Abstract
OBJECTIVE: This study aims to explore recent literature on gestational diabetes mellitus (GDM) screening, assessment, and monitoring and identifying research hotspots and future trends. METHODS: In this study, bibliometric methods were employed to analyze the literature related to the screening, assessment, and monitoring of GDM retrieved from the Web of Science Core Collection (WoSCC). Specifically, the analysis focused on the annual publication and citation trends of relevant literature, collaborative networks involving countries, institutions, authors, and journals, keyword co-occurrence analysis, reference co-citation analysis, historical evolution of the research field, and topic modeling. RESULTS: The results show a 50% rise in publications on gestational diabetes over the past 5 years, with the field experiencing distinct developmental stages from 1961 to 2026. China ranks first in global publication volume, while the United States leads in citation impact and international collaboration intensity. Keyword analysis identified three core clusters and a "three jumps and two rises" evolution pattern of citation bursts, with machine learning and adverse pregnancy outcomes emerging as ongoing high-burst-strength keywords. Latent Dirichlet allocation (LDA) topic modeling classified 16 optimal topics into four groups: Screening and Diagnostic Approaches, Pathophysiology and Molecular Mechanisms, Environmental, Social and Behavioral Determinants, and Clinical Management, Complications and Health Outcomes. CONCLUSION: The focus of GDM screening, assessment, and monitoring is shifting from traditional oral glucose tolerance test (OGTT)-based diagnosis to biomarker-based early prediction and AI-driven digital monitoring throughout pregnancy, highlighting the importance of patient characteristics and risk factors. Future research will contribute to improving clinical practices for gestational diabetes and enhancing maternal and infant health. This study's integrated bibliometric and LDA topic modeling approach clarifies the knowledge structure and evolutionary trends of the GDM screening-assessment-monitoring continuum, providing targeted new perspectives for further exploration in related fields.