Maternal serum screening marker levels in twin pregnancies affected by gestational diabetes

Vaccination in twin pregnancies: comparison between immunization before conception and during pregnancy

To evaluate the development of neutralizing Anti-Spike Protein IgG (Anti-S-IgG) during twin pregnancies before conception vs. during pregnancy. In this prospective study, three blood samples were collected from pregnant women and subjected to anti-S-IgG immunodiagnostics. The patient's medical records, including vaccination and PCR test results, were collected from the hospital's electronic database. Age-matched non-pregnant women were used as a control group. We enrolled 83 women with twin pregnancies. 49 women were vaccinated before conception, 21 women were vaccinated during pregnancy, and 13 were not vaccinated. Of the 13 women who weren't vaccinated, three became positive during pregnancy, and all three were severely ill. By contrast, in women who were vaccinated during or before pregnancy, COVID-19 infection during pregnancy caused only mild symptoms. A ten-fold lower level of neutralizing Anti-S-IgG in the 3rd trimester was observed in healthy women who were vaccinated before conception and remained healthy until discharge from the hospital after delivery 1605 (IQR: 763-2410) compared to the healthy women who were vaccinated during pregnancy 152 AU/mL (IQR: 54-360). This difference was higher among women who were infected by COVID-19 (as verified by a positive PCR test). The third-trimester level of neutralizing Ant-S-IgG in the infected group was 4770 AU/mL (4760-6100) in infected women vaccinated before conception compared to those vaccinated during pregnancy who had 70 AU/mL (IQR: 20-170) (p < 0.001). In women vaccinated at 13-16 weeks gestation, neutralizing Anti-S-IgG at 20-22 weeks went up to 372 AU/mL (IQR: 120-1598) but rapidly dropped to 112 AU/mL (IQR: 54-357) at 28-30 weeks, (p < 0.001), a faster decline than in women vaccinated at a median 22 weeks before conception. Being infected by COVID-19 before conception was linked to having low Anti-S-IgG levels during pregnancy, whereas being infected by COVID-19 during pregnancy led to a very high response in the 3rd trimester. In twin pregnancies, significantly lower neutralizing Anti-S-IgG levels were observed in women vaccinated during pregnancy compared to those vaccinated before conception, whether infected or not infected by COVID-19. A full course of vaccination before conception is recommended.Trial registration. ClinicalTrials.gov Protocol Registration and Results System (PRS) Receipt Release Date: October 4, 2021. https://clinicaltrials.gov/ ID: NCT04595214.

Ultrasonographic placental parameters at 11-13+6 weeks' gestation in the prediction of complications in pregnancy after assisted reproductive technology

OBJECTIVE

To evaluate the performance of maternal factors, biophysical and biochemical markers at 11-13 + 6 weeks' gestation in the prediction of gestational diabetes mellitus with or without large for gestational age (GDM ± LGA) fetus and great obstetrical syndromes (GOS) among singleton pregnancy following in-vitro fertilisation (IVF)/embryo transfer (ET).

MATERIALS AND METHODS

A prospective cohort study was conducted between December 2017 and January 2020 including patients who underwent IVF/ET. Maternal mean arterial pressure (MAP), ultrasound markers including placental volume, vascularisation index (VI), flow index (FI) and vascularisation flow index (VFI), mean uterine artery pulsatility index (mUtPI) and biochemical markers including placental growth factor (PlGF) and soluble fms-like tyrosine kinase-1 (sFlt-1) were measured at 11-13 + 6 weeks' gestation. Logistic regression analysis was performed to determine the significant predictors of complications.

RESULTS

Among 123 included pregnancies, 38 (30.9%) had GDM ± LGA fetus and 28 (22.8%) had GOS. The median maternal height and body mass index were significantly higher in women with GDM ± LGA fetus. Multivariate logistic regression analysis demonstrated that in the prediction of GDM ± LGA fetus and GOS, there were significant independent contributions from FI MoM (area under curve (AUROC) of 0.610, 95% CI 0.492-0.727; p = 0.062) and MAP MoM (AUROC of 0.645, 95% CI 0.510-0.779; p = 0.026), respectively.

CONCLUSION

FI and MAP are independent predictors for GDM ± LGA fetus and GOS, respectively. However, they have low predictive value. There is a need to identify more specific novel biomarkers in differentiating IVF/ET pregnancies that are at a higher risk of developing complications.

Early Identification of the Maternal, Placental and Fetal Dialog in Gestational Diabetes and Its Prevention

Gestational diabetes mellitus (GDM) complicates between 5 and 12% of pregnancies, with associated maternal, fetal, and neonatal complications. The ideal screening and diagnostic criteria to diagnose and treat GDM have not been established and, currently, diagnostic use with an oral glucose tolerance test occurs late in pregnancy and produces poor reproducibility. Therefore, in recent years, significant research has been undertaken to identify a first-trimester biomarker that can predict GDM later in pregnancy, enable early intervention, and reduce GDM-related adverse pregnancy outcomes. Possible biomarkers include glycemic markers (fasting glucose and hemoglobin A1c), adipocyte-derived markers (adiponectin and leptin), pregnancy-related markers (pregnancy-associated plasma protein-A and the placental growth factor), inflammatory markers (C-reactive protein and tumor necrosis factor-α), insulin resistance markers (sex hormone-binding globulin), and others. This review summarizes current data on first-trimester biomarkers, the advantages, and the limitations. Large multi-ethnic clinical trials and cost-effectiveness analyses are needed not only to build effective prediction models but also to validate their clinical use.

Imaging findings in association with altered maternal alpha-fetoprotein levels during pregnancy

Maternal serum alpha-fetoprotein is a valuable laboratory test used in pregnant women as an indicator to detect certain clinical abnormalities. These can be grouped into four main categories: fetal factors, pregnancy complications, placental abnormalities, and maternal factors. Imaging is an invaluable tool to investigate the various etiologies leading to altered maternal serum alpha-fetoprotein. By reading this article, the radiologist, sonologist, or other health care practitioner should be able to define the probable pathology leading to the laboratory detected abnormal maternal serum levels, thus helping the clinician to appropriately manage the pregnancy and counsel the patient.

First trimester biomarkers for prediction of gestational diabetes mellitus

PURPOSE

To develop a first trimester prediction model for gestational diabetes mellitus (GDM) using obesity, placental, and inflammatory biomarkers.

METHODS

We used a first trimester dataset of the ASPRE study to evaluate clinical and biochemical biomarkers. All biomarkers levels (except insulin) were transformed to gestational week-specific medians (MoMs), adjusted for maternal body mass index (BMI), maternal age, and parity. The MoM values of each biomarker in the GDM and normal groups were compared and used for the development of a prediction model assessed by area under the curve (AUC).

RESULTS

The study included 185 normal and 20 GDM cases. In the GDM group, compared to the normal group BMI and insulin (P = 0.003) were higher (both P < 0.003). The MoM values of uterine artery pulsatility index (UtA-PI) and soluble (s)CD163 were higher (both P < 0.01) while pregnancy associated plasma protein A (PAPP-A), placental protein 13 (PP13), and tumor-necrosis factor alpha (TNFα) were lower (all P < 0.005). There was no significant difference between the groups in placental growth factor, interleukin 6, leptin, peptide YY, or soluble mannose receptor (sMR/CD206). In screening for GDM in obese women the combination of high BMI, insulin, sCD163, and TNFα yielded an AUC of 0.95, with detection rate of 89% at 10% false positive rate (FPR). In non-obese women, the combination of sCD163, TNFα, PP13 and PAPP-A yielded an AUC of 0.94 with detection rate of 83% at 10% FPR.

CONCLUSION

A new model for first trimester prediction of the risk to develop GDM was developed that warrants further validation.

New predictors of early impaired placentation preceding miscarriage before 10 weeks of gestation in IVF pregnancies: A prospective study

INTRODUCTION

In a recent study of 10,011 pregnant women, 95% of miscarriages occurred before routine ultrasound scan at 11-14 weeks. Our study aimed to identify early first trimester parameters which may predict miscarriage before 10 weeks of gestation for in vitro fertilization (IVF) pregnancies.

METHODS

A cohort of 115 healthy IVF patients with a singleton viable embryo in early first trimester were studied in a tertiary university-affiliated medical center (April 2017-June 2018). Calculations included gestational age (GA); ultrasound evaluation of crown-rump length (CRL), mean gestational sac diameter (GSD) and volume (GSV), mean yolk sac diameter (YSD) and volume (YSV); fetal heart rate (FHR), mean uterine arteries pulsatility index (UtA-PI); and maternal blood placental protein 13 (PP13) levels. Patients were divided into three groups by GA; and early miscarriage versus ongoing pregnancy after GA 10 weeks.

RESULTS

Early fetal loss occurred in 14.8% of patients; miscarriage group had higher discrepancy between calculated and measured GA (P < 0.001), lower GSD and GSV (P = 0.005 and P = 0.02, respectively), significantly different YSD and YSV, and lower GSD/YSD and GSV/YSV ratios (P = 0.001 and P = 0.003, respectively). UtA-PI/CRL ratio was higher in patients with miscarriage at GA 46-48 days and GA >48 days (P = 0.034 and P = 0.026, respectively). PP13/CRL ratio was higher in patients with miscarriage at GA >48 days (P = 0.041).

DISCUSSION

In IVF pregnancies with live embryo at first ultrasound scan, high UtA-PI/CRL and maternal blood PP13/CRL ratios may indicate impaired placentation preceded early pregnancy loss. A larger cohort is needed to further verify these predictions.