Simple Model to Predict Gestational Diabetes in Nulliparous Women in Early Pregnancy

Background: The aim of this study was to develop a simple tool using anthropometric, clinical, and analytical variables to predict the risk of gestational diabetes mellitus in the first trimester of pregnancy. Methods: A historical cohort study was conducted with 1,946 Caucasian nulliparous pregnant women at the Department of Obstetrics and Gynecology of the University Hospital of Puerto Real (Cádiz/Spain). The predictive model used was a multivariate logistic regression evaluated by 10-fold cross-validation with five iterations. Receiver-operating characteristic and prediction recall curves were plotted with the predictions of the model. Optimal cut-off points of the receiver-operating characteristic curve were estimated using the Youden Index and minimum distance to point 1,1. Results: The final logistic regression model included both maternal weight and height, thyroid-stimulating hormone, family history of diabetes mellitus or hypertension, and the presence of chronic hypertension as predictive variables. The model showed an accuracy of 0.93 and a receiver-operating characteristic area under the curve of 0.791. Conclusions: This report provides a tool to predict the onset of gestational diabetes mellitus in nulliparous women during the first trimester of pregnancy. This tool is more accurate than the currently available tools and can facilitate the implementation of preventative interventions.