Abstract 30: Assessing subcutaneous, visceral and liver fat using first trimester antenatal ultrasound and creating a predictive model for gestational diabetes

Objective: Gestational Diabetes mellitus (GDM) is diagnosed in the second or third trimester of pregnancy that was not clearly present prior to gestation. It is associated with increased maternal and foetal morbidity including increased risks of preeclampsia, large for gestational age newborns, and cesarean birth. Predicting the risk of GDM early in the first trimester will help in appropriate nutritional and life style changes in the mother. Various prediction models using maternal age, family history of DM, BMI, and material glucose and triglycerides have been studied. Using the first trimester Antenatal Ultrasound (AUS) to get data on liver fat, subcutaneous fat thickness (SFT) and visceral fat thickness (VFT), we attempt to build a predictive model for the subsequent risk of GDM. Methods: After Institutional Ethics committee approval, we conducted a prospective cohort study of all pregnant women who came for Antenatal visit in their first trimester at our institute between Jan 2019 to Oct 2020. A detailed history, anthropometric measurements including BMI, neck circumference, waist: hip ratio were noted. Blood was sent for random blood sugar (RBS) and/or HbA1c. Patients with pre-existing Diabetes, IVF pregnancies and those with liver disease or currently on hepatotoxic drugs were excluded. At 11-13 weeks SFT, VFT and liver fat was estimated using AUS. 75 gm OGTT was done after 24 weeks of gestation and IADPSG criteria were utilized for diagnosis of GDM. The data was divided into two groups based on the development of GDM in the second trimester and analyzed. Risk factors for GDM were tested using univariate analysis. Area under the ROC was constructed to study the accuracy of different variables for predicting GDM. Regression analysis using forward conditional method was used to develop risk prediction model. Goodness of fit of the model was assessed by Homer Lemeshow test. All statistical tests were done using SPSS software v21. Results: A total of 265 singleton pregnancies were included in our study. The prevalence of GDM was found to be 22% (n = 59). Family history of DM (OR 2.3), history of PCOS (OR 3.5) and presence of Fatty Liver (OR 12.5) was associated with development of GDM (p value <0.01). The area under the curve (in parenthesis) for predicting GDM for BMI > 24.5 kg/m2 (0.82), WHR > 0.88 (0.67), Neck circumference > 32.5 cm (0.74), RBS > 110 (0.85), SFT > 2.5 (0.81), VFT > 4.75 (0.93), Fatty liver (0.6). A model including RBS, VFT and Liver fat gave the best prediction of GDM with an accuracy of 94%. Conclusion: First trimester AUS is an economical and effective tool in combination with a random glucose to predict GDM.