Abstract Gestational diabetes mellitus has long been framed, both clinically and conceptually, as a disorder of glucose dysregulation. Yet, in day-to-day perinatal practice, a persistent mismatch remains between glycemic control and pregnancy outcome. Well-controlled glucose does not reliably prevent fetal growth restriction, macrosomia, or later metabolic vulnerability, suggesting that key biological drivers lie outside glucose alone. This systematic review was undertaken to interrogate that gap. Following Preferred Reporting Items for Systematic Reviews and Meta-analyses 2020 guidance, we synthesized evidence from 37 eligible studies spanning clinical cohorts, mechanistic placental investigations, endocrine physiology, and translational models to examine how thyroid, adrenal, pancreatic, and placental axes interact in diabetic pregnancy. Rather than treating these systems in isolation, we approached pregnancy as a dynamic endocrine network, with the placenta functioning as an active integrator and stress amplifier. Across diverse study designs, convergent signals emerged: Subtle thyroid hormone shifts, altered cortisol rhythms, placental corticotropin-releasing hormone excess, dysregulated glucocorticoid metabolism, and lactogenic hormone overactivity consistently modified insulin resistance, nutrient partitioning, and fetal growth trajectories independently of measured glucose levels. These interacting pathways offer a coherent mechanistic explanation for so-called “outlier” pregnancies, in which outcomes deviate from glycemic expectations. The findings also expose limitations in current risk stratification strategies that rely almost exclusively on glucose metrics. Taken together, the evidence supports a reframing of diabetic pregnancy as a systems endocrinology disorder rather than a purely glycemic disease. Future progress will depend on longitudinal, multiaxis endocrine phenotyping, integration of placental biomarkers, and systems-biology-informed clinical trials capable of translating network-level insight into precision perinatal care.
Pasaribu et al. (2026) studied this question.