Main Findings
Our predictive model for use around the time of delivery demonstrated good discriminatory ability (AUC 0.81; 95% CI 0.74, 0.87) and improved prediction over reported OGTT values at 4-12 weeks postpartum (AUC 0.60; 95% CI 0.53, 0.67)14, the current standard of care, to identify women at high risk for postpartum impaired glucose tolerance. Compared to reported values for a postpartum OGTT, our model also demonstrated improved sensitivity, specificity, PPV and NPV at several cut-points to identify women with impaired glucose tolerance by 1 year postpartum.14 Our results provide proof of concept that a risk score may be able to accurately identify women with recent GDM around the time of delivery who are likely to progress to impaired glucose tolerance postpartum. With less than 50% of women with recent GDM receiving any postpartum glucose testing or intervention,10,13 identifying high risk women around the time of delivery could help to target follow-up testing and intervention efforts in this high risk population.
Adults with impaired glucose metabolism are at high risk of progressing to type 2 diabetes, making them an important population for early intervention and prevention.26 To develop a clinically useful model, we prioritized potential predictors that can be readily collected in the prenatal and early postpartum period, and used a Lasso regression, which is a data-driven predictive modeling algorithm, to select covariates for inclusion in a final model. This algorithm has been used to identify clusters of clinical predictors of progression to type 2 diabetes in non-pregnant populations,27-29 but have not been employed in populations with recent GDM. Our final model included eight covariates that are known to correlate with the risk of progression to impaired glucose tolerance in women with GDM including, pre-pregnancy weight and BMI, previous GDM, early GDM diagnosis, Hispanic ethnicity, and fasting and 2-hour plasma glucose at 2 days postpartum.19,25,30-34
The predictive ability of the final model did not change meaningfully in several sensitivity analyses, including excluding plasma glucose values at 2 days postpartum, which is not currently standard of care. Model findings were also robust when evaluating the exclusion of collinear weight and BMI covariates within the model, suggesting that while these variables are closely correlated, including both in the model overall improves prediction, rather than adversely affecting the model’s performance. Model performance did not change meaningfully when Hispanic ethnicity was removed from the model or replaced with family history of type 2 diabetes.25