A first trimester prediction model and nomogram for gestational diabetes mellitus based on maternal clinical risk factors in a resource-poor setting.

BACKGROUND: The implementation of universal screening for Gestational Diabetes Mellitus (GDM) is challenged by several factors key amongst which is limited resources, hence the continued reliance on risk factor-based screening. Effective identification of high-risk women early in pregnancy may enable preventive intervention. This study aimed at developing a GDM prediction model based on maternal clinical risk factors that are easily assessable in the first trimester of pregnancy in a population of Nigerian women. METHODS: This was a multi-hospital prospective observational cohort study of 253 consecutively selected pregnant women from which maternal clinical data was collected at 8-12 weeks gestational age. Diagnosis of GDM was made via a one-step 75-gram Oral Glucose Tolerance Test (OGTT) at 24-28 weeks of gestation. A GDM prediction model and nomogram based on selected maternal clinical risk factors was developed using multiple logistic regression analysis, and its performance was assessed by Receiver Operator Curve (ROC) analysis. Data analysis was carried out using Statistical Package for Social Sciences (SPSS) version 25 and Python programming language (version 3.0). RESULTS: Increasing maternal age, higher body mass index (BMI), a family history of diabetes mellitus in first-degree relative and previous history of foetal macrosomia were the major predictors of GDM. The model equation was: LogitP = 6.358 - 0.066 × Age - 0.075 × First trimester BMI - 1.879 × First-degree relative with diabetes mellitus - 0.522 × History of foetal macrosomia. It had an area under the receiver operator characteristic (ROC) curve (AUC) of 0.814 (95% CI: 0.751-0.877; p-value < 0.001), and at a predicted probability threshold of 0.745, it had a sensitivity of 79.2% and specificity of 74.5%. CONCLUSION: This first trimester prediction model reliably identifies women at high risk for GDM development in the first trimester, and the nomogram enhances its practical applicability, contributing to improved clinical outcomes in the study population.

[Association between sleep status in the first trimester and preterm birth].

Objective: To investigate the relationship between sleep status in the first trimester and preterm birth. Methods: Clinical data of pregnant women who received regular prenatal examination and delivered in Peking University Third Hospital from September 1, 2019 to June 10, 2020 were collected. The Pittsburgh sleep quality index (PSQI) was used to investigate their sleep status during 8-12 weeks of gestation, and the delivery outcomes were followed up. According to the gestational age at delivery and the cause of preterm birth, they were divided into full-term delivery group (204 cases), preterm birth group (13 cases) and spontaneous preterm birth group (9 cases). The correlation between the sleep status in the first trimester and preterm birth or spontaneous preterm birth was analyzed. Results: The median PSQI score of full-term delivery group was 4.0 points (3.0, 6.0 points), which was lower than those of preterm delivery group [6.0 points (4.0, 8.0 points)] and spontaneous preterm delivery group [7.0 points (4.0, 8.0 points)], and the differences were statistically significant (all P<0.05). The proportion of pregnant women with poor sleep quality (PSQI score>7 points) in full-term delivery group [14.2% (29/204)] was lower than those in preterm delivery group (5/13) and spontaneous preterm delivery group (4/9), and the differences were statistically significant (all P<0.05). Compared with the full-term delivery group [8.0 hours (7.0, 9.0 hours)], the preterm birth group [7.0 hours (7.0, 8.0 hours)] and spontaneous preterm birth group [7.0 hours (7.0, 8.0 hours)] had significantly shorter sleep duration at night (all P<0.05). Multivariate analysis showed that PSQI score in the first trimester was an independent risk factor for preterm birth (aOR=1.22, 95%CI: 1.02-1.45; P=0.026). Pregnancy with assisted reproductive technology (aOR=5.55, 95%CI: 1.22-25.31; P=0.027), gestational diabetes mellitus (aOR=9.27, 95%CI: 1.96-43.82; P=0.005), PSQI score in the first trimester (aOR=1.27, 95%CI: 1.01-1.58; P=0.039) were independent risk factors for spontaneous preterm birth. Conclusion: Attention should be paid to the decreased sleep quality in the first trimester, which might significantly increase the risk of preterm birth and spontaneous preterm birth.

A Reanalysis of Mental Disorders Risk Following First-Trimester Abortions in Denmark.

Background: A previous Danish study of monthly and tri-monthly rates of first-time psychiatric contact following first induced abortions reported higher rates compared to first live births but similar rates compared to nine months pre-abortion. Therefore, the researchers concluded abortion has no independent effect on mental health; any differences between psychiatric contacts after abortion and delivery are entirely attributable to pre-existing mental health differences. However, these conclusions are inconsistent with similar studies that used longer time frames. Reanalysis of the published Danish data over slightly longer time frames may reconcile this discordance. Method: Monthly and tri-monthly data was extracted for reanalysis of cumulative effects over nine- and twelvemonths post-abortion. Results: Across all psychiatric diagnoses, cumulative average monthly rate of first-time psychiatric contact increased from an odds ratio of 1.12 (95% CI: 1.02 to 1.22) at 9-months to 1.49 (95% CI: 1.37 to 1.63) at 12 months post-abortion as compared to the 9 months pre-abortion rate. At 12 months post-abortion, first-time psychiatric contact was higher across all four diagnostic groupings and highest for personality or behavioral disorders (OR=1.87; 95% CI:1.48 to 2.36) and neurotic, stress related, or somatoform disorders (OR=1.60; 95% CI: 1.41 to 1.81). Conclusions: Our reanalysis revealed that the Danish data is consistent with the larger body of both record-based and survey- based studies when viewed over periods of observation of at least nine months. Longer periods of observation are necessary to capture both anniversary reactions and the exhaustion of coping mechanisms which may delay observation of post-abortion effects.

Analysis of Predictive Information From Biomarkers Added to Clinical Models of Preeclampsia: Consideration of PAPP-A2, Activin A, and sFlt-1:PlGF Ratio.

BACKGROUND: Preeclampsia remains a major cause of maternal and fetal adverse outcomes in pregnancy; however, accurate and universally acceptable predictive tools remain elusive. We investigated whether a panel of biomarkers could improve risk prediction for preeclampsia when measured at various pregnancy time points. METHODS: In this prospective cohort study, 192 women with first-trimester high-risk singleton pregnancies were consecutively recruited from tertiary obstetrics clinics in Montréal, Canada. Clinical information (height, pre-pregnancy weight, personal and family medical history, medication use) was collected at baseline. Blood pressure was measured and blood samples collected at each trimester to quantify soluble Fms-like tyrosine kinase 1 (sFlt-1), placental growth factor (PlGF), pregnancy-associated plasma protein A2 (PAPP-A2), PAPP-A, activin A, inhibin A, follistatin, and glycosylated fibronectin. A random-effects hierarchic logistic regression model was used to relate change in biomarker levels to incidence of preeclampsia. RESULTS: When added to a clinical model composed of maternal age, pre-pregnancy body mass index, race, and mean arterial pressure, a positive third-trimester result for both PAPP-A2 and activin A had a better positive predictive value than the sFlt-1:PlGF ratio added to the clinical model (91.67% [95% confidence interval (CI) 78.57%-100%] vs 66.67% [57.14%-100%]), while maintaining a comparable high negative predictive value (97.69% [95% CI 95.34%-100%] vs 96.00% [92.19%-99.21%]). CONCLUSIONS: Whereas the third-trimester sFlt-1:PlGF ratio can predict short-term absence of preeclampsia, PAPP-A2 and activin A had both high positive and negative predictive values and therefore could serve as biomarkers to predict the occurrence (and absence) of preeclampsia; these findings will be validated in future studies.

Anxiety, prenatal distress, and resilience during the first trimester of gestation.

OBJECTIVE: To describe and analyze the relationship between pregnancy-related anxiety, prenatal distress, and individual resilience in pregnant women during the first trimester of pregnancy and compare it with the obstetric variable of parity. METHOD: Quantitative, descriptive, cross-sectional study using non-probabilistic circumstantial sampling. A total of 144 women participated. The Prenatal Distress Questionnaire, the Resilience Scale, and the Pregnancy-Related Anxiety Questionnaire were used. A descriptive analysis with measures of central tendency was performed, and the reliability of the instruments was assessed. RESULTS: The average age was 33.57 years. 58.3% were multiparous and 41.7% primiparous. Anxiety was found in 21.5% and very high levels of resilience in 54.9%. Primiparous women showed higher levels of worry about the future and fear of childbirth than multiparous women. Pregnant women with high resilience showed lower levels of anxiety and stress. CONCLUSION: Pregnant women with higher levels of resilience show less anxiety and stress during the first trimester of pregnancy. Primiparous women show more anxiety and stress than multiparous women.

First-Trimester Ultrasound Screening in Routine Obstetric Practice.

Technologic advances and ultrasonographer-physician experience in fetal imaging have led to significant improvements in our ability to distinguish between normal and abnormal fetal structural development in the latter part of the first trimester. As a critical component of pregnancy care, assessment of fetal anatomy at the end of the first trimester with a standardized imaging protocol should be offered to all pregnant patients regardless of aneuploidy screening results because it has been demonstrated to identify approximately half of fetal structural malformations. Early identification of abnormalities allows focused genetic counseling, timely diagnostic testing, and subspecialist consultation. In addition, a normal ultrasound examination result offers some degree of reassurance to most patients. Use of cell-free DNA alone for aneuploidy screening while foregoing an accompanying early anatomic evaluation of the fetus will result in many anomalies that are typically detected in the first trimester not being identified until later in pregnancy, thus potentially diminishing the quality of obstetric care for pregnant individuals and possibly limiting their reproductive options, including pregnancy termination.

Prediction of severe preeclampsia and intrauterine growth restriction based on serum placental exosome miR-520a-5p levels during the first-trimester.

BACKGROUND: To assess the predictive capabilities of serum exosomal levels of micro-RNA-520a-5p (miR-520a-5p) concerning the occurrence of severe preeclampsia (sPE) and fetal growth restriction (FGR) during the first trimester of pregnancy. METHODS: During the period spanning from October 2020 to October 2021, serum samples were procured from the first trimester and subsequently preserved by freezing at -80 ℃. These samples were obtained from 105 pregnant women in a nested case-control study. This cohort consisted of individuals who later developed sPE (sPE group, n = 35) and FGR (FGR group, n = 35) during the third trimester. Additionally, 35 women with normal blood pressure were denoted as normal pregnancy group. Serum samples from the first trimester were retrieved from all groups for further analysis after thawing. Exosomes were extracted from the serum samples collected during the first trimester and examined using transmission electron microscopy, western blot, and nanoparticle tracking analysis. Additionally, the determination of their placental origin was also established during the course of the study. Exosome miR-520a-5p levels were measured using real-time quantitative polymerase chain reaction assays, primarily involving quantitative reverse transcription polymerase chain reactions. Fetal placental tissues from the 3 groups were collected shortly after birth, and miR-520a-5p expression was measured using real-time quantitative polymerase chain reaction. Serum placental exosomes and fetal placental tissues were compared for miR-520a-5p levels. Placental trophoblasts were identified as the source of serum exosomes in all 3 groups. RESULTS: It was found that serum placental exosomes exhibited lower levels of miR-520a-5p in both the sPE and FGR groups when compared to the normal pregnancy group. This finding was consistent with observations made in postpartum placental tissues. The predictive accuracy for sPE using miR-520a-5p levels in serum placental exosomes during the first trimester was notably higher (area under the receiver operating characteristic curve = 0.806, P <.05) compared to the prediction of FGR (area under the receiver operating characteristic curve = 0.628, P <.05). CONCLUSION: Placenta-derived exosomes can be extracted from maternal serum during the first trimester of pregnancy and miR-520a-5p detected from the exosomes. The downregulation of miR-520a-5p serves as a more predictive indicator for the subsequent development of sPE compared to predicting FGR.

Diagnostic utility of clinicodemographic, biochemical and metabolite variables to identify viable pregnancies in a symptomatic cohort during early gestation.

A significant number of pregnancies are lost in the first trimester and 1-2% are ectopic pregnancies (EPs). Early pregnancy loss in general can cause significant morbidity with bleeding or infection, while EPs are the leading cause of maternal mortality in the first trimester. Symptoms of pregnancy loss and EP are very similar (including pain and bleeding); however, these symptoms are also common in live normally sited pregnancies (LNSP). To date, no biomarkers have been identified to differentiate LNSP from pregnancies that will not progress beyond early gestation (non-viable or EPs), defined together as combined adverse outcomes (CAO). In this study, we present a novel machine learning pipeline to create prediction models that identify a composite biomarker to differentiate LNSP from CAO in symptomatic women. This prospective cohort study included 370 participants. A single blood sample was prospectively collected from participants on first emergency presentation prior to final clinical diagnosis of pregnancy outcome: LNSP, miscarriage, pregnancy of unknown location (PUL) or tubal EP (tEP). Miscarriage, PUL and tEP were grouped together into a CAO group. Human chorionic gonadotrophin ß (ß-hCG) and progesterone concentrations were measured in plasma. Serum samples were subjected to untargeted metabolomic profiling. The cohort was randomly split into train and validation data sets, with the train data set subjected to variable selection. Nine metabolite signals were identified as key discriminators of LNSP versus CAO. Random forest models were constructed using stable metabolite signals alone, or in combination with plasma hormone concentrations and demographic data. When comparing LNSP with CAO, a model with stable metabolite signals only demonstrated a modest predictive accuracy (0.68), which was comparable to a model of ß-hCG and progesterone (0.71). The best model for LNSP prediction comprised stable metabolite signals and hormone concentrations (accuracy = 0.79). In conclusion, serum metabolite levels and biochemical markers from a single blood sample possess modest predictive utility in differentiating LNSP from CAO pregnancies upon first presentation, which is improved by variable selection and combination using machine learning. A diagnostic test to confirm LNSP and thus exclude pregnancies affecting maternal morbidity and potentially life-threatening outcomes would be invaluable in emergency situations.

Increased risk of fetal left-right asymmetry disorders associated with maternal SARS-CoV-2 infection during the first trimester.

Our center has observed a substantial increase in the detection rate of fetal left-right(LR) asymmetry disorders between March and May 2023. This finding has raised concerns because these pregnant women experienced the peak outbreak of SARS-CoV-2 in China during their first trimester. To explore the relationship between maternal SARS-CoV-2 infection and fetal LR asymmetry disorders. A retrospective collection of clinical and ultrasound data diagnosed as fetal LR asymmetry disorders was conducted from January 2018 to December 2023. The case-control study involved fetuses with LR asymmetry disorders and normal fetuses in a 1:1 ratio. We evaluated and compared the clinical and fetal ultrasound findings in pregnant women with SARS-CoV-2 infection and pregnant women without infection. The Student t-test was utilized to compare continuous variables, while the chi-squared test was employed for univariable analyses. The incidence rate of LR asymmetry disorders from 2018 to 2023 was as follows: 0.17‰, 0.63‰, 0.61‰, 0.57‰, 0.59‰, and 3.24‰, respectively. A total of 30 fetuses with LR asymmetry disorders and 30 normal fetuses were included. This case-control study found that SARS-CoV-2 infection (96.67% vs 3.33%, P = .026) and infection during the first trimester (96.55% vs 3.45%, P = .008) were identified as risk factors. The odds ratio values were 10.545 (95% CI 1.227, 90.662) and 13.067 (95% CI 1.467, 116.419) respectively. In cases of SARS-CoV-2 infection in the first trimester, the majority of infections (88.1%, 37/42) occurred between 5 and 6 weeks of gestation. We found that 43.7% (66/151) of fetuses with LR asymmetry disorder had associated malformations, 90.9% (60/66) exhibited cardiac malformations. SARS-CoV-2 infection during the first trimester significantly increases the risk of fetal LR asymmetry disorders, particularly when the infection occurs between 5 and 6 gestation weeks. The most common associated malformation is heart malformation.

Diagnostic accuracy of ultrasound screening for fetal structural abnormalities during the first and second trimester of pregnancy in low-risk and unselected populations.

BACKGROUND: Prenatal ultrasound is widely used to screen for structural anomalies before birth. While this is traditionally done in the second trimester, there is an increasing use of first-trimester ultrasound for early detection of lethal and certain severe structural anomalies. OBJECTIVES: To evaluate the diagnostic accuracy of ultrasound in detecting fetal structural anomalies before 14 and 24 weeks' gestation in low-risk and unselected pregnant women and to compare the current two main prenatal screening approaches: a single second-trimester scan (single-stage screening) and a first- and second-trimester scan combined (two-stage screening) in terms of anomaly detection before 24 weeks' gestation. SEARCH METHODS: We searched MEDLINE, EMBASE, Science Citation Index Expanded (Web of Science), Social Sciences Citation Index (Web of Science), Arts & Humanities Citation Index and Emerging Sources Citation Index (Web of Science) from 1 January 1997 to 22 July 2022. We limited our search to studies published after 1997 and excluded animal studies, reviews and case reports. No further restrictions were applied. We also screened reference lists and citing articles of each of the included studies. SELECTION CRITERIA: Studies were eligible if they included low-risk or unselected pregnant women undergoing a first- and/or second-trimester fetal anomaly scan, conducted at 11 to 14 or 18 to 24 weeks' gestation, respectively. The reference standard was detection of anomalies at birth or postmortem. DATA COLLECTION AND ANALYSIS: Two review authors independently undertook study selection, quality assessment (QUADAS-2), data extraction and evaluation of the certainty of evidence (GRADE approach). We used univariate random-effects logistic regression models for the meta-analysis of sensitivity and specificity. MAIN RESULTS: Eighty-seven studies covering 7,057,859 fetuses (including 25,202 with structural anomalies) were included. No study was deemed low risk across all QUADAS-2 domains. Main methodological concerns included risk of bias in the reference standard domain and risk of partial verification. Applicability concerns were common in studies evaluating first-trimester scans and two-stage screening in terms of patient selection due to frequent recruitment from single tertiary centres without exclusion of referrals. We reported ultrasound accuracy for fetal structural anomalies overall, by severity, affected organ system and for 46 specific anomalies. Detection rates varied widely across categories, with the highest estimates of sensitivity for thoracic and abdominal wall anomalies and the lowest for gastrointestinal anomalies across all tests. The summary sensitivity of a first-trimester scan was 37.5% for detection of structural anomalies overall (95% confidence interval (CI) 31.1 to 44.3; low-certainty evidence) and 91.3% for lethal anomalies (95% CI 83.9 to 95.5; moderate-certainty evidence), with an overall specificity of 99.9% (95% CI 99.9 to 100; low-certainty evidence). Two-stage screening had a combined sensitivity of 83.8% (95% CI 74.7 to 90.1; low-certainty evidence), while single-stage screening had a sensitivity of 50.5% (95% CI 38.5 to 62.4; very low-certainty evidence). The specificity of two-stage screening was 99.9% (95% CI 99.7 to 100; low-certainty evidence) and for single-stage screening, it was 99.8% (95% CI 99.2 to 100; moderate-certainty evidence). Indirect comparisons suggested superiority of two-stage screening across all analyses regarding sensitivity, with no significant difference in specificity. However, the certainty of the evidence is very low due to the absence of direct comparisons. AUTHORS' CONCLUSIONS: A first-trimester scan has the potential to detect lethal and certain severe anomalies with high accuracy before 14 weeks' gestation, despite its limited overall sensitivity. Conversely, two-stage screening shows high accuracy in detecting most fetal structural anomalies before 24 weeks' gestation with high sensitivity and specificity. In a hypothetical cohort of 100,000 fetuses, the first-trimester scan is expected to correctly identify 113 out of 124 fetuses with lethal anomalies (91.3%) and 665 out of 1776 fetuses with any anomaly (37.5%). However, 79 false-positive diagnoses are anticipated among 98,224 fetuses (0.08%). Two-stage screening is expected to correctly identify 1448 out of 1776 cases of structural anomalies overall (83.8%), with 118 false positives (0.1%). In contrast, single-stage screening is expected to correctly identify 896 out of 1776 cases before 24 weeks' gestation (50.5%), with 205 false-positive diagnoses (0.2%). This represents a difference of 592 fewer correct identifications and 88 more false positives compared to two-stage screening. However, it is crucial to acknowledge the uncertainty surrounding the additional benefits of two-stage versus single-stage screening, as there are no studies directly comparing them. Moreover, the evidence supporting the accuracy of first-trimester ultrasound and two-stage screening approaches primarily originates from studies conducted in single tertiary care facilities, which restricts the generalisability of the results of this meta-analysis to the broader population.

Caesarean Section Scar and Placental Location at the First Trimester of Pregnancy-A Prospective Longitudinal Study.

Background and Objectives: This study aims to report the location of the placenta in the first trimester of pregnancy in groups of women according to the number of previous caesarean deliveries and the visibility of the caesarean scar niche. Materials and Methods: The prospective observational research included adult women aged 18 to 41 years during pregnancy after one or more previous caesarean sections (CSs). Transvaginal (TVS) and transabdominal sonography (TAS) was used to examine the uterine scar and placental location during 11-14 weeks. The CS scar niche ("defect") was bordered in the sagittal plane as a notch at the previous CS scar's site with a depth of 2.0 mm or more. A comparative analysis of the placental location (high or low and anterior or posterior) was performed between groups of women according to the CS number and the CS scar niche. Results: A total of 122 participants were enrolled during the first-trimester screening. The CS scar defect ("niche") was visible in 40.2% of cases. In cases after one previous CS, the placenta was low in the uterine cavity (anterior or posterior) at 77.4%, and after two or more CSs, it was at 67.9%. Comparing the two groups according to the CS scar niche, the placenta was low in 75.5% of cases in the participant group with a CS scar niche and in 75% of cases without a CS scar niche (p = 0.949). Conclusions: The number of previous caesarean deliveries has no effect on the incidence rate of low-lying placentas in the first trimester. Moreover, the presence of the CS scar niche is not associated with anterior low-lying placentas.

Relationship of Beta-Human Chorionic Gonadotropin to Ectopic Pregnancy Detection and Size.

Introduction: Ectopic pregnancies are a significant cause of morbidity and mortality in the first trimester of pregnancy. Hospital protocols requiring a specific beta-human chorionic gonadotropin (ß-hCG) level to qualify for diagnostic testing (pelvic ultrasound) can delay diagnosis and treatment. In this study we sought to determine the relationship between ß-hCG level and the size of ectopic pregnancy with associated outcomes. Methods: We performed a retrospective case review of patients diagnosed with ectopic pregnancy in an urban, academic emergency department specializing in obstetrical care, from January 1, 2015-December 31, 2017. Variables extracted included presentation, treatment, adverse outcomes, and rates of rupture. Results: We identified 519 unique ectopic pregnancies. Of those ectopic pregnancies, 22.9% presented with evidence of rupture on ultrasound, and 14.4% showed evidence of hemodynamic instability (pulse >100 beats per minute; systolic blood pressure <90 millimeters of mercury; or evidence of significant blood loss) on presentation. Medical management outcomes were as follows: of 177 patients who received single-dose methotrexate, 14.7% failed medical management and required surgical intervention; of 46 who received multi-dose methotrexate, 36.9% failed medical management and required surgical intervention. Ultimately, 55.7% of patients required operative management of their ectopic pregnancy. Mean ß-hCG level at initial presentation was 7,096 milli-international units per milliliter (mIU/mL) (SD 88,872 mIU/mL) with a median of 1,289 mIU/mL; 50.4% of ectopic pregnancies presented with ß-hCG levels less than the standard discriminatory zone of 1,500 mIU/mL. Additionally, 44% of the patients who presented with evidence of rupture had ß-hCG levels less than 1,500 mIU/mL. Comparison of size of ectopic pregnancy (based on maximum dimension in millimeters) to ß-hCG levels revealed a very weak correlation (r = 0.144, P < .001), and detection of ectopic pregnancies by ultrasound was independent of ß-hCG levels. Conclusion: Levels of ß-hCG do not correlate with the presence or size of an ectopic pregnancy, indicating need for diagnostic imaging regardless of ß-hCG level in patients with clinical suspicion for ectopic pregnancy. Almost one-sixth of patients presented with evidence of hemodynamic instability, and approximately one quarter of patients presented with evidence of rupture requiring emergent operative management. Ultimately, more than half of patients required an operative procedure to definitively manage their ectopic pregnancy.

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.

Longitudinal hematological change in uncomplicated twin pregnancies: The white blood cell count decreases through pregnancy after the first trimester.

OBJECTIVE: Longitudinal hematological changes throughout twin pregnancies have not been reported. This study aimed to reveal longitudinal changes in hematological indices in twin pregnancies. MATERIALS AND METHODS: We conducted a retrospective chart review of hematological changes in uncomplicated twin pregnancies delivered at ≥37 weeks of gestation between 2010 and 2013 and randomly selected uncomplicated singletons during the same period. A complete blood count and hemogram were performed as blood examinations in the first trimester (9-13 weeks), late second trimester (22-27 weeks), mid-third trimester (33-35 weeks, only in twin pregnancies), and late third trimester (36-38 weeks). We evaluated inter-trimester differences in hematological indices and compared the values between twin and singleton pregnancies in each trimester. RESULTS: The final analysis group included 60 twin pregnancies and 63 singleton pregnancies. The white blood cell (WBC) count in twin pregnancies decreased throughout the pregnancy after the first trimester and became significantly lower than that in singletons in the late third trimester. The WBC count showed only a slight decrease in the third trimester in singleton pregnancies, whereas it showed a marked decrease throughout the pregnancy in twin pregnancies. The marked decrease in the total WBC count in twin pregnancies is mainly due to a decrease in neutrophils. The red blood cell count and hemoglobin and hematocrit values in twin pregnancies showed more marked decreases in the second trimester than in singletons. No decrease was observed after the second trimester of pregnancy. The platelet count decreased in the third trimester of twin pregnancies. CONCLUSION: We clarified the longitudinal hematological changes in twin pregnancies that showed augmentation of or differed from those of singleton pregnancies. It should be specifically mentioned that the WBC count markedly decreased through pregnancy after the first trimester, which is a characteristic change in twin pregnancies.

Early prediction of gestational diabetes mellitus using maternal demographic and clinical risk factors.

OBJECTIVE: To build and validate an early risk prediction model for gestational diabetes mellitus (GDM) based on first-trimester electronic medical records including maternal demographic and clinical risk factors. METHODS: To develop and validate a GDM prediction model, two datasets were used in this retrospective study. One included data of 14,015 pregnant women from Máxima Medical Center (MMC) in the Netherlands. The other was from an open-source database nuMoM2b including data of 10,038 nulliparous pregnant women, collected in the USA. Widely used maternal demographic and clinical risk factors were considered for modeling. A GDM prediction model based on elastic net logistic regression was trained from a subset of the MMC data. Internal validation was performed on the remaining MMC data to evaluate the model performance. For external validation, the prediction model was tested on an external test set from the nuMoM2b dataset. RESULTS: An area under the receiver-operating-characteristic curve (AUC) of 0.81 was achieved for early prediction of GDM on the MMC test data, comparable to the performance reported in previous studies. While the performance markedly decreased to an AUC of 0.69 when testing the MMC-based model on the external nuMoM2b test data, close to the performance trained and tested on the nuMoM2b dataset only (AUC = 0.70).

First-trimester fetal size, accelerated growth in utero, and child neurodevelopment in a cohort study.

BACKGROUND: Early pregnancy is a critical window for neural system programming; however, the association of first-trimester fetal size with children's neurodevelopment remains to be assessed. This study aimed to explore the association between first-trimester fetal size and children's neurodevelopment and to examine whether intrauterine accelerated growth could compensate for the detrimental effects of first-trimester restricted growth on childhood neurodevelopment. METHODS: The participants were from a birth cohort enrolled from March 2014 to March 2019 in Wuhan, China. A total of 2058 fetuses with crown to rump length (CRL) (a proxy of first-trimester fetal size) measurements in the first trimester and neurodevelopmental assessment at age 2 years were included. We measured the first-trimester CRL and defined three fetal growth patterns based on the growth rate of estimated fetal weight from mid to late pregnancy. The neurodevelopment was assessed using the Bayley Scales of Infant Development of China Revision at 2 years. RESULTS: Each unit (a Z score) increase of first-trimester CRL was associated with increased scores in mental developmental index (MDI) (adjusted beta estimate = 1.19, (95% CI: 0.42, 1.95), P = 0.03) and psychomotor developmental index (PDI) (adjusted beta estimate = 1.36, (95% CI: 0.46, 2.26), P < 0.01) at age 2 years, respectively. No significant association was observed between fetal growth rate and PDI. For children with restricted first-trimester fetal size (the lowest tertile of first-trimester CRL), those with "intrauterine accelerated growth" pattern (higher growth rates) had significantly higher MDI (adjusted beta estimate = 6.14, (95% CI: 3.80, 8.49), P < 0.001) but indistinguishable PDI compared to those with "intrauterine faltering growth" pattern (lower growth rates). Main limitations of this study included potential misclassification of gestational age due to recall bias of the last menstrual period and residual confounding. CONCLUSIONS: The current study suggests that restricted first-trimester fetal size is associated with mental and psychomotor developmental delay in childhood. However, in children with restricted first-trimester fetal size, intrauterine accelerated growth was associated with improved mental development but had little effect on psychomotor development. Additional studies are needed to validate the results in diverse populations.

Trends in Reporting of Nuchal Translucency Measurements After the Clinical Introduction of Cell-Free DNA Screening.

Nuchal translucency (NT) measurement in conjunction with serum analytes has been used for first-trimester aneuploidy screening in the United States since 2005. We sought to analyze the trends in reporting of NT measurements to the Nuchal Translucency Quality Review program in all pregnancies beginning after the clinical introduction of cell-free DNA (cfDNA) screening for fetal aneuploidy in 2011. Overall, reported NT measurements decreased 74.3% from 2012 to 2022. A similar decline was noted among individuals with pregnancies at increased risk for aneuploidy based on patient age and twin gestations. The decrease in reporting aligns temporally with the availability of cfDNA screening and the coronavirus disease 2019 (COVID-19) pandemic.

Spatiotemporal expression of thyroid hormone transporter MCT8 and THRA mRNA in human cerebral organoids recapitulating first trimester cortex development.

Thyroid hormones (TH) play critical roles during nervous system development and patients carrying coding variants of MCT8 (monocarboxylate transporter 8) or THRA (thyroid hormone receptor alpha) present a spectrum of neurological phenotypes resulting from perturbed local TH action during early brain development. Recently, human cerebral organoids (hCOs) emerged as powerful in vitro tools for disease modelling recapitulating key aspects of early human cortex development. To begin exploring prospects of this model for thyroid research, we performed a detailed characterization of the spatiotemporal expression of MCT8 and THRA in developing hCOs. Immunostaining showed MCT8 membrane expression in neuronal progenitor cell types including early neuroepithelial cells, radial glia cells (RGCs), intermediate progenitors and outer RGCs. In addition, we detected robust MCT8 protein expression in deep layer and upper layer neurons. Spatiotemporal SLC16A2 mRNA expression, detected by fluorescent in situ hybridization (FISH), was highly concordant with MCT8 protein expression across cortical cell layers. FISH detected THRA mRNA expression already in neuroepithelium before the onset of neurogenesis. THRA mRNA expression remained low in the ventricular zone, increased in the subventricular zone whereas strong THRA expression was observed in excitatory neurons. In combination with a robust up-regulation of known T3 response genes following T3 treatment, these observations show that hCOs provide a promising and experimentally tractable model to probe local TH action during human cortical neurogenesis and eventually to model the consequences of impaired TH function for early cortex development.

Deep-learning computer vision can identify increased nuchal translucency in the first trimester of pregnancy.

OBJECTIVE: Many fetal anomalies can already be diagnosed by ultrasound in the first trimester of pregnancy. Unfortunately, in clinical practice, detection rates for anomalies in early pregnancy remain low. Our aim was to use an automated image segmentation algorithm to detect one of the most common fetal anomalies: a thickened nuchal translucency (NT), which is a marker for genetic and structural anomalies. METHODS: Standardized mid-sagittal ultrasound images of the fetal head and chest were collected for 560 fetuses between 11 and 13 weeks and 6 days of gestation, 88 (15.7%) of whom had an NT thicker than 3.5 mm. Image quality was graded as high or low by two fetal medicine experts. Images were divided into a training-set (n = 451, 55 thick NT) and a test-set (n = 109, 33 thick NT). We then trained a U-Net convolutional neural network to segment the fetus and the NT region and computed the NT:fetus ratio of these regions. The ability of this ratio to separate thick (anomalous) NT regions from healthy, typical NT regions was first evaluated in ground-truth segmentation to validate the metric and then with predicted segmentation to validate our algorithm, both using the area under the receiver operator curve (AUROC). RESULTS: The ground-truth NT:fetus ratio detected thick NTs with 0.97 AUROC in both the training and test sets. The fetus and NT regions were detected with a Dice score of 0.94 in the test set. The NT:fetus ratio based on model segmentation detected thick NTs with an AUROC of 0.96 relative to clinician labels. At a 91% specificity, 94% of thick NT cases were detected (sensitivity) in the test set. The detection rate was statistically higher (p = 0.003) in high versus low-quality images (AUROC 0.98 vs. 0.90, respectively). CONCLUSION: Our model provides an explainable deep-learning method for detecting increased NT. This technique can be used to screen for other fetal anomalies in the first trimester of pregnancy.