(1229) Cardiometabolic Health Indices as Predictors of Gestational Diabetes

The rate of gestational diabetes mellitus (GDM) diagnosis in pregnancy is rising and traditional models only quantify glucose values for diagnosis without considering insulin resistance (IR) or other markers of cardiometabolic (CM) health. Multiple markers of IR and CM health exist, including triglyceride glucose index (TyG), Homeostatic Model Assessment for Insulin Resistance (HOMA-IR), and Adipose Tissue Insulin Resistance Index (Adipo-IR), in addition to BMI, blood lipids, and lactate. As insulin resistance itself likely plays a large role in development of GDM but also pregnancy and neonatal outcomes, we sought to understand if an association exists between these markers and development of GDM in our population. 


Study Design:
This cohort was derived from two prospective cohort studies of metabolic health in pregnant individuals through 22 weeks gestation at a single regional academic medical center. Fasting venous blood draws were performed. Differences between groups (those that developed GDM and those that did not) were assessed using T-test and Mann-Whitney U, as appropriate, and binary logistic regression was used to assess which factors predicted subsequent GDM diagnosis.

Results:
A total of 52 individuals were included in our analysis, with 22 (42.3%) developing GDM during pregnancy (Table). Maternal age, BMI, TyG, lactate, insulin, triglycerides, HOMA-IR, free fatty acids, VLDL, and Adipo-IR were all significantly different between those who did and did not develop GDM.  Fasting glucose and individual lipid parameters were not significantly different between those who did and did not develop GDM. When controlling for maternal age and pre-pregnancy BMI, TyG and adipoIR both remained significant predictors of GDM (p < 0.01).

Conclusion:

Despite a relatively small sample, TyG and other CM indices were better predictors of GDM than early fasting glucose alone, even when controlling for maternal age and BMI,. Future studies with a larger sample should focus on specific metabolic indices and their thresholds for risk assessment of developing GDM.