Background: Coronavirus disease 2019 (COVID-19)-associated mucormycosis (CAM) is a relatively new concept in the literature that emerged during the pandemic. Bibliometric analysis is a type of analysis that uses mathematical and statistical methods to study the formal properties of knowledge areas. This study aimed to reveal the main themes, conceptual structures, and trends of bibliometric studies on mucormycosis in 2 different periods, pre-and during the pandemic.

Methods: This study consisted of 2 periods: pre-COVID-19 and COVID-19. Articles were collected from the Web of Science (WOS) Core Collection database. We provided AND and OR connectors for the keyword query and selected studies based on relevant keywords. Collected data were classified based on their publication date and examined using the R programming language (Version 4.0.3) package Bibliometrix and SciMAT Software.

Results: A total of 1261 articles were investigated, and performance and information structure analyses were conducted. Based on Bradford's law, the Journal of Fungi was the top-ranked journal in both periods. Cureus and mycoses were placed 2nd and 3rd in the second period. India is the largest contributor. In performance analysis, conceptual structures such as Rhizopus oryzae, epidemiology, diagnosis, management, treatment, and outcomes were at the forefront of mucormycosis publications during the COVID-19 period.

Conclusions: Research trends have shifted to the clinical treatment and management of COVID-19. Therefore, pathogenesis, diagnosis, follow-up, and treatment strategies for CAM should be developed in the future.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9726392PMC
http://dx.doi.org/10.1097/MD.0000000000032118DOI Listing

Publication Analysis

Top Keywords

bibliometric analysis
8
conceptual structures
8
evaluation covid-19
4
covid-19 pandemic
4
mucormycosis
4
pandemic mucormycosis
4
mucormycosis studies
4
studies bibliometric
4
analysis
4
analysis background
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!