The function of oral glucose tolerance test protocols in diagnosing and managing gestational diabetes: can insulin requirements be predicted?

Aims: This study aims to evaluate the effectiveness of diagnostic tests, clinical, and laboratory markers in predicting insulin requirements in pregnant women diagnosed with gestational diabetes mellitus (GDM). Additionally, we assessed differences in maternal and neonatal outcomes between insulin-managed and diet-managed GDM patients. Methods: A retrospective analysis was conducted on 406 pregnant women diagnosed with GDM at Ankara Etlik City Hospital between October 2022 and December 2024. Patients were categorized based on the diagnostic method used: the one-step 75 g oral glucose tolerance test (OGTT) or the two-step 100 g OGTT following a 50 g OGTT. Clinical, laboratory, and demographic data were compared between insulin-treated and diet-controlled groups. The predictive capacity of fasting plasma glucose (FPG), glucose levels at 1st, 2nd, and 3rd hours during OGTT, and HbA1c for insulin requirement were assessed using receiver operating characteristic (ROC) analysis. Results: In the 75 g OGTT group, fasting, 1st-hour, and 2nd-hour glucose levels were significantly higher in the insulin-requiring group (p92 mg/dl and 2nd hour glucose >160 mg/dl were predictive of insulin requirement. HbA1c >5.25% was also a significant predictor (p=0.009). However, in the 100 g OGTT group, only the 2nd hour glucose level (>169 mg/dl, p=0.032) was predictive of insulin need, while HbA1c was not statistically significant. Birth outcomes showed that insulin-treated patients had an earlier gestational age at delivery (p=0.001), but neonatal outcomes were not significantly different between insulin-treated and diet-managed groups. Conclusion: The findings suggest that glucose levels and HbA1c in the 75 g OGTT group are more effective in predicting insulin requirements in GDM patients than the 100 g OGTT. The study underscores the importance of identifying predictive markers for early intervention, potentially guiding clinicians in selecting optimal diagnostic methods and improving patient outcomes.