First Trimester Prediction of Gestational Diabetes using a Predictive Model of Biochemical ParametersA Longitudinal Study

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Introduction: Current international guidelines recommend screening for Gestational Diabetes Mellitus (GDM) between 24-28 weeks of gestational age. It has been proven that early diagnosis and prompt treatment can effectively reduce and can even avoid many of the maternal and foetal complications. There are no accepted methods of testing before the recommended 24-28 weeks which can predict the development of GDM. Aim: To develop a risk based predictive model using clinical and biochemical parameters for predicting the development of GDM in the first trimester. Materials and Methods: This longitudinal prospective observational study was conducted in the Department of Obstetrics and Gyanecology at the SRM Institute of Science and Technology, Kancheepuram, Tamil Nadu, India from January 2017 to July 2018 and included 120 pregnant women with gestational age <15 weeks over a period of 18 months. Detailed history, height, weight, Body Mass Index (BMI) and blood pressure were recorded followed by measurement of serum creatinine, uric acid and albumin. At 24-28 weeks of gestation, screening for GDM was performed according to Diabetes in Pregnancy Study group of India (DIPSI) criteria. Predictive modeling using stepwise linear regression to choose the best model that can predict the development of GDM was performed. A Receiver Operating characteristic Curve (ROC) was constructed to identify the best cut-off value that can predict the development of GDM. Results: A total of 130 pregnant women who fulfilled the inclusion criteria were enrolled for the study. Ten women were lost to follow-up in 2nd trimester. Final cohort consisted of 120 women and 19 (15.8%) of them developed GDM based on DIPSI criteria between 24-28 weeks. Rest 101 (84.2%) did not develop GDM. Significant correlation was found between BMI (r=0.49, p<0.005), systolic Blood Pressure (BP) (r=0.35, p<0.005) and diastolic BP (r=0.33, p<0.005) with GDM. There was significant increase in creatinine and uric acid (p<0.005) and decrease in albumin (p<0.005) in GDM as compared to non GDM. First trimester uric acid >3.35 mg/dL showed sensitivity of 100% and specificity of 84.2% for predicting GDM. Predictive modeling showed that model containing uric acid, creatinine and albumin had a higher correlation (r=0.82) with Plasma Glucose (PG) as compared to other models containing uric acid alone or uric acid and creatinine. Conclusion: It is possible to predict the development of GDM early in the first trimester using this predictive model of biochemical parameters with high accuracy