A Bibliometric Analysis of the Top 30 Most-cited Articles in Gestational Diabetes Mellitus Literature (1946-2019).

Objective The aim of this bibliometric analysis is to evaluate the importance and impact of the articles that have been published with the title gestational diabetes mellitus (GDM) in the specialty of obstetrics & gynecology and endocrinology during the period 1946-2019. It also reveals that the area of GDM has received increased attention and interest by researchers, research funding institutions, and practitioners. Material and methods A thorough database search of Scopus and Web of Science was performed and the articles pertaining to gestational diabetes mellitus that were published between 1946 and 2019 were reviewed by two reviewers, Iftikhar PM and Ali F, with respect to their year of publication, authors, country of origin, journal of publication, and the affiliated institutions of the authors as well as journals. Institutional review board approval was not required for this study, as the data being analyzed were already available electronically, and otherwise, in libraries and databases. Results The 30 most-cited articles on gestational diabetes mellitus were thoroughly analyzed. The top article was cited 5028 times while the least number of citations for any article was 328. Among these 30 articles, five were published in the year 2005, which is the highest number of publications in any given year of the timeline being considered in this study. Most of the articles (n = 18) were from the United States of America, followed by Australia (n = 3); other countries contributed to two or fewer articles. Diabetes Care made most (n = 8) of the list. We found one author who had three publications and the rest contributed two or less articles. The top article in our study was cited almost 5028 times; meanwhile, there are 13 journals from different specialties that have referenced the most cited articles pertaining to gestational diabetes. Conclusion Our bibliometric analysis provides a picture of scientific research, which will help in evidence-based descriptions, comparisons, and visualizations of research output in GDM, and it can be used to explicate and describe the patterns of performance and impact of GDM research.