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.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Aims Dyslipidemia in pregnancy is associated with adverse pregnancy outcomes as elevated triglycerides might be considered as a risk factor for hyperglycemia and gestational diabetes. As only a few studies have addressed the association between maternal triglycerides and glucose metabolism, we aimed to explore the pathophysiologic associations of moderate hypertriglyceridemia and maternal glucose metabolism in pregnancy. Methods Sixty-seven pregnant women received a detailed metabolic characterization at 12+0–22+6 weeks of gestation by an extended 2h-75g OGTT (oral glucose tolerance test); with measurements of glucose, insulin and C-peptide at fasting and every 30 min after ingestion and assessment of triglycerides at fasting state. All examinations were repeated at 24+0–27+6 weeks of gestation. Results Elevated triglycerides in early gestation were associated with insulin resistance and β-cell dysfunction. Mean glucose concentrations during the OGTT in early pregnancy were already higher in women with hypertriglyceridemia as compared to women with triglycerides in the normal range. A higher degree of insulin resistance and increased OGTT glucose levels were also observed when metabolic assessments were repeated between 24 and 28 weeks of gestation. Of note, elevated triglycerides at early gestation were associated with development of gestational diabetes by logistic regression (odds ratio: 1.16, 95%CI: 1.03–1.34, p=0.022 for an increase of 10 mg/dl). Conclusions Hypertriglyceridemia at the start of pregnancy is closely related to impaired insulin action and β-cell function. Women with hypertriglyceridemia have higher mean glucose levels in early- and mid-gestation. Pregnant women with elevated triglycerides in early pregnancy are at increased risk of developing gestational diabetes.
Background: Several prognostic models for gestational diabetes mellitus (GDM) are provided in the literature; however, their clinical significance has not been thoroughly evaluated, especially with regard to application at early gestation and in accordance with the most recent diagnostic criteria. This external validation study aimed to assess the predictive accuracy of published risk estimation models for the later development of GDM at early pregnancy. Methods: In this cohort study, we prospectively included 1132 pregnant women.Risk evaluation was performed before 16 + 0 weeks of gestation including a routine laboratory examination. Study participants were followed-up until delivery to assess GDM status according to the IADPSG 2010 diagnostic criteria. Fifteen clinical prediction models were calculated according to the published literature. Results: Gestational diabetes mellitus was diagnosed in 239 women, that is 21.1% of the study participants. Discrimination was assessed by the area under the ROC curve and ranged between 60.7% and 76.9%, corresponding to an acceptable accuracy. With some exceptions, calibration performance was poor as most models were developed based on older diagnostic criteria with lower prevalence and therefore tended to underestimate the risk of GDM. The highest variable importance scores were observed for history of GDM and routine laboratory parameters. Conclusions: Most prediction models showed acceptable accuracy in terms of discrimination but lacked in calibration, which was strongly dependent on study settings. Simple biochemical variables such as fasting glucose, HbA1c and triglycerides can improve risk prediction. One model consisting of clinical and laboratory parameters showed satisfactory accuracy and could be used for further investigations.
Aims A family history of type 2 diabetes mellitus (T2DM) markedly increases an individual's lifetime risk of developing the disease. For gestational diabetes (GDM), this risk factor is less well characterized. This study aimed to investigate the relationship between family history of T2DM in first- and second-degree relatives in women with GDM and the differences in metabolic characteristics at early gestation. Methods This prospective cohort study included 1129 pregnant women. A broad risk evaluation was performed before 16 + 0 weeks of gestation, including a detailed family history of the different types of diabetes and a laboratory examination of glucometabolic parameters. Participants were followed up until delivery and GDM assessed according to the latest diagnosis criteria. Results We showed that pregnant women with first- (FHD1, 26.6%, OR 1.91, 95%CI 1.16 to 3.16, p = 0.005), second- (FHD2, 26.3%, OR 1.88, 95%CI 1.16 to 3.05, p = 0.005) or both first- and second-degree relatives with T2DM (FHD1 + D2, 33.3%, OR 2.64, 95%CI 1.41 to 4.94, p < 0.001) had a markedly increased risk of GDM compared to those with negative family history (FHN) (n = 100, 15.9%). The association was strongest if both parents were affected (OR 4.69, 95%CI 1.33 to 16.55, p = 0.009). Women with FHD1 and FHD1 + D2 had adverse glucometabolic profiles already in early pregnancy. Conclusions Family history of T2DM is an important risk factor for GDM, also by applying the current diagnostic criteria. Furthermore, we showed that the degree of kinship plays an essential role in quantifying the risk already at early pregnancy.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.