eMOM: enhanced Monitoring to Optimize Maternal Diabetes detection

项目概要/摘要 在美国，每年有超过250，000名妇女患妊娠糖尿病（GDM）， 占怀孕总数的6.4%。目前用于诊断GDM的方法尚未进行 直到第二个三个月结束或第三个三个月早期;但是，可能存在血糖异常 导致产妇和新生儿不良结局的风险早在此之前就已存在 标准筛选。随着最新一代的动态葡萄糖监测仪（CGM）， 能够收集不需要手指针刺校准的准确数据， 舒适地佩戴足够长的时间以捕获葡萄糖动力学现在是可行的。本 一项提案旨在通过以下方式纵向评估健康、非糖尿病孕妇的血糖水平： 使用盲态CGM数据收集，从6-12周开始，间隔4周 怀孕这些数据将允许确定平均探头葡萄糖水平的差异 存在于发生GDM的女性与不使用标准口腔护理的女性之间 葡萄糖耐量试验（OGTT）筛查。此外，随着CGM数据的频率 收集，首次检测平均探头葡萄糖水平差异的最佳时间可以是 探讨了最后，将进行更严格的OGTT，以评估 作为GDM诊断基础的代谢异常，包括 是由于胰岛素抵抗或β细胞功能障碍。利用一个财团进行 目前的研究，一个大的队列是可行的，这将允许评估的因素， 导致生育障碍和GDM的风险，包括人种/种族、孕前BMI， 孕妇年龄、产次和孕期体重增加。这项研究的结果可以提供 如果盲法CGM可以代替OGTT，我们如何诊断GDM的范式转变 并了解导致GDM诊断的代谢改变。

Project Summary/Abstract Over 250,000 women develop gestational diabetes mellitus (GDM) each year in the U.S, affecting 6.4% of all pregnancies. Current methods for the diagnosis of GDM are not conducted until the end of the second or early in the third trimester; however, it is possible dysglycemia leading to both adverse maternal and neonatal outcomes are present well before this gold standard screening. With the newest generation of continuous glucose monitors (CGM), the ability to collect accurate data that does not require fingerstick calibration and can be comfortably worn long enough to capture glucose dynamics is now feasible. The present proposal seeks to longitudinally assess glycemia in healthy, non-diabetic pregnant women by using blinded CGM data collection in 4-week intervals beginning between 6-12 weeks’ gestation. These data will allow for determination if a difference in mean sensor glucose levels exists between women who develop GDM vs. those who do not using standard of care oral glucose tolerance test (OGTT) screening. Furthermore, with the frequency of CGM data collection, the optimal time to first detect the difference in mean sensor glucose levels can be explored. Finally, more rigorous OGTTs will be conducted allowing for assessment of the metabolic abnormalities that underlie the diagnosis of GDM including whether the dysglycemia is due to insulin resistance or β-cell dysfunction. With the use of a consortium to conduct the present study, a large cohort is feasible which will allow for assessment of factors that may contribute to risk of dysglycemia and GDM, including race/ethnicity, pre-pregnancy BMI, maternal age, parity and weight gain during pregnancy. The findings of this study may provide a paradigm shift in how we diagnose GDM if blinded CGM can be used in place of an OGTT and understanding of the metabolic alterations that lead to diagnosis of GDM.