Introduction: This study aimed to identify risk factors among maternal characteristics, obstetric history, and first trimester preeclampsia-specific biomarkers that were associated with subsequent development of gestational diabetes mellitus (GDM) and evaluate the performance of the prediction models.
Methods: This study was a secondary analysis of a prospective cohort study. The performance of the prediction models was assessed by area under the receiver operating characteristic curve (AUROC).
Results: A total of 837 (8.9%) cases of GDM and 8,535 (91.1%) unaffected cases were included. The AUROC of the prediction model combining maternal characteristics and obstetric history (0.735) was better than that of the model utilizing maternal characteristics (AUROC 0.708) and preeclampsia-specific biomarkers (AUROC 0.566). Among the preeclampsia-specific biomarkers, the mean arterial pressure (MAP) contributed to the increasing risk of GDM; however, its addition did not improve the AUROC of the model combining maternal characteristics and obstetric history (0.738).
Conclusion: The first trimester prediction model for GDM with maternal characteristics and obstetric history achieves moderate predictability. The inclusion of MAP in the model combining maternal characteristics and obstetric history does not improve the screening performance for GDM. Future studies are needed to explore the effect of blood pressure control from early pregnancy on preventing GDM.
Keywords: Biomarker; First trimester; Gestational diabetes mellitus; Prediction; Screening.
© 2022 The Author(s). Published by S. Karger AG, Basel.