Refining the diagnosis of gestational diabetes mellitus: a systematic review and meta-analysis

Authors

Ellen C. Francis, Rutgers School of Public Health
Camille E. Powe, Massachusetts General Hospital
William L. Lowe, Northwestern University Feinberg School of Medicine
Sara L. White, King's College London
Sara L. White, King's College London
Denise M. Scholtens, Northwestern University Feinberg School of Medicine
Jiaxi Yang, NUS Yong Loo Lin School of Medicine
Yeyi Zhu, Kaiser Permanente
Cuilin Zhang, NUS Yong Loo Lin School of Medicine
Marie France Hivert, Massachusetts General Hospital
Marie France Hivert, Massachusetts General Hospital
Soo Heon Kwak, Seoul National University College of Medicine
Arianne Sweeting, Faculty of Medicine and Health
Paul W. Franks, Harvard T.H. Chan School of Public Health
Stephen S. Rich, University of Virginia School of Medicine
Robert Wagner, Deutsches Diabetes-Zentrum
Tina Vilsbøll, Steno Diabetes Center Copenhagen
Kimberly K. Vesco, Kaiser Permanente Center for Health Research
Miriam S. Udler, Massachusetts General Hospital
Tiinamaija Tuomi, Helsinki University Hospital
Emily K. Sims, Indiana University School of Medicine
Jennifer L. Sherr, Yale School of Medicine
Robert K. Semple, Edinburgh Medical School
Rebecca M. Reynolds, Edinburgh Medical School
Maria J. Redondo, Baylor College of Medicine
Leanne M. Redman, Pennington Biomedical Research Center
Richard E. Pratley, AdventHealth Translational Research Institute
Rodica Pop-Busui, University of Michigan Medical School
Toni I. Pollin, University of Maryland School of Medicine
Wei Perng, University of Colorado Anschutz Medical Campus
Ewan R. Pearson, University of Dundee School of Medicine
Susan E. Ozanne, University of Cambridge
Katharine R. Owen, University of Oxford Medical Sciences Division
Richard Oram, University of Exeter Medical School

Document Type

Article

Publication Date

12-1-2023

Abstract

Background: Perinatal outcomes vary for women with gestational diabetes mellitus (GDM). The precise factors beyond glycemic status that may refine GDM diagnosis remain unclear. We conducted a systematic review and meta-analysis of potential precision markers for GDM. Methods: Systematic literature searches were performed in PubMed and EMBASE from inception to March 2022 for studies comparing perinatal outcomes among women with GDM. We searched for precision markers in the following categories: maternal anthropometrics, clinical/sociocultural factors, non-glycemic biochemical markers, genetics/genomics or other -omics, and fetal biometry. We conducted post-hoc meta-analyses of a subset of studies with data on the association of maternal body mass index (BMI, kg/m2) with offspring macrosomia or large-for-gestational age (LGA). Results: A total of 5905 titles/abstracts were screened, 775 full-texts reviewed, and 137 studies synthesized. Maternal anthropometrics were the most frequent risk marker. Meta-analysis demonstrated that women with GDM and overweight/obesity vs. GDM with normal range BMI are at higher risk of offspring macrosomia (13 studies [n = 28,763]; odds ratio [OR] 2.65; 95% Confidence Interval [CI] 1.91, 3.68), and LGA (10 studies [n = 20,070]; OR 2.23; 95% CI 2.00, 2.49). Lipids and insulin resistance/secretion indices were the most studied non-glycemic biochemical markers, with increased triglycerides and insulin resistance generally associated with greater risk of offspring macrosomia or LGA. Studies evaluating other markers had inconsistent findings as to whether they could be used as precision markers. Conclusions: Maternal overweight/obesity is associated with greater risk of offspring macrosomia or LGA in women with GDM. Pregnancy insulin resistance or hypertriglyceridemia may be useful in GDM risk stratification. Future studies examining non-glycemic biochemical, genetic, other -omic, or sociocultural precision markers among women with GDM are warranted.

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