Background: Gestational diabetes mellitus (GDM) is the most common complication during pregnancy, and it is associated with short- and long-term health impairments. Even with increasing incidence rates worldwide, to date, GDM lacks an international standard diagnosis criterion.
Objective: To elucidate whether a chronobiological perspective may improve the identification of patients at risk for neonatal complications.
Methods: We analyzed a dataset with 92 recruited pregnant patients with Continuous Glucose Monitoring (CGM) data obtained in a blinded study. The primary outcome consisted in evaluating whether the composite of adverse neonatal outcomes could be predicted by chronobiological variables derived from fitting glucose oscillation to a circadian rhythm. The secondary neonatal outcomes included preterm birth, neonatal intensive care unit admission, hypoglycemia, mechanical ventilation or continuous positive airway pressure, hyperbilirubinemia, and hospital length of stay. The secondary maternal outcomes included weight gain during pregnancy, hypertensive disorders of pregnancy, induction of labor, cesarean delivery, and postpartum complications. 87 subjects had enough data to study for glucose circadian rhythmicity.
Results: We developed a 3-covariate model including two chronobiological metrics, the midline estimating statistic of rhythm (MESOR) and glucose M10 start-time, and age that was predictive of the primary outcome, and associated with maternal secondary outcomes (preeclampsia with severe features and weight gain during pregnancy), and newborn secondary outcomes (preterm delivery < 37 weeks, indicated preterm delivery, NICU admission, need for CPAP, and differences in length of hospital stay).
Conclusions: Chronobiological parameters might contribute to a better identification of the adverse outcomes associated with GDM in both the mother and newborn.
© 2024. The Author(s), under exclusive licence to Springer Nature Limited.