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©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Diabetes. Oct 15, 2025; 16(10): 111309
Published online Oct 15, 2025. doi: 10.4239/wjd.v16.i10.111309
Published online Oct 15, 2025. doi: 10.4239/wjd.v16.i10.111309
Advances in gestational diabetes mellitus screening: Emerging trends and future directions
Didem Kaymak, Department of Perinatology, Istanbul Education and Research Hospital, Istanbul 34098, Türkiye
Ayse Seval Ozgu-Erdinc, Department of Perinatology, University of Health Sciences, Ankara Bilkent City Hospital, Ankara TR-06800, Türkiye
Author contributions: Kaymak D and Erdinc-Ozgu AS jointly contributed to the writing, editing, and final approval of the manuscript.
Conflict-of-interest statement: The authors declare no conflict of interests for this article.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Ayse Seval Ozgu-Erdinc, MD, Full Professor, Department of Perinatology, University of Health Sciences, Ankara Bilkent City Hospital, Üniversiteler Mahallesi 1604. Cadde No. 9 Bilkent/Çankaya, Ankara TR-06800, Türkiye.
Received: June 27, 2025
Revised: July 14, 2025
Accepted: September 10, 2025
Published online: October 15, 2025
Processing time: 110 Days and 11.9 Hours
Revised: July 14, 2025
Accepted: September 10, 2025
Published online: October 15, 2025
Processing time: 110 Days and 11.9 Hours
Core Tip
Core Tip: This review offers an integrative and up-to-date overview of gestational diabetes mellitus (GDM), emphasizing the evolving understanding of its pathophysiology and the emerging role of multi-modal biomarkers in early prediction. By combining evidence on metabolic, inflammatory, placental, genetic, and urinary biomarkers, alongside advanced machine learning-based models, this work underscores the shift toward precision diagnostics. It critically evaluates conventional screening strategies and highlights avenues for improving early detection and individualized care. The synthesis aims to support clinicians and researchers in refining GDM risk stratification and mitigating long-term maternal-fetal consequences.