Bibliometric analysis of the most cited articles on COVID-19 in Web of Science

Authors

  • Ignacio Ladrero Paños Graduado en Enfermería y Medicina. Servicio de Urgencias y Emergencias 061 Aragón
  • José Antonio Salvador Oliván Licenciado y Doctor en Medicina. Profesor Titular del departamento de Ciencias de la Documentación e HIstoria de la Ciencia. Universidad de Zaragoza

DOI:

https://doi.org/10.60108/ce.171

Keywords:

bibliometrics; indicators of scientific production; COVID-19; coronavirus; bibliometric analysis

Abstract

As a result of the pandemic caused by the SARS-CoV-2 virus, the number of publications has increased exponentially. The objective of this study is to perform a bibliometric analysis to identify and analyze the characteristics of the most cited articles related to COVID-19. The 200 most cited and published documents on COVID-19 in 2020 were selected from the main WoS collection. Bibliometric indicators of production, collaboration and impact were used, and the type of study, the level of evidence were evaluated and a content analysis was carried out through the MeSH terms. Most of the documents were original articles. The New England Journal of Medicine was the one with the highest impact factor (74,699) and published most of the papers (11.6%). China was the country of the authors who published more than half of the documents and collaborated mainly with the United States, England and Germany. The four authors' institutions that received the most citations were located in China. Most of the articles provided information on clinical outcomes and the main keywords corresponded to the different names of the virus causing the pandemic. More than 90% of the articles offered a grade IV level of evidence and only 8 experimental works were found. Most of the most cited articles present a low level of evidence and mainly offer information on clinical outcomes.

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Published

2021-11-02

How to Cite

Ladrero Paños, I., & Salvador Oliván, J. A. (2021). Bibliometric analysis of the most cited articles on COVID-19 in Web of Science. Conocimiento Enfermero, 4(14), 63–82. https://doi.org/10.60108/ce.171