> Details
Francis, Ellen C.;
Powe, Camille E.;
Lowe, William L.;
White, Sara L.;
Scholtens, Denise M.;
Yang, Jiaxi;
Zhu, Yeyi;
Zhang, Cuilin;
Hivert, Marie-France;
Kwak, Soo Heon;
Sweeting, Arianne;
Tobias, Deirdre K.;
Merino, Jordi;
Ahmad, Abrar;
Aiken, Catherine;
Benham, Jamie L.;
Bodhini, Dhanasekaran;
Clark, Amy L.;
Colclough, Kevin;
Corcoy, Rosa;
Cromer, Sara J.;
Duan, Daisy;
Felton, Jamie L.;
Gillard, Pieter;
[...]
Refining the diagnosis of gestational diabetes mellitus: a systematic review and meta-analysis
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- Media type: E-Article
- Title: Refining the diagnosis of gestational diabetes mellitus: a systematic review and meta-analysis
- Contributor: Francis, Ellen C.; Powe, Camille E.; Lowe, William L.; White, Sara L.; Scholtens, Denise M.; Yang, Jiaxi; Zhu, Yeyi; Zhang, Cuilin; Hivert, Marie-France; Kwak, Soo Heon; Sweeting, Arianne; Tobias, Deirdre K.; Merino, Jordi; Ahmad, Abrar; Aiken, Catherine; Benham, Jamie L.; Bodhini, Dhanasekaran; Clark, Amy L.; Colclough, Kevin; Corcoy, Rosa; Cromer, Sara J.; Duan, Daisy; Felton, Jamie L.; Gillard, Pieter; [...]
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imprint:
Springer Science and Business Media LLC, 2023
- Published in: Communications Medicine
- Language: English
- DOI: 10.1038/s43856-023-00393-8
- ISSN: 2730-664X
- Origination:
- Footnote:
- Description: <jats:title>Abstract</jats:title><jats:sec> <jats:title>Background</jats:title> <jats:p>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.</jats:p> </jats:sec><jats:sec> <jats:title>Methods</jats:title> <jats:p>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/m<jats:sup>2</jats:sup>) with offspring macrosomia or large-for-gestational age (LGA).</jats:p> </jats:sec><jats:sec> <jats:title>Results</jats:title> <jats:p>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 [<jats:italic>n</jats:italic> = 28,763]; odds ratio [OR] 2.65; 95% Confidence Interval [CI] 1.91, 3.68), and LGA (10 studies [<jats:italic>n</jats:italic> = 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.</jats:p> </jats:sec><jats:sec> <jats:title>Conclusions</jats:title> <jats:p>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.</jats:p> </jats:sec>
- Access State: Open Access