Bibliometric analysis of researches on traditional Chinese medicine for coronavirus disease 2019 (COVID-19)
Autor
Yang, Ke-Lu
Jin, Xin-Yao
Gao, Ya
Xie, Jin
Liu, Ming
Zhang, Jun-Hua
Tian, Jin-Hui
Institución
Resumen
Background: The coronavirus disease 2019 (COVID-19) has caused a
worldwide pandemic, and traditional Chinese medicine (TCM) has
played an important role in response. We aimed to analyze the published
literature on TCM for COVID-19, and provide reference for later
research.
Methods: This study searched the CBM, CNKI, PubMed, and EMBASE
from its establishment to March 11, 2020. VOSviewer 1.6.11 and
gCLUTO 2.0 software were used to visually analyze the included studies.
Results: A total of 309 studies were included, including 61 journals, 1441
authors, 277 institutions, and 27 provinces. Cooperation among regions
was closer, but the teamwork of institutions and authors were more likely
to be confined to the same region. Among the authors with frequency greater than two (65 authors), only 19 authors who had connection with
others. More than 70% (358/491) of keywords only presented once, and
20 keywords shown more than 10 times. Five research topics were
identified: Data mining method based analysis on the medication law of
Chinese medicine in prevention and management of COVID-19,
exploration of active compounds of Chinese medicine for COVID-19
treatment based on network pharmacology and molecular docking, expert
consensus and interpretation of COVID-19 treatment, research on the
etiology and pathogenesis of COVID-19, and clinical research of TCM
for COVID-19 treatment. Conclusion: The research hotspots were scattered, and the collaboration
between authors and institutions needed to be further strengthened. To
improve the quality and efficiency of research output, the integration of
scientific research and resources, as well as scientific collaboration is
needed.