The published trend of studies on COVID-19 and diabetes: bibliometric analysis

Abstract

BackgroundSince the COVID-19 pandemic outbreak, diabetes mellitus (DM) has been at the core of the confirmed risk factors for fatal or critical care unit-treated COVID-19 and COVID-19 related complications. Although relevant studies on DM have developed rapidly during the COVID-19 pandemic. However, the aforementioned research results have not been systematically quantified by means of bibliometric analysis.PurposeThe purpose of this study is to provide a comprehensive analysis of the current status and trends of publications related to DM research during the COVID19 epidemic.MethodsA bibliometric analysis was performed using the Web of Science database. In this study, we used citespace, R software and R-Bibliometrix to analyze keywords, most-cited authors, most-cited countries, most-cited global documents, and co-occurrence and co-citation networks.ResultsA total of 1688 publications was included in this study. Investigators from the United States contributed the most publications. The United States, China and Europe have the most collaboration with the other countries/regions. A total of 3355 institutions made contributions to this study. Of the top 10 institutions with the most publications, N8 Research Partnership showed the most centrality. Among the top 10 journals, Diabetes Research and Clinical Practice published the most articles. Among authors included, Khunti Kamlesh is rated first with 27 papers and has the highest centrality. The most frequently co-cited article is entitled “Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study”. The most popular keywords included diabetes, mortality, diabetes, outcome, occurrences, risk, and type 1 diabetes.ConclusionThis bibliometric study provides an overall picture of DM research and research trends during the COVID-19 pandemic and provides a basis for researchers to develop their next research strategies.

Mapping knowledge landscapes and emerging trends of Marburg virus: A text-mining study

“…Especially during the global pandemic of COVID-19, the number of relevant studies has increased rapidly. Many scholars have utilized the bibliometric method to aid in comprehending the prevalence of COVID-19 and the evolution of treatment and prevention approaches, especially vaccines [ [21] , [22] , [23] , [24] , [25] , [26] ]. Moreover, the application of bibliometric analysis could also facilitate an evaluation of scientific influence and research quality within specific domains and direct scientists and policymakers in establishing priority research areas while providing decision-making support for infectious disease prevention and control strategies [ [18] , [19] , [20] ].…”

“…For instance, in the field of infectious diseases, the global COVID-19 pandemic triggered by the novel coronavirus in 2019 became a pivotal research subject in the biomedical domain. A substantial amount of bibliometric analysis has summarized various aspects of COVID-19, including its pathogenesis, vaccine development, and prognosis [ [21] , [22] , [23] , [24] , [25] , [26] ]. However, we note the scarcity of scholarly literature conducting bibliometric analyses in the domains of the Marburg virus or Ebola virus [ 27 , 28 ].…”