Bibliometric analysis of researches on traditional Chinese medicine for coronavirus disease 2019 (COVID-19)

Cargando...
Miniatura

Fecha

Fecha

2020

Director de trabajo de grado

Título de la revista

Abrir versión en línea

ISSN de la revista

Título del volumen

Editor

Integrative Medicine Research

Seleccione un documento PDF para visualizar

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.

Descripción

Palabras clave

COVID-19, Traditional Chinese medicine, Bibliometrics, Visual analysis

Citación

Aprobación

Revisión

Complementado por

Referenciado por