesis of the effects of traditional Chinese herbal medicine for COVID-19. The use of traditional Chinese herbal medicine for treatment or prevention of these novel viral infections affecting the pneumonia will be investigated.
1000 Sacherschließung
gnd 1206347392 COVID-19
lokal Traditional Chinese herbal medicine emerging infectious diseases
lokal Systematic review
lokal Meta-analysis
lokal Pneumonia
lokal Coronavirus
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/TGksIFl1eGk=|https://frl.publisso.de/adhoc/uri/TGl1LCBYaWFvYm8=|https://frl.publisso.de/adhoc/uri/R3VvLCBMaXV4dWU=|https://frl.publisso.de/adhoc/uri/TGksIEp1YW4=|https://frl.publisso.de/adhoc/uri/WmhvbmcsIERvbmdsaW5n|https://frl.publisso.de/adhoc/uri/WmhhbmcsIFlvbmdnYW5n|https://frl.publisso.de/adhoc/uri/Q2xhcmtlLCBNaWtl|https://frl.publisso.de/adhoc/uri/SmluLCBSb25namlhbmc=
1000 Label
1000 Förderer
  1. Chengdu University of Traditional Chinese Medicine |
1000 Fördernummer
  1. -
1000 Förderprogramm
  1. Education Foundation
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Chengdu University of Traditional Chinese Medicine |
    1000 Förderprogramm Education Foundation
    1000 Fördernummer -
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6423647.rdf
1000 Erstellt am 2020-10-19T15:56:13.666+0200
1000 Erstellt von 218
1000 beschreibt frl:6423647
1000 Bearbeitet von 25
1000 Zuletzt bearbeitet 2020-11-18T11:21:00.278+0100
1000 Objekt bearb. Wed Nov 18 11:21:00 CET 2020
1000 Vgl. frl:6423647
1000 Oai Id
  1. oai:frl.publisso.de:frl:6423647 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
1000 Gegenstand von

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