Early Assessment of the Risk for Gestational Diabetes Mellitus: Can Fasting Parameters of Glucose Metabolism Contribute to Risk Prediction?

Abstract

Background: An early identification of the risk groups might be beneficial in reducing morbidities in patients with gestational diabetes mellitus (GDM). Therefore, this study aimed to assess the biochemical predictors of glycemic conditions, in addition to fasting indices of glucose disposal, to predict the development of GDM in later stage and the need of glucose-lowering medication. Methods: A total of 574 pregnant females (103 with GDM and 471 with normal glucose tolerance [NGT]) were included. A metabolic characterization was performed before 15 +6 weeks of gestation by assessing fasting plasma glucose (FPG), fasting insulin (FI), fasting C-peptide (FCP), and glycosylated hemoglobin (HbA1c). Thereafter, the patients were followed-up until the delivery. Results: Females with NGT had lower levels of FPG, FI, FCP, or HbA1c at the early stage of pregnancy, and therefore, showed an improved insulin action as compared to that in females who developed GDM. Higher fasting levels of FPG and FCP were associated with a higher risk of developing GDM. Moreover, the predictive accuracy of this metabolic profiling was also good to distinguish the patients who required glucose-lowering medications. Indices of glucose disposal based on C-peptide improved the predictive accuracy compared to that based on insulin. A modified quantitative insulin sensitivity check index (QUICKIc) showed the best differentiation in terms of predicting GDM (area under the receiver operating characteristics curve [ROC-AUC], 72.1%) or need for pharmacotherapy (ROC-AUC, 83.7%). Conclusion:Fasting measurements of glucose and C-peptide as well as the surrogate indices of glycemic condition could be used for stratifying pregnant females with higher risk of GDM at the beginning of pregnancy.

Early markers of gestational diabetes mellitus

“…Li et al recently reported results of their study which included 2112 pregnant women and concluded that a fasting glucose concentration over 4.5 mmol/L during the first trimester offers optimal specificity and sensitivity for GDM prediction ( 28 ). The fasting plasma glucose concentration was more accurate than other traditional risk factors, such BMI or age, when used for GDM prediction, but it was less accurate than OGTT testing ( 25 , 26 , 29 ).…”

“…Existing international guidelines recommend testing for pregestational diabetes in women in early pregnancy with body mass index (BMI) > 30 kg/ m 2 , impaired glucose tolerance, and a history of GDM (7). (25,26,29).…”

The Clinical Characteristics of Gestational Diabetes Mellitus in Korea: A National Health Information Database Study

“…Gestational diabetes mellitus (GDM) is defined as the existence of impaired glucose metabolism in pregnancy and is associated with high adverse health risks to both the mother and child [1][2][3][4]. In the Hyperglycemia and Adverse Pregnancy Outcomes study, the risk of adverse maternal, fetal, and neonatal outcomes increased with progressive hyperglycemia, even with no clear inflection points [5].…”

Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study

“…Recent prediction models for GDM have been developed using conventional regression analyses [17][18][19]. However, machine learning, a data analysis technique that develops algorithms to predict outcomes by "learning" from data, is increasingly emphasized as a competitive alternative to regression analysis.…”