ReviewInternational journal of molecular sciences2024
Predictive Utility of Biochemical Markers for the Diagnosis and Prognosis of Gestational Diabetes Mellitus.
Review in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Role of adiponectin in gestational diabetes mellitus: advances in mechanistic insights and early predictive potential.Adipocyte · 2026Review
- Dual-center prospective validation of an early second-trimester predictive model integrating BMI trajectories and pathophysiological biomarkers for gestational diabetes risk stratification.Journal of diabetes investigation · 2026Article
- Editorial: Recent advances in gestational diabetes: diagnosis, treatment and prevention.Frontiers in endocrinology · 2026Article
- Emerging biomarkers for gestational diabetes mellitus and related pediatric outcomes.World journal of clinical pediatrics · 2025Review
- From Molecular Insights to Clinical Management of Gestational Diabetes Mellitus-A Narrative Review.International journal of molecular sciences · 2025Review
- Evaluating the Predictive Value of HOMA-IR in Gestational Diabetes: A Case-Control Study from Romania.Diagnostics (Basel, Switzerland) · 2025Article
- Role of random blood glucose and HbA1c levels in optimizing glucose tolerance screening in early pregnancy: a retrospective cohort study.Obstetrics & gynecology science · 2025Article
- Plasma sFRP4 Levels and Their Relationship with HOMA IR in Women with Gestational Diabetes Mellitus.Medical journal of the Islamic Republic of Iran · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Gestational diabetes mellitus (GDM) is a common complication during pregnancy with an increasing prevalence worldwide. Early prediction of GDM and its associated adverse outcomes is crucial for timely intervention and improved maternal and fetal health. The objective of this review is to provide a comprehensive summary of contemporary evidence on biomarkers, focusing on their potential to predict the development of GDM and serve as predictors of maternal, fetal, and neonatal outcomes in women with GDM. A literature search was conducted in the PubMed database using relevant terms. Original research articles published in English between 1 January 2015, and 30 June 2024, were included. A two-stage screening process was employed to identify studies on biomarkers for GDM diagnosis and prognosis and to evaluate the evidence for each biomarker's diagnostic performance and its potential prognostic correlation with GDM. Various biochemical markers, including adipokines, inflammatory markers, insulin resistance markers, glycemic markers, lipid profile markers, placenta-derived markers, and other related markers, have shown promise in identifying women at risk of developing GDM and predicting adverse pregnancy outcomes. Several promising markers with high predictive performance were identified. However, no single biomarker has demonstrated sufficient accuracy to replace the current diagnostic criteria for GDM. The complexity of multiple pathways in GDM pathogenesis highlights the need for a multi-marker approach to improve risk stratification and guide personalized management strategies. While significant progress has been made in GDM biomarker research, further studies are required to refine and validate these markers for clinical use and to develop a comprehensive, evidence-based approach to GDM prediction and management that can improve maternal and child health outcomes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.