The prevalence of gestational diabetes mellitus (GDM) has increased substantially over the past two decades. This increased prevalence is of concern given the association of GDM with adverse pregnancy outcomes as well as longer-term adverse outcomes for both women and their children. Identification and treatment of GDM are clinically important, as treatment can lessen the frequency of at least some ? but not all ? adverse outcomes. One potential explanation for the inconsistent relationship of GDM treatment to the reduction of adverse maternal, neonatal, and childhood outcomes is that GDM diagnosis and treatment typically occur in the third trimester, which may be too late to ameliorate all of the adverse effects associated with maternal dysglycemia. However, efforts to identify clinically relevant maternal dysglycemia earlier in gestation, such as the first trimester, or to predict who will subsequently develop GDM, have not been successful. One reason for this lack of success is that the evaluation of glucose levels during pregnancy has primarily involved singular measures of fasting glucose or only a few glucose levels following a glucose load. Such measures may provide limited insight into a maternal glycemic state that is in flux both in the short and long term. Continuous glucose monitoring (CGM) provides an opportunity to evaluate glucose profiles and gain information related to how these profiles change longitudinally over hours, days, weeks, and months. In this proposal, we will address the hypothesis that maternal glucose signatures, starting early in pregnancy, will predict the subsequent diagnosis of GDM and be better associated with maternal and newborn outcomes than the third-trimester diagnosis of GDM. To address this hypothesis, we will use data from CGM to examine glycemic patterns during pregnancy, and analyze these patterns to determine how strongly they are associated with the subsequent development of GDM as well as adverse maternal and neonatal outcomes. The proposed study will define the evolution of glucose levels during pregnancy in women without diabetes mellitus, and define patterns of glycemia in early pregnancy that identify women who will progress to GDM and/or who will be more likely to have maternal and neonatal adverse outcomes. These data are crucial to help determine future clinical trials and interventions to reduce short- and long-term adverse pregnancy outcomes.
The prevalence of gestational diabetes mellitus (GDM) has increased substantially, and it is associated with both short- and long-term adverse outcomes for both women and their children. The strategies used for GDM rely on diagnosis and treatment in the third trimester, but these have not consistently reduced or eliminated the adverse outcomes that occur. Therefore, there is a vital need to develop novel strategies, including earlier diagnosis and better ascertainment of blood sugar profiles, that predict adverse outcomes related to dysglycemia, which will result in better treatment approaches and outcomes.
