First Trimester Aneuploidy Screening Markers in Women with Pre-Gestational Diabetes Mellitus

Challenges of prenatal diagnosis in obese pregnant women

Obesity rates are increasing world-wide with most of the increase in women of the reproductive age group. While recognised as an important contributor to non-communicable diseases, pregnant women with obesity are particularly at risk of not only maternal and pregnant complications but also have an increased risk of congenital malformations. Furthermore, pregnant obese women are more likely to be older and therefore at a greater risk of aneuploidy. Prenatal diagnosis in these women especially those who are morbidly obese is challenging due not only to their weight but the implications of the increase adiposity on biochemical markers of aneuploidy. In this review we discuss the current challenges in providing prenatal diagnosis for these women including those related to the ergonomics of ultrasound and those inherent in them because of their obesity. Appropriate counselling for these women should include the lower sensitivity of the tests, the difficulties in performing some of the procedures (imaging and invasive testing) as well as the increased risk of structural abnormalities related to their obesity.

Diagnostic accuracy of maternal serum multiple marker screening for early detection of gestational diabetes mellitus in the absence of a gold standard test

Background

Gestational diabetes mellitus (GDM) is associated with adverse diabetic complications for both mother and child during pregnancy. The common Gold Standard (GS) for diagnosis of GDM is 75 g oral glucose tolerance test (OGTT) during 24–28 gestational weeks which seems a little late for any proper intervention. This study aimed to employ the Bayesian latent class models (LCMs) for estimating the early diagnostic power of combination of serum multiple marker in detecting GDM during 14–17 weeks of gestation.

Methods

Data from a sample of 523 pregnant women who participated in gestational diabetes screening tests at health centers affiliated to Shahid Beheshti University of Medical Sciences in Tehran, Iran from 2017 to 2018 were used. The beta-human chorionic gonadotropin (β-hCG), unconjugated estriol (uE3), and alfa-fetoprotein (AFP) values were extracted from case records for all participants. The Bayesian LCMs were applied for estimating sensitivity, specificity, and area under receiver operating characteristic curve (AUC) of combining the three biomarkers’ results in the absence of GS, adjusting for maternal age and body mass index.

Results

The mean (standard deviation) maternal age of the participants was 28.76 (±5.33) years. Additionally, the mean (standard deviation) BMI was 24.57 (±3.22) kg/m². According to the Bayesian model, the cSensitivity, cSpecificity, and cAUC for the optimal composite diagnostic test were estimated as 94% (95% credible interval (CrI) [0.91–0.99]), 86% (95% CrI [0.80–0.92]), and 0.92 (95% CrI [0.87–0.98]), respectively.

Conclusions

Overall, the findings revealed that the combination of uE3, AFP, and β-hCG results might be considered as an acceptable predictor for detecting GDM with a rather high level of accuracy in the early second trimester of pregnancy without a GS.

Pregestational diabetes in pregnancy: Complications, management, surveillance, and mechanisms of disease-A review

Diabetes is an increasingly common diagnosis among pregnant women. Pregestational diabetes is associated with an increase in many adverse pregnancy outcomes, which impact both on the woman and her fetus. The models of pregnancy care for women with diabetes are based largely on observational data or consensus opinion. Strategies for aneuploidy screening and monitoring for fetal well-being should be modified in women with diabetes. There is an increasing understanding of the mechanisms by which congenital anomalies and disorders of fetal growth occur, involving epigenetic modifications, changes in gene expression in critical developmental pathways, and oxidative stress. This knowledge may lead to pathways for improved care for these high-risk pregnancies.

First trimester prenatal screening biomarkers and gestational diabetes mellitus: A systematic review and meta-analysis

Biomarkers commonly assessed in prenatal screening have been associated with a number of adverse perinatal and birth outcomes. However, it is not clear whether first trimester measurements of prenatal screening biomarkers are associated with subsequent risk of gestational diabetes mellitus (GDM). We aimed to systematically review and statistically summarize studies assessing the relationship between first trimester prenatal screening biomarker levels and GDM development. We comprehensively searched PubMed/MEDLINE, EMBASE, CINAHL, and Scopus (from inception through January 2018) and manually searched the reference lists of all relevant articles. We included original, published, observational studies examining the association of first trimester pregnancy associated plasma protein-A (PAPP-A) and/or free β-human chorionic gonadotropin (free β-hCG) levels with GDM diagnosis. Mean differences were calculated comparing PAPP-A and free β-hCG multiples of median (MoM) levels between women who developed GDM and those who did not and were subsequently pooled using two-sided random-effects models. Our meta-analysis of 13 studies on PAPP-A and nine studies on free β-hCG indicated that first trimester MoM levels for both biomarkers were lower in women who later developed GDM compared to women who remained normoglycemic throughout pregnancy (MD -0.17; 95% CI -0.24, -0.10; MD -0.04; 95% CI -0.07–0.01). There was no evidence for between-study heterogeneity among studies on free β-hCG (I² = 0%). A high level of between-study heterogeneity was detected among the studies reporting on PAPP-A (I² = 90%), but was reduced after stratifying by geographic location, biomarker assay method, and timing of GDM diagnosis. Our meta-analysis indicates that women who are diagnosed with GDM have lower first trimester levels of both PAPP-A and free β-hCG than women who remain normoglycemic throughout pregnancy. Further assessment of the predictive capacity of these biomarkers within large, diverse populations is needed.