Gestational diabetes & diabetes in pregnancy
Development and validation of a multivariable genotype-informed gestational diabetes prediction algorithm for clinical use in the Mexican population: insights into susceptibility mechanisms
Authors' conclusion
We developed a predictive model using both genetic and clinical factors to identify Mexican women at risk of developing GDM. These findings may contribute to a greater understanding of metabolic functions that underlie elevated GDM risk and support personalized patient recommendations.
Study context
- Population
- Pregnant Mexican women; Gestational diabetes mellitus (GDM) diagnosed by 2-hour 75 g oral glucose tolerance test (OGTT) at 24–28 gestational weeks
- Outcome
- Discrimination of GDM prediction model combining SNPs and clinical variables
Methodological detailsgenotype-informed, external validation, 10-fold cross-validation, 114 single-nucleotide polymorphisms (SNPs) with reported predictive power evaluated, Cuido mi Embarazo (CME) cohort split 70% training, 30% testing
- Genotype-informed
- External validation
- 10-fold cross-validation
- 114 SNPs with reported predictive power evaluated
- CME cohort split 70% training, 30% testing
Performance
As reported in the abstract
GDM prediction model (11 SNPs + 4 clinical variables) performance
| Test or model | AUC (further validation) |
|---|---|
| HMPMPS | 0.8001 |
HMPMPS
AUC (further validation)0.8001
- AUC of training dataset on further validation
- 0.8256
Further findings
| Outcome | CME | HMPMPS |
|---|---|---|
| Further validation AUC | ||
| AUC (training dataset) | 0.8256 | — not stated in the abstract |
| AUC | — not stated in the abstract | 0.8001 |
— not stated in the abstract
Parts of this Brief are withheld: the automatic checks could not confirm them against the abstract.
Original publication
Development and validation of a multivariable genotype-informed gestational diabetes prediction algorithm for clinical use in the Mexican population: insights into susceptibility mechanisms. BMJ Open Diabetes Res Care. Published 21 April 2023. doi:10.
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