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A bibliometric analysis of research related Chinese Medicine in the prevention and treatment of corona virus disease 2019

OBJECTIVE: To perform a bibliometric analysis of published research related to the use of traditional Chinese medicine (TCM) for the treatment of Coronavirus Disease 2019 (COVID-19). METHODS: Research documents related to the use of TCM for prevention and treatment of COVID-19 published up to Septem...

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Detalles Bibliográficos
Autores principales: Dayuan, Zhong, Lan, Li, Luhua, Xu, Huanjie, Li, Dahao, Chen, Yumiao, Luo, Dingxiang, Li, Yihui, Deng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9575316/
https://www.ncbi.nlm.nih.gov/pubmed/36278116
http://dx.doi.org/10.1016/j.heliyon.2022.e11120
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author Dayuan, Zhong
Lan, Li
Luhua, Xu
Huanjie, Li
Dahao, Chen
Yumiao, Luo
Dingxiang, Li
Yihui, Deng
author_facet Dayuan, Zhong
Lan, Li
Luhua, Xu
Huanjie, Li
Dahao, Chen
Yumiao, Luo
Dingxiang, Li
Yihui, Deng
author_sort Dayuan, Zhong
collection PubMed
description OBJECTIVE: To perform a bibliometric analysis of published research related to the use of traditional Chinese medicine (TCM) for the treatment of Coronavirus Disease 2019 (COVID-19). METHODS: Research documents related to the use of TCM for prevention and treatment of COVID-19 published up to September 19, 2021, were retrieved from the Web of Science database. Bibliometrix R 4.0 software package was used to analyze data, including countries of publication, research institutions, journals, citations, and keywords. Further analysis was conducted to identify co-occurrence of keywords in the documents, including their titles and abstracts. Cooperative network analyses of authors, institutions, and countries of publication were also conducted. The classification types were statistically analyzed and the research progress of key TCMs was reviewed. RESULTS: A total of 417 documents were included in our analysis. Of these, 85.13% originated in China. Of the 417 documents, 148 (35.5%) were published in journals with impact factors in quartile 1 and 164 (39.3%) in journals in quartile 2. The documents were mainly published in journals categorized as Medicine. The results of network analysis showed close cooperation between institutions and countries. Excluding disease- and drug-related keywords, the top four keywords were ‘Systematic review’, ‘Network pharmacology’, ‘Medicine’ and ‘Molecular docking’. Keyword co-occurrence analysis showed 4 main keywords association groups. Statistical analysis of the TCM studies showed that Lianhua Qingwen capsule, Qingfei Paidu decoction, Shufeng Jiedu capsules and ReDuNing injection were the most studied Chinese medicines. Lianhua Qingwen capsules, Qingfei Paidu decoction, ReDuNing injection, and Shufeng Jiedu capsules were used in clinical, bioinformatics, and basic research. Toujie Quwen granule, Jinhua Qinggan granule, Shuanghuanglian oral liquid, Tanreqing injection, and Xuanfei Baidu decoction were used in clinical and bioinformatics research, although basic research on their mechanisms of action is lacking. CONCLUSION: Research intensity and recognition, as well as cooperation, in the field of Chinese medicine for the prevention and treatment of COVID-19 has increased. Research types are generally comprehensive, and investigated several TCM formulations that are specifically recommended by Chinese COVID-19 guidelines. However, comprehensive, in-depth research on their molecular mechanisms of action is still lacking. More basic research is thus needed to identify therapeutic mechanisms to standardize and validate the use of TCM in the prevention and treatment of COVID-19.
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spelling pubmed-95753162022-10-17 A bibliometric analysis of research related Chinese Medicine in the prevention and treatment of corona virus disease 2019 Dayuan, Zhong Lan, Li Luhua, Xu Huanjie, Li Dahao, Chen Yumiao, Luo Dingxiang, Li Yihui, Deng Heliyon Review Article OBJECTIVE: To perform a bibliometric analysis of published research related to the use of traditional Chinese medicine (TCM) for the treatment of Coronavirus Disease 2019 (COVID-19). METHODS: Research documents related to the use of TCM for prevention and treatment of COVID-19 published up to September 19, 2021, were retrieved from the Web of Science database. Bibliometrix R 4.0 software package was used to analyze data, including countries of publication, research institutions, journals, citations, and keywords. Further analysis was conducted to identify co-occurrence of keywords in the documents, including their titles and abstracts. Cooperative network analyses of authors, institutions, and countries of publication were also conducted. The classification types were statistically analyzed and the research progress of key TCMs was reviewed. RESULTS: A total of 417 documents were included in our analysis. Of these, 85.13% originated in China. Of the 417 documents, 148 (35.5%) were published in journals with impact factors in quartile 1 and 164 (39.3%) in journals in quartile 2. The documents were mainly published in journals categorized as Medicine. The results of network analysis showed close cooperation between institutions and countries. Excluding disease- and drug-related keywords, the top four keywords were ‘Systematic review’, ‘Network pharmacology’, ‘Medicine’ and ‘Molecular docking’. Keyword co-occurrence analysis showed 4 main keywords association groups. Statistical analysis of the TCM studies showed that Lianhua Qingwen capsule, Qingfei Paidu decoction, Shufeng Jiedu capsules and ReDuNing injection were the most studied Chinese medicines. Lianhua Qingwen capsules, Qingfei Paidu decoction, ReDuNing injection, and Shufeng Jiedu capsules were used in clinical, bioinformatics, and basic research. Toujie Quwen granule, Jinhua Qinggan granule, Shuanghuanglian oral liquid, Tanreqing injection, and Xuanfei Baidu decoction were used in clinical and bioinformatics research, although basic research on their mechanisms of action is lacking. CONCLUSION: Research intensity and recognition, as well as cooperation, in the field of Chinese medicine for the prevention and treatment of COVID-19 has increased. Research types are generally comprehensive, and investigated several TCM formulations that are specifically recommended by Chinese COVID-19 guidelines. However, comprehensive, in-depth research on their molecular mechanisms of action is still lacking. More basic research is thus needed to identify therapeutic mechanisms to standardize and validate the use of TCM in the prevention and treatment of COVID-19. Elsevier 2022-10-17 /pmc/articles/PMC9575316/ /pubmed/36278116 http://dx.doi.org/10.1016/j.heliyon.2022.e11120 Text en © 2022 Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Review Article
Dayuan, Zhong
Lan, Li
Luhua, Xu
Huanjie, Li
Dahao, Chen
Yumiao, Luo
Dingxiang, Li
Yihui, Deng
A bibliometric analysis of research related Chinese Medicine in the prevention and treatment of corona virus disease 2019
title A bibliometric analysis of research related Chinese Medicine in the prevention and treatment of corona virus disease 2019
title_full A bibliometric analysis of research related Chinese Medicine in the prevention and treatment of corona virus disease 2019
title_fullStr A bibliometric analysis of research related Chinese Medicine in the prevention and treatment of corona virus disease 2019
title_full_unstemmed A bibliometric analysis of research related Chinese Medicine in the prevention and treatment of corona virus disease 2019
title_short A bibliometric analysis of research related Chinese Medicine in the prevention and treatment of corona virus disease 2019
title_sort bibliometric analysis of research related chinese medicine in the prevention and treatment of corona virus disease 2019
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9575316/
https://www.ncbi.nlm.nih.gov/pubmed/36278116
http://dx.doi.org/10.1016/j.heliyon.2022.e11120
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