Glycemic Observation Using A1C for Gestational Diabetes Diagnosis

使用 A1C 进行血糖观察以诊断妊娠期糖尿病

• 批准号: 10364803
• 负责人: John Matthew Higgins
• 金额: $ 73.05万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-15 至 2027-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10364803
• 关键词: Accounting; Adopted; Affect; Age Distribution; Birth trauma; Blood; Blood Glucose; Blood Tests; Cell Cycle Kinetics; Complete Blood Count; Complications of Diabetes Mellitus; Data; Diabetes Mellitus; Diagnosis; Diagnostic; Discipline of obstetrics; Dystocia; Erythrocytes; Fasting; Ferritin; Gestational Age; Gestational Diabetes; Glycosylated Hemoglobin; Glycosylated hemoglobin A; Goals; Hematology; Hemoglobin concentration result; Hyperglycemia; Hypertension; Individual; Investigation; Link; Maternal-fetal medicine; Measurement; Measures; Metabolic; Methods; Modeling; Modernization; Monitor; Mothers; National Institute of Diabetes and Digestive and Kidney Diseases; Neonatal Hypoglycemia; Neonatal Jaundice; OGTT; Outcome; Participant; Population; Predictive Value; Pregnancy; Pregnancy Complications; Pregnant Women; Reproducibility; Research Personnel; Reticulocyte count; Risk; Shoulder; Testing; Time; Time Study; Training; Validation; Variant; Woman; Work; adverse outcome; adverse pregnancy outcome; base; clinical practice; cohort; glucose monitor; improved; maternal hyperglycemia; modifiable risk; neonatal death; offspring; pregnancy disorder; screening; stillbirth; virtual

Abstract Pregnant women are universally screened for gestational diabetes (GDM) at 24-28 weeks gestation because of the well-established link between hyperglycemia and adverse pregnancy outcomes. In the past decade, hemoglobin A1c (A1C), which measures the percentage of glycated hemoglobin in red blood cells (RBCs), has transformed the diagnosis of diabetes outside of pregnancy. While A1C has modernized diabetes diagnosis in non-pregnant individuals, pregnant women continue to be diagnosed with GDM using cumbersome oral glucose tolerance tests (OGTTs), which require fasting and multiple timed blood draws, and have problems with intra-individual reproducibility. Despite its potential advantages, A1C has not been adopted to screen for GDM because it is affected by pregnancy-related changes in RBC kinetics, rendering simple A1C-based inferences of glycemia during gestation unreliable. We and others have demonstrated how pregnancy disrupts the strong relationship between A1C and glycemia due to pregnancy-related changes in RBC kinetics. In previous work, we have also successfully used mechanistic modeling to adjust A1Cs for non-glycemic variation outside of pregnancy. The goal of this proposal, Glycemic Observation Using A1C for Gestational Diabetes Diagnosis (GO A1C GDM), is to optimize A1C’s ability to detect hyperglycemia in pregnancy by adjusting for gestational changes in RBC kinetics that affect A1C’s relationship with glycemia. We will leverage accurate longitudinal glycemic measurements from continuous glucose monitoring (CGM) and rigorous ascertainment of hyperglycemia-associated adverse outcomes in 2150 pregnant women participating in the Glycemic Observation and Metabolic Outcomes in Mothers and Offspring study (GO MOMs) to accomplish this goal. In GO MOMs, participants will have A1Cs measured and undergo serial 10-day periods of CGM monitoring at 4 time points across pregnancy. Our proposal, GO A1C GDM, adds serial hematologic measurements (CBCs, reticulocyte counts, and ferritin) across gestation and employs mechanistic modeling to improve A1C-based glycemia estimation during pregnancy. In Aim 1, we will adjust A1C for typical gestational changes in RBC kinetics (GA-adjusted A1C). In Aim 2, we will personalize A1C adjustments, using hematologic measurements to capture gestational changes in RBC kinetics specific to individuals (CBC-adjusted A1C). In Aim 3, we will test the ability of A1Cs adjusted for RBC kinetics to predict hyperglycemia-associated adverse outcomes. We will compare this predictive ability to that of traditional OGTT-based GDM diagnosis. The proposed investigations have potential to greatly simplify the method by which we diagnose GDM, delivering advances in precision diabetes screening to the entire obstetric population.

抽象的 孕妇在24-28周的妊娠期普遍筛查妊娠糖尿病（GDM），因为 高血糖和不良妊娠结局之间建立良好的联系。在过去的十年中， 血红蛋白A1C（A1C）测量红细胞糖化血红蛋白的百分比（RBC）的百分比 改变了怀孕以外的糖尿病的诊断。而A1C在现代化的糖尿病中诊断 非怀孕的人，孕妇继续使用麻烦的口服诊断为GDM 葡萄糖耐量测试（OGTTS），需要禁食和多个定时抽血，并且有问题 具有个体内的可重复性。尽管具有潜在的优势，但尚未采用A1C进行筛选 GDM是因为它受RBC动力学与妊娠相关的变化的影响，从而使基于A1C的简单 妊娠期间血糖的推断不可靠。我们和其他人已经证明了怀孕如何破坏 由于RBC动力学与妊娠相关的变化，A1C与血糖之间的牢固关系。在 先前的工作，我们还成功地使用了机械建模来调整非血糖变化的A1C 在怀孕之外。该提案的目的是使用A1C进行妊娠糖尿病的血糖观察 诊断（GO A1C GDM）是优化A1C通过调整妊娠中检测高血糖的能力 RBC动力学的妊娠变化会影响A1C与血糖的关系。我们将利用准确的 连续葡萄糖监测（CGM）和严格确定的纵向血糖测量 2150名孕妇参加血糖的高血糖相关广告结果 在母亲和后代研究（GO MOMS）中，观察和代谢结果以实现这一目标。在 妈妈，参与者将测量A1C，并在4时进行10天的CGM监控时间 怀孕期间的时间点。我们的建议GO A1C GDM增加了串行血液学测量（CBCS， 网状细胞计数和铁蛋白）遍及妊娠和员工机械建模，以改善基于A1C的 怀孕期间的血糖估计。在AIM 1中，我们将调整A1C，以了解RBC的典型妊娠变化 动力学（Ga-phsewusted A1C）。在AIM 2中，我们将使用血液学测量来个性化A1C调整 捕获个人特定的RBC动力学的妊娠变化（CBC调整后的A1C）。在AIM 3中，我们将 测试针对RBC动力学调整的A1CS预测高血糖相关的广告结果的能力。我们 将将这种预测能力与传统的基于OGTT的GDM诊断能力进行比较。提议 调查有可能极大地简化我们诊断GDM的方法，从而实现进步 精密糖尿病对整个产科人群进行筛查。