Gestational age and models for predicting gestational diabetes mellitus

The late pregnancy urine metabolites independently linked to GDM were markers for diminished insulin sensitivity and glucose-stimulated insulin release. The high predictive accuracy of the models in both early and late pregnancy in this cohort supports the notion that a urinary metabolite phenotype may separate GDM vs CON across both early and late gestation. A large validation study should be conducted to affirm the accuracy of this noninvasive and time-efficient technology in identifying GDM.

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Publication Details

Journal
Metabolomics
Published
2025-09-26
DOI
https://doi.org/10.1007/s11306-025-02314-3
Citations
1
Primary Topic
Gestational Diabetes Research and Management
Type
article
Field-Weighted Citation Impact
2.06
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article

Gestational age and models for predicting gestational diabetes mellitus

Jeffrey Gornbein, Aisling Murphy, Ophelia Yin, Brian J. Koos
1 citations
Metabolomics
Gestational Diabetes Research and Management
2.06
article

Gestational age and models for predicting gestational diabetes mellitus

Jeffrey Gornbein, Aisling Murphy, Ophelia Yin, Brian J. Koos
article en
1 citations

Abstract

The late pregnancy urine metabolites independently linked to GDM were markers for diminished insulin sensitivity and glucose-stimulated insulin release. The high predictive accuracy of the models in both early and late pregnancy in this cohort supports the notion that a urinary metabolite phenotype may separate GDM vs CON across both early and late gestation. A large validation study should be conducted to affirm the accuracy of this noninvasive and time-efficient technology in identifying GDM.

MetabolomicsVol. 21(5)
University of California, Los Angeles (US), University of California, San Francisco (US)
Openalex Percentile: Top 12%
Gestational Diabetes Research and Management
2.06
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