Screening for pre-eclampsia by maternal factors and biomarkers at 11-13 weeks' gestation

Low-Dose Aspirin after ASPRE-More Questions Than Answers? Current International Approach after PE Screening in the First Trimester

Preeclampsia (PE) is a multi-factorial disorder of pregnancy, and it continues to be one of the leading causes of fetal and maternal morbidity and mortality worldwide. Aspirin is universally recommended for high-risk women to reduce preeclampsia risk. The purpose of this review is to summarize the recommendations of various scientific societies on predicting preeclampsia and their indications for the inclusion of acetylsalicylic acid (ASA) prophylaxis. Fourteen guidelines were compared. The recommended dose, screening method, and gestational age at the start of the test vary depending on the recommendation. The societies are inclined to recommend using increasingly higher doses (>75 mg) of ASA, with many encouraging doses from 100 mg upward. Most societies indicate that the optimal time for implementing aspirin is prior to 16 weeks' gestation. Following the publication of the Aspirin for Evidence-Based Preeclampsia Prevention (ASPRE) trial results and other papers evaluating the Fetal Medicine Foundation (FMF) screening model, a large number of societies have changed their recommendations from those based on risk factors alone to the ones based on the risk assessment proposed by the FMF. This allows for the detection of a high-risk pregnancy population in whom aspirin will be remarkably effective in preventing preterm PE, thereby decreasing maternal and fetal morbidity.

Preeclampsia at term can be classified into 2 clusters with different clinical characteristics and outcomes based on angiogenic biomarkers in maternal blood

BACKGROUND

An antiangiogenic state has emerged as a mechanism of disease in preeclampsia. Angiogenic biomarkers are used in the risk assessment of this syndrome, particularly of early disease. The role of an antiangiogenic state in late preeclampsia is unclear.

OBJECTIVE

This study aimed to determine the prevalence, characteristics, and clinical significance of angiogenic/antiangiogenic factor abnormalities in women with preeclampsia stratified according to gestational age at delivery.

STUDY DESIGN

Two studies were conducted: (1) a longitudinal nested case-control study comprising women with preeclampsia (n=151) and a control group (n=540); and (2) a case series of patients with preeclampsia (n=452). In patients with preeclampsia, blood was collected at the time of diagnosis. Plasma concentrations of placental growth factor and soluble fms-like tyrosine kinase-1 were determined by enzyme-linked immunosorbent assays. An abnormal angiogenic profile was defined as a plasma ratio of placental growth factor and soluble fms-like tyrosine kinase-1 expressed as a multiple of the median <10th percentile for gestational age based on values derived from the longitudinal study. The proportion of patients diagnosed with preeclampsia who had an abnormal angiogenic profile was determined in the case-series participants and stratified by gestational age at delivery into early (≤34 weeks), intermediate (34.1-36.9 weeks), and term (≥37 weeks) preeclampsia. The demographics, clinical characteristics, and pregnancy outcomes of women with preeclampsia with and without an abnormal angiogenic profile were compared.

RESULTS

The prevalence of an abnormal angiogenic profile was higher in preterm than in term preeclampsia (for early, intermediate, and term in the case-control study: 90%, 100%, and 39%; for the case series: 98%, 80%, and 55%, respectively). Women with preeclampsia at term who had an abnormal angiogenic profile were more frequently nulliparous (57% vs 35%), less likely to smoke (14% vs 26%), at greater risk for maternal (14% vs 5%) or neonatal (7% vs 1%) complications, and more often had placental lesions consistent with maternal vascular malperfusion (42% vs 23%; all, P<.05) than those without an abnormal profile. Women with preeclampsia at term who had a normal angiogenic profile had a higher frequency of chronic hypertension (36% vs 21%) and were more likely to have class ≥2 obesity (41% vs 23%) than those with an abnormal profile (both, P<.05).

CONCLUSION

Patients with early preeclampsia had an abnormal angiogenic profile in virtually all cases, whereas only 50% of women with preeclampsia at term had such abnormalities. The profile of angiogenic biomarkers can be used to classify patients with preeclampsia at term, on the basis of mechanisms of disease, into 2 clusters, which have different demographics, clinical characteristics, and risks of adverse maternal and neonatal outcomes. These findings provide a simple approach to classify preeclampsia at term and have implications for future clinical care and research.

Combined maternal risk factors and the Quadruple test to predict late-onset preeclampsia in pregnant Thai women

BACKGROUND

This study aimed to evaluate the predictive power of a model combining maternal risk factors and the Quadruple screen test for late-onset preeclampsia (PE).

METHODS

All pregnant women that received the Quadruple test for Down syndrome at 15^+ 0-20^+ 6 weeks' gestation were recruited. Maternal serum α-fetoprotein, β-human chorionic gonadotropin, unconjugated estriol, and inhibin A were measured as multiples of the median. A logistic regression model was used to identify predictors associated with late-onset PE with severe features. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to assess the model's predictive ability.

RESULTS

Fifty-five of the 2,000 pregnant women had PE, and 31 of 55 women had late-onset PE. Multivariate analysis identified maternal age ≥ 35 years, inhibin A, history of previous PE, history of infertile, cardiac disease, chronic hypertension, and thyroid disease as significant risk factors. The area under the curve of the receiver operating characteristic curve was 0.78. The likelihood ratio to predict late-onset PE was 49.4 (total score > 60).

CONCLUSIONS

Our model combining serum inhibin A with maternal risk factors was useful in predicting late-onset PE. Close monitoring of these patients is recommended.

Reference ranges of uterine artery pulsatility index from first to third trimester based on serial Doppler measurements: longitudinal cohort study

OBJECTIVE

To provide gestational-age (GA)-specific reference ranges for mean uterine artery (UtA) pulsatility index (PI) based on longitudinal data assessment throughout pregnancy.

METHODS

This was a prospective longitudinal cohort study of singleton low-risk pregnancies with adequate health and nutritional status at the time of enrolment and without fetal anomaly, receiving prenatal care between January 2018 and July 2021 at the Maternal Fetal Medicine Unit of IRCCS San Raffaele Scientific Institute, Milan, Italy. Women were recruited at ≤ 12 + 6 weeks' gestation and underwent serial standardized ultrasound monitoring, including UtA-PI measurement, by experienced certified operators until delivery. Association of UtA-PI with GA was modeled with fractional polynomial regression. Equations for mean ± SD of the estimated curves were calculated, as well as GA-specific reference charts of centiles for UtA-PI from 10 + 0 to 39 + 0 gestational weeks.

RESULTS

We included 476 healthy, low-risk pregnant women and a total of 2045 ultrasound scans (median, 4 (range, 3-9) per patient) were available for analysis. Mean UtA-PI was 1.84 ± 0.55, 1.07 ± 0.38 and 0.78 ± 0.23 in the first, second and third trimesters of pregnancy, respectively. Goodness-of-fit assessment revealed that second-degree smoothing was the most accurate fractional polynomial for describing the course of UtA-PI throughout gestation; therefore, it was modeled in a multilevel framework for the construction of UtA-PI curves. We observed a rapid and substantial decrease in mean UtA-PI before 16 weeks, with subsequent smoother decrement of the slope and more stable values from 20 until 39 weeks. The 3rd , 5th , 10th , 25th , 50th , 75th , 90th , 95th and 97th centiles according to GA for UtA-PI are provided, as well as equations to allow calculation of any value as a centile.

CONCLUSIONS

UtA-PI shows a progressive non-linear decrease throughout pregnancy. The new reference ranges for GA-specific mean UtA-PI constructed using rigorous methodology may have a better performance compared with previous models for screening for placenta-associated diseases in the early stages of pregnancy and for evaluating the potential risk for pregnancy-induced hypertension and/or small-for-gestational age later in pregnancy. © 2022 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Potential biomarkers for late-onset and term preeclampsia: A scoping review

Preeclampsia is a progressive, multisystem pregnancy disorder. According to the time of onset or delivery, preeclampsia has been subclassified into early-onset (<34 weeks) and late-onset (≥34 weeks), or preterm (<37 weeks) and term (≥37 weeks). Preterm preeclampsia can be effectively predicted at 11-13 weeks well before onset, and its incidence can be reduced by preventively using low-dose aspirin. However, late-onset and term preeclampsia are more prevalent than early forms and still lack effective predictive and preventive measures. This scoping review aims to systematically identify the evidence of predictive biomarkers reported in late-onset and term preeclampsia. This study was conducted based on the guidance of the Joanna Briggs Institute (JBI) methodology for scoping reviews. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for scoping reviews (PRISMA-ScR) was used to guide the study. The following databases were searched for related studies: PubMed, Web of Science, Scopus, and ProQuest. Search terms contain "preeclampsia," "late-onset," "term," "biomarker," or "marker," and other synonyms combined as appropriate using the Boolean operators "AND" and "OR." The search was restricted to articles published in English from 2012 to August 2022. Publications were selected if study participants were pregnant women and biomarkers were detected in maternal blood or urine samples before late-onset or term preeclampsia diagnosis. The search retrieved 4,257 records, of which 125 studies were included in the final assessment. The results demonstrate that no single molecular biomarker presents sufficient clinical sensitivity and specificity for screening late-onset and term preeclampsia. Multivariable models combining maternal risk factors with biochemical and/or biophysical markers generate higher detection rates, but they need more effective biomarkers and validation data for clinical utility. This review proposes that further research into novel biomarkers for late-onset and term preeclampsia is warranted and important to find strategies to predict this complication. Other critical factors to help identify candidate markers should be considered, such as a consensus on defining preeclampsia subtypes, optimal testing time, and sample types.

Reconsidering Race Adjustment in Prenatal Alpha-Fetoprotein Screening

OBJECTIVE

Black racial designation is the only race for which adjustment is recommended for maternal prenatal serum alpha-fetoprotein (AFP) screening. The objective of this study is to reevaluate the relationship between maternal race and maternal serum AFP values in prenatal analyte screening.

METHODS

This was a single-center retrospective analysis of patients who underwent prenatal analyte screening between January 2007 and December 2020. Nomograms for raw maternal serum AFP values by gestational age were created and compared between patients identified as "Black" and "non-Black" on the laboratory requisition. Multivariable linear regression models were created to evaluate the relationship among gestational age, maternal weight, and maternal race on maternal serum AFP levels. The new models were compared with the laboratory-derived calculations, which used historically determined race adjustments.

RESULTS

A total of 43,997 patients underwent analyte screening, and 27,710 patients had complete data for analysis. Of these, 6% were identified as Black. Black patients had laboratory blood draws at a mean gestational age of 123 days, compared with 120 days in non-Black patients ( P <.001), and had higher maternal weight (mean 170 vs 161 lbs, P <.001). Nomograms for raw maternal serum AFP values did not differ between Black and non-Black patients ( P =.065). When adjusted for gestational age and maternal weight, no difference in maternal serum AFP values was identified between Black and non-Black individuals ( P =.81).

CONCLUSION

No difference in maternal serum AFP values was identified between Black and non-Black pregnant individuals when adjusted by maternal weight and gestational age at blood draw. These findings suggest that routine race-based adjustment of maternal serum AFP screening should be discontinued.

Aspirin Discontinuation at 24 to 28 Weeks' Gestation in Pregnancies at High Risk of Preterm Preeclampsia: A Randomized Clinical Trial

IMPORTANCE

Aspirin reduces the incidence of preterm preeclampsia by 62% in pregnant individuals at high risk of preeclampsia. However, aspirin might be associated with an increased risk of peripartum bleeding, which could be mitigated by discontinuing aspirin before term (37 weeks of gestation) and by an accurate selection of individuals at higher risk of preeclampsia in the first trimester of pregnancy.

OBJECTIVE

To determine whether aspirin discontinuation in pregnant individuals with normal soluble fms-like tyrosine kinase-1 to placental growth factor (sFlt-1:PlGF) ratio between 24 and 28 weeks of gestation was noninferior to aspirin continuation to prevent preterm preeclampsia.

DESIGN, SETTING, AND PARTICIPANTS

Multicenter, open-label, randomized, phase 3, noninferiority trial conducted in 9 maternity hospitals across Spain. Pregnant individuals (n = 968) at high risk of preeclampsia during the first-trimester screening and an sFlt-1:PlGF ratio of 38 or less at 24 to 28 weeks of gestation were recruited between August 20, 2019, and September 15, 2021; of those, 936 were analyzed (intervention: n = 473; control: n = 463). Follow-up was until delivery for all participants.

INTERVENTIONS

Enrolled patients were randomly assigned in a 1:1 ratio to aspirin discontinuation (intervention group) or aspirin continuation until 36 weeks of gestation (control group).

MAIN OUTCOMES AND MEASURES

Noninferiority was met if the higher 95% CI for the difference in preterm preeclampsia incidences between groups was less than 1.9%.

RESULTS

Among the 936 participants, the mean (SD) age was 32.4 (5.8) years; 3.4% were Black and 93% were White. The incidence of preterm preeclampsia was 1.48% (7/473) in the intervention group and 1.73% (8/463) in the control group (absolute difference, -0.25% [95% CI, -1.86% to 1.36%]), indicating noninferiority.

CONCLUSIONS AND RELEVANCE

Aspirin discontinuation at 24 to 28 weeks of gestation was noninferior to aspirin continuation for preventing preterm preeclampsia in pregnant individuals at high risk of preeclampsia and a normal sFlt-1:PlGF ratio.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03741179 and ClinicalTrialsRegister.eu Identifier: 2018-000811-26.

Pre-eclampsia

Pre-eclampsia is a life-threatening disease of pregnancy unique to humans and a leading cause of maternal and neonatal morbidity and mortality. Women who survive pre-eclampsia have reduced life expectancy, with increased risks of stroke, cardiovascular disease and diabetes, while babies from a pre-eclamptic pregnancy have increased risks of preterm birth, perinatal death and neurodevelopmental disability and cardiovascular and metabolic disease later in life. Pre-eclampsia is a complex multisystem disease, diagnosed by sudden-onset hypertension (>20 weeks of gestation) and at least one other associated complication, including proteinuria, maternal organ dysfunction or uteroplacental dysfunction. Pre-eclampsia is found only when a placenta is or was recently present and is classified as preterm (delivery <37 weeks of gestation), term (delivery ≥37 weeks of gestation) and postpartum pre-eclampsia. The maternal syndrome of pre-eclampsia is driven by a dysfunctional placenta, which releases factors into maternal blood causing systemic inflammation and widespread maternal endothelial dysfunction. Available treatments target maternal hypertension and seizures, but the only 'cure' for pre-eclampsia is delivery of the dysfunctional placenta and baby, often prematurely. Despite decades of research, the aetiology of pre-eclampsia, particularly of term and postpartum pre-eclampsia, remains poorly defined. Significant advances have been made in the prediction and prevention of preterm pre-eclampsia, which is predicted in early pregnancy through combined screening and is prevented with daily low-dose aspirin, starting before 16 weeks of gestation. By contrast, the prediction of term and postpartum pre-eclampsia is limited and there are no preventive treatments. Future research must investigate the pathogenesis of pre-eclampsia, in particular of term and postpartum pre-eclampsia, and evaluate new prognostic tests and treatments in adequately powered clinical trials.

Perspectives on the Use of Placental Growth Factor (PlGF) in the Prediction and Diagnosis of Pre-Eclampsia: Recent Insights and Future Steps

Pre-eclampsia (PE) is a complex multisystem disease of pregnancy that is becoming increasingly recognized as a state of angiogenic imbalance characterized by low concentrations of placental growth factor (PlGF) and elevated soluble fms-like tyrosine kinase (sFlt-1). PlGF is a protein highly expressed by the placenta with vasculogenic and angiogenic properties, which has a central role in spiral artery remodeling and the development of a low-resistance placental capillary network. PlGF concentrations are significantly lower in women with preterm PE, and these reduced levels have been shown to precede the clinical onset of disease. Subsequently, the clinical utility of maternal serum PlGF has been extensively studied in singleton gestations from as early as 11 to 13 weeks' gestation, utilizing a validated multimarker prediction model, which performs superiorly to the National Institute for Health and Care Excellence (NICE) and American College of Obstetricians and Gynecologists (ACOG) guidelines in the detection of preterm PE. There is extensive research highlighting the role of PlGF-based testing utilizing commercially available assays in accelerating the diagnosis of PE in symptomatic women over 20 weeks' gestation and predicting time-to-delivery, allowing individualized risk stratification and appropriate antenatal surveillance to be determined. "Real-world" data has shown that interpretation of PlGF-based test results can aid clinicians in improving maternal outcomes and a growing body of evidence has implied a role for sFlt-1/PlGF in the prognostication of adverse pregnancy and perinatal events. Subsequently, PlGF-based testing is increasingly being implemented into obstetric practice and is advocated by NICE. This literature review aims to provide healthcare professionals with an understanding of the role of angiogenic biomarkers in PE and discuss the evidence for PlGF-based screening and triage. Prospective studies are warranted to explore if its implementation significantly improves perinatal outcomes, explore the value of repeat PlGF testing, and its use in multiple pregnancies.

Incidence of stillbirth: effect of deprivation

OBJECTIVES

To examine the relationship between the English index of multiple deprivation (IMD) and the incidence of stillbirth and assess whether IMD contributes to the prediction of stillbirth provided by the combination of maternal demographic characteristics and elements of medical history.

METHODS

This was a prospective, observational study of 159 125 women with a singleton pregnancy who attended their first routine hospital visit at 11 + 0 to 13 + 6 weeks' gestation in two maternity hospitals in the UK. The inclusion criterion was delivery at ≥ 24 weeks' gestation of a fetus without major abnormality. Participants completed a questionnaire on demographic characteristics and obstetric and medical history. IMD was used as a measure of socioeconomic status, which takes into account income, employment, education, skills and training, health and disability, crime, barriers to housing and services, and living environment. Each neighborhood is ranked according to its level of deprivation relative to that of other areas into one of five equal groups, with Quintile 1 containing the 20% most deprived areas and Quintile 5 containing the 20% least deprived areas. Logistic regression analysis was used to determine whether IMD provided a significant independent contribution to stillbirth after adjustment for known maternal risk factors.

RESULTS

The overall incidence of stillbirth was 0.35% (551/159 125), and this was significantly higher in the most deprived compared with the least deprived group (Quintile 1 vs Quintile 5). The odds ratio (OR) in Quintile 1 was 1.57 (95% CI, 1.16-2.14) for any stillbirth, 1.64 (95% CI, 1.20-2.28) for antenatal stillbirth and 1.89 (95% CI, 1.23-2.98) for placental dysfunction-related stillbirth. In Quintile 1 (vs Quintile 5), there was a higher incidence of factors that contribute to stillbirth, including black race, increased body mass index, smoking, chronic hypertension and previous stillbirth. The OR of black (vs white) race was 2.58 (95% CI, 2.14-3.10) for any stillbirth, 2.62 (95% CI, 2.16-3.17) for antenatal stillbirth and 3.34 (95% CI, 2.59-4.28) for placental dysfunction-related stillbirth. Multivariate analysis showed that IMD did not have a significant contribution to the prediction of stillbirth provided by maternal race and other maternal risk factors. In contrast, in black (vs white) women, the risk of any and antenatal stillbirth was 2.4-fold higher and the risk of placental dysfunction-related stillbirth was 2.9-fold higher after adjustment for other maternal risk factors.

CONCLUSIONS

The incidence of stillbirth, particularly placental dysfunction-related stillbirth, is higher in women living in the most deprived areas in South East England. However, in screening for stillbirth, inclusion of IMD does not improve the prediction provided by race, other maternal characteristics and elements of medical history. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Effects of maternal characteristics and medical history on first trimester biomarkers for preeclampsia

Objective

To identify and quantify the effects of maternal characteristics and medical history on the distribution of Placental Growth Factor (PlGF), mean arterial pressure (MAP), and Uterine Artery Mean Pulsatility Index (UtA-PI); and to standardize the expected values for these biomarkers in the first trimester to create unique multiples of the median (MoMs) for Latin-American population.

Methods

This is a prospective cohort built exclusively for research purposes of consecutive pregnant women attending their first-trimester screening ultrasound at a primary care center for the general population in Mexico City between April 2019 and October 2021. We excluded fetuses with chromosomal abnormalities, major fetal malformations, and women delivering in another care center. Linear regression was used on log-transformed biomarkers to assess the influence of maternal characteristics on non-preeclamptic women to create MoM.

Results

Of a total of 2,820 pregnant women included in the final analysis, 118 (4.18%) developed PE, of which 22 (0.78%) delivered before 34 weeks of gestation, 74 (2.62%) before 37 weeks, and 44 (1.56%) from 37 weeks gestation. Characteristics that significantly influenced PLGF were fetal crown rump length (CRL), maternal age, nulliparity, body mass index (BMI), chronic hypertension, Lupus, spontaneous pregnancy, polycystic ovary syndrome (PCOS), hypothyroidism, preeclampsia (PE) in a previous pregnancy, and mother with PE. MAP had significant influence from CRL, maternal age, PE in a previous pregnancy, induction of ovulation, a mother with PE, chronic hypertension, BMI, and hypothyroidism. UtA-PI was influenced by CRL, maternal age, a mother with PE, chronic hypertension, and gestational diabetes mellitus (GDM) in a previous pregnancy.

Conclusion

Population-specific multiples of the median (MoMs) for PlGF, MAP, and UtA-PI in the first trimester adequately discriminate among women developing preeclampsia later in pregnancy.

Predictive Performance of Machine Learning-Based Methods for the Prediction of Preeclampsia-A Prospective Study

(1) Background: Preeclampsia (PE) prediction in the first trimester of pregnancy is a challenge for clinicians. The aim of this study was to evaluate and compare the predictive performances of machine learning-based models for the prediction of preeclampsia and its subtypes. (2) Methods: This prospective case-control study evaluated pregnancies that occurred in women who attended a tertiary maternity hospital in Romania between November 2019 and September 2022. The patients' clinical and paraclinical characteristics were evaluated in the first trimester and were included in four machine learning-based models: decision tree (DT), naïve Bayes (NB), support vector machine (SVM), and random forest (RF), and their predictive performance was assessed. (3) Results: Early-onset PE was best predicted by DT (accuracy: 94.1%) and SVM (accuracy: 91.2%) models, while NB (accuracy: 98.6%) and RF (accuracy: 92.8%) models had the highest performance when used to predict all types of PE. The predictive performance of these models was modest for moderate and severe types of PE, with accuracies ranging from 70.6% and 82.4%. (4) Conclusions: The machine learning-based models could be useful tools for EO-PE prediction and could differentiate patients who will develop PE as early as the first trimester of pregnancy.

First-trimester screening for pre-eclampsia and small for gestational age: A comparison of the gaussian and Fetal Medicine Foundation algorithms

OBJECTIVE

Pre-eclampsia (PE) and small for gestational age (SGA) can be predicted from the first trimester. The most widely used algorithm worldwide is the Fetal Medicine Foundation (FMF) algorithm. The recently described Gaussian algorithm has reported excellent results although it is unlikely to be externally validated. Therefore, as an alternative approach, we compared the predictive accuracy for PE and SGA of the Gaussian and FMF algorithms.

METHODS

Secondary analysis of a prospective cohort study was conducted at Vall d'Hebron University Hospital (Barcelona) with 2641 singleton pregnancies. The areas under the curve for the predictive performance for early-onset and preterm PE and early-onset and preterm SGA were calculated with the Gaussian and FMF algorithms and subsequently compared.

RESULTS

The FMF and Gaussian algorithms showed a similar predictive performance for most outcomes and marker combinations. Nevertheless, significant differences for early-onset PE prediction favored the Gaussian algorithm in the following combinations: mean arterial blood pressure (MAP) with pregnancy-associated plasma protein A, MAP with placental growth factor, and MAP alone.

CONCLUSIONS

The first-trimester Gaussian and FMF algorithms have similar performances for PE and SGA prediction when applied with all markers within a routine care setting in a Spanish population, adding evidence to the external validity of the FMF algorithm.

First-trimester preterm preeclampsia prediction with metabolite biomarkers: differential prediction according to maternal body mass index

BACKGROUND

Prediction of preeclampsia risk is key to informing effective maternal care. Current screening for preeclampsia at 11 to 13 weeks of gestation using maternal demographic characteristics and medical history with measurements of mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor can identify approximately 75% of women who develop preterm preeclampsia with delivery at <37 weeks of gestation. Further improvements to preeclampsia screening tests will likely require integrating additional biomarkers. Recent research suggests the existence of distinct maternal risk profiles. Therefore, biomarker evaluation should account for the possibility that a biomarker only predicts preeclampsia in a specific maternal phenotype.

OBJECTIVE

This study aimed to verify metabolite biomarkers as preterm preeclampsia predictors early in pregnancy in all women and across body mass index groups.

STUDY DESIGN

Observational case-control study drawn from a large prospective study on the early prediction of pregnancy complications in women attending their routine first hospital visit at King's College Hospital, London, United Kingdom, in 2010 to 2015. Pregnant women underwent a complete first-trimester assessment, including the collection of blood samples for biobanking. In 11- to 13-week plasma samples of 2501 singleton pregnancies, the levels of preselected metabolites implicated in the prediction of pregnancy complications were analyzed using a targeted liquid chromatography-mass spectrometry method, yielding high-quality quantification data on 50 metabolites. The ratios of amino acid levels involved in arginine biosynthesis and nitric oxide synthase pathways were added to the list of biomarkers. Placental growth factor and pregnancy-associated plasma protein A were also available for all study subjects, serving as comparator risk predictors. Data on 1635 control and 106 pregnancies complicated by preterm preeclampsia were considered for this analysis, normalized using multiples of medians. Prediction analyses were performed across the following patient strata: all subjects and the body mass index classes of <25, 25 to <30, and ≥30 kg/m². Adjusted median levels were compared between cases and controls and between each body mass index class group. Odds ratios and 95% confidence intervals were calculated at the mean ±1 standard deviation to gauge clinical prediction merits.

RESULTS

The levels of 13 metabolites were associated with preterm preeclampsia in the entire study population (P<.05) with particularly significant (P<.01) associations found for 6 of them, namely, 2-hydroxy-(2/3)-methylbutyric acid, 25-hydroxyvitamin D3, 2-hydroxybutyric acid, alanine, dodecanoylcarnitine, and 1-(1Z-octadecenyl)-2-oleoyl-sn-glycero-3-phosphocholine. Fold changes in 7 amino acid ratios, all involving glutamine or ornithine, were also significantly different between cases and controls (P<.01). The predictive performance of some metabolites and ratios differed according to body mass index classification; for example, ornithine (P<.001) and several ornithine-related ratios (P<.0001 to P<.01) were only strongly associated with preterm preeclampsia in the body mass index of <25 kg/m² group, whereas dodecanoylcarnitine and 3 glutamine ratios were particularly predictive in the body mass index of ≥30 kg/m² group (P<.01).

CONCLUSION

Single metabolites and ratios of amino acids related to arginine bioavailability and nitric oxide synthase pathways were associated with preterm preeclampsia risk at 11 to 13 weeks of gestation. Differential prediction was observed according to body mass index classes, supporting the existence of distinct maternal risk profiles. Future studies in preeclampsia prediction should account for the possibility of different maternal risk profiles to improve etiologic and prognostic understanding and, ultimately, clinical utility of screening tests.

Establishment and validation of a predictive model of preeclampsia based on transcriptional signatures of 43 genes in decidua basalis and peripheral blood

Preeclampsia (PE) has an increasing incidence worldwide, and there is no gold standard for prediction. Recent progress has shown that abnormal decidualization and impaired vascular remodeling are essential to PE pathogenesis. Therefore, it is of great significance to analyze the decidua basalis and blood changes of PE to explore new methods. Here, we performed weighted gene co-expression network analysis based on 9553 differentially expressed genes of decidua basalis data (GSE60438 includes 25 cases of PE and 23 non-cases) from Gene Expression Omnibus to screen relevant module-eigengenes (MEs). Among them, MEblue and MEgrey are the most correlated with PE, which contains 371 core genes. Subsequently, we applied the logistic least absolute shrinkage and selection operator regression, screened 43 genes most relevant to prediction from the intersections of the 371 genes and training set (GSE48424 includes 18 cases of PE and 18 non-cases) genes, and built a predictive model. The specificity and sensitivity are illustrated by receiver operating characteristic curves, and the stability was verified by two validation sets (GSE86200 includes 12 cases of PE and 48 non-cases, and GSE85307 includes 47 cases of PE and 110 non-cases). The results demonstrated that our predictive model shows good predictions, with an area under the curve of 0.991 for the training set, 0.874 and 0.986 for the validation sets. Finally, we found the 43 key marker genes in the model are closely associated with the clinically accepted predictive molecules, including FLT1, PIGF, ENG and VEGF. Therefore, this predictive model provides a potential approach for PE diagnosis and treatment.

Quality assessment of first-trimester screening for preterm pre-eclampsia

OBJECTIVE

To assess the performance and impact of first-trimester preterm pre-eclampsia screening in a single center.

METHODS

This was a single-center study of women with a singleton pregnancy who were screened prospectively for preterm pre-eclampsia (i.e. delivery before 37 weeks' gestation) using maternal characteristics, mean arterial pressure (MAP), uterine artery Doppler pulsatility index, maternal serum pregnancy-associated plasma protein-A and placental growth factor. The individual risk for preterm pre-eclampsia was estimated from a published model, and those with a risk above 1 in 200 were recommended to take 150 mg soluble aspirin per day until 34 weeks. Information on the incidence of pre-eclampsia was obtained from the hospital register of adverse pregnancy outcomes. Screening performance indicators, including detection and false-positive rates, were estimated from the distribution of risks. Screening impact was estimated by dividing the observed prevalence by the expected prevalence, which was derived from the distribution of risks.

RESULTS

The distributions of MAP, uterine artery Doppler pulsatility index and serum markers were consistent with the risk model parameters. The estimated detection and false-positive rates were 79.7% and 16.2%, respectively. There were six cases of preterm pre-eclampsia, four of which occurred in women with a positive screening result. The prevalence was 62% of that expected, but the 95% CI of 23-140% indicated that the study was underpowered to assess the impact.

CONCLUSIONS

This study demonstrates that the performance of preterm pre-eclampsia screening can be estimated in a single center with fewer than 2000 women screened. However, in order to assess the impact of screening on the prevalence of the condition, a much larger cohort is needed. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Machine-learning-based prediction of pre-eclampsia using first-trimester maternal characteristics and biomarkers

OBJECTIVE

To evaluate the accuracy of predicting the risk of developing pre-eclampsia (PE) according to first-trimester maternal demographic characteristics, medical history and biomarkers using artificial-intelligence and machine-learning methods.

METHODS

The data were derived from prospective non-interventional screening for PE at 11-13 weeks' gestation at two maternity hospitals in the UK. The data were divided into three subsets. The first set, including 30 437 subjects, was used to develop the training process, the second set of 10 000 subjects was utilized to optimize the machine-learning hyperparameters and the third set of 20 352 subjects was coded and used for model validation. An artificial neural network was used to predict from the demographic characteristics and medical history the prior risk that was then combined with biomarker values to determine the risk of PE and preterm PE with delivery at < 37 weeks' gestation. An additional network was trained without including race as input. Biomarkers included uterine artery pulsatility index (UtA-PI), mean arterial blood pressure (MAP), placental growth factor (PlGF) and pregnancy-associated plasma protein-A. All markers were entered using raw values without conversion into standardized multiples of the median. The prediction accuracy was estimated using the area under the receiver-operating-characteristics curve (AUC). We further computed the detection rate at 10%, 20% and 40% false-positive rates (FPR). The impact of taking aspirin was also added. Shapley values were calculated to evaluate the contribution of each parameter to the prediction of risk. We used a non-parametric test to compare the expected AUC with the one obtained when we randomly scrambled the labels and kept the predictions. For the general prediction, we performed 10 000 permutations of the labels. When the AUC was higher than the one obtained in all 10 000 permutations, we reported a P-value of < 0.0001. For the race-specific analysis, we performed 1000 permutations. When the AUC was higher than the AUC in permutations, we reported a P-value of < 0.001.

RESULTS

The detection rate for preterm PE vs no PE, at a 10% FPR, was 53.3% when screening by maternal factors only, and the corresponding AUC was 0.816; these increased to 75.3% and 0.909, respectively, with the addition of biomarkers into the model. Information on race was important for the prediction accuracy; when race was not used to train the model, at a 10% FPR, the detection rate of preterm PE vs no PE decreased to 34.5-45.5% (for different races) when screening by maternal factors only and to 55.0-62.1% when biomarkers were added. The major predictors of PE were high MAP and UtA-PI, and low PlGF. The accuracy of prediction of all PE cases was lower than that for preterm PE. Aspirin use was recommended for cases who were at high risk of preterm PE. The AUC of all PE vs no PE was 0.770 when screening by maternal factors and 0.817 when the biomarkers were added; the respective detection rates, at a 10% FPR, were 41.3% and 52.9%.

CONCLUSIONS

Screening for PE using a non-linear machine-learning-based approach does not require a population-based normalization, and its performance is similar to that of logistic regression. Removing race information from the model reduces its prediction accuracy, especially for the non-white populations when only maternal factors are considered. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Human Plasma Proteome During Normal Pregnancy

The human plasma proteome is underexplored despite its potential value for monitoring health and disease. Herein, using a recently developed aptamer-based platform, we profiled 7288 proteins in 528 plasma samples from 91 normal pregnancies (Gene Expression Omnibus identifier GSE206454). The coefficient of variation was <20% for 93% of analytes (median 7%), and a cross-platform correlation for selected key angiogenic and anti-angiogenic proteins was significant. Gestational age was associated with changes in 953 proteins, including highly modulated placenta- and decidua-specific proteins, and they were enriched in biological processes including regulation of growth, angiogenesis, immunity, and inflammation. The abundance of proteins corresponding to RNAs specific to populations of cells previously described by single-cell RNA-Seq analysis of the placenta was highly modulated throughout gestation. Furthermore, machine learning-based prediction of gestational age and of time from sampling to term delivery compared favorably with transcriptomic models (mean absolute error of 2 weeks). These results suggested that the plasma proteome may provide a non-invasive readout of placental cellular dynamics and serve as a blueprint for investigating obstetrical disease.

Novel First-Trimester Prediction Model for Any Type of Preterm Birth Occurring before 37 Gestational Weeks in the Absence of Other Pregnancy-Related Complications Based on Cardiovascular Disease-Associated MicroRNAs and Basic Maternal Clinical Characteristics

The goal of the study was to establish an efficient first-trimester predictive model for any type of preterm birth before 37 gestational weeks (spontaneous preterm birth (PTB) or preterm prelabor rupture of membranes (PPROM)) in the absence of other pregnancy-related complications, such as gestational hypertension, preeclampsia, fetal growth restriction, or small for gestational age. The retrospective study was performed in the period from 11/2012 to 3/2020. Peripheral blood samples were collected from 6440 Caucasian individuals involving 41 PTB and 65 PPROM singleton pregnancies. A control group with 80 singleton term pregnancies was selected on the basis of equal sample-storage time. A combination of only six microRNAs (miR-16-5p, miR-21-5p, miR-24-3p, miR-133a-3p, miR-155-5p, and miR-210-3p; AUC 0.812, p < 0.001, 70.75% sensitivity, 78.75% specificity, cut-off > 0.652) could predict preterm delivery before 37 gestational weeks in early stages of gestation in 52.83% of pregnancies with a 10.0% FPR. This predictive model for preterm birth based on aberrant microRNA expression profile was further improved via implementation of maternal clinical characteristics (maternal age and BMI at early stages of gestation, infertility treatment with assisted reproductive technology, occurrence of preterm delivery before 37 gestational weeks in previous pregnancy(ies), and presence of any kind of autoimmune disease (rheumatoid arthritis, systemic lupus erythematosus, antiphospholipid syndrome, type 1 diabetes mellitus, or other autoimmune disease)). With this model, 69.81% of pregnancies destined to deliver before 37 gestational weeks were identified with a 10.0% FPR at early stages of gestation. When other clinical variables as well as those mentioned above—such as positive first-trimester screening for early preeclampsia with onset before 34 gestational weeks and/or fetal growth restriction with onset before 37 gestational weeks using the Fetal Medicine Foundation algorithm, as well as positive first-trimester screening for spontaneous preterm birth with onset before 34 gestational weeks using the Fetal Medicine Foundation algorithm—were added to the predictive model for preterm birth, the predictive power was even slightly increased to 71.70% with a 10.0% FPR. Nevertheless, we prefer to keep the first-trimester screening for any type of preterm birth occurring before 37 gestational weeks in the absence of other pregnancy-related complications as simple as possible.

American College of Cardiology and American Heart Association blood pressure categories-a systematic review of the relationship with adverse pregnancy outcomes in the first half of pregnancy

OBJECTIVE

A relationship between the 2017 American College of Cardiology and American Heart Association blood pressure thresholds and adverse pregnancy outcomes has been reported, but few studies have explored the diagnostic test properties of these cutoffs.

DATA SOURCES

We systematically searched electronic databases (from 2017 to 2021) for reports of blood pressure measurements in pregnancy, classified according to 2017 American College of Cardiology and American Heart Association criteria, and their relationship with pregnancy outcomes.

STUDY ELIGIBILITY CRITERIA

Studies recording blood pressure at <20 weeks gestation were included.

METHODS

Meta-analyses were used to investigate the strength of the association between blood pressure cutoffs and adverse outcomes, and the diagnostic test properties were calculated.

RESULTS

Of 23 studies included, there was a stepwise relationship between the American College of Cardiology and American Heart Association blood pressure category (when compared with normal blood pressure of <120/80 mmHg) and the strength of the association with preeclampsia. The category of elevated blood pressure had a risk ratio of 2.0 (95% prediction interval, 0.8-4.8), the stage 1 hypertension category had a risk ratio of 3.0 (95% prediction interval, 1.1-8.5), and the stage 2 hypertension category had a risk ratio of 7.9 (95% prediction interval, 1.8-35.1). Between-study variability was related to the magnitude of the association with stronger relationships in larger studies at low risk of bias and with unselected populations with multiple routine blood pressure measurements. None of the systolic blood pressure measurements of <120 mmHg, <130/80 mmHg, or <140/90 mmHg were useful to rule out the development of preeclampsia (all negative likelihood ratios >0.2). Only a blood pressure measurement of ≥140/90 mmHg was a good predictor for the development of preeclampsia (positive likelihood ratio, 5.95). The findings were similar for other outcomes.

CONCLUSION

Although a blood pressure of 120 to 140 over 80 to 90 mmHg at <20 weeks gestation is associated with a heightened risk for preeclampsia and adverse pregnancy outcomes and may assist in risk prediction in multivariable modelling, lowering the diagnostic threshold for chronic hypertension would not assist clinicians in identifying women at heightened risk.

Prospective observational comparison of arteria uterina blood flow between two frozen embryo transfer cycle regimens: natural cycle versus hormonal replacement cycle

PURPOSE

Is there a difference in the blood flow of the Arteria uterina in frozen embryo transfer (FET) cycles between a Natural Cycle (NC) and a Hormonal Replacement Therapy (HRT) cycle?

METHODS

Prospective observational study with measurement of the pulsatility index (PI) and resistance index (RI) throughout the ovarian stimulation cycle for IVF/ICSI, the FET cycle and at 12 weeks of gestation.

RESULTS

A total of 124 ovarian stimulation cycles with preimplantation genetic testing for aneuploidy (PGT-A) and "freeze-all" strategy due to PGT-A were included. Mean patient's age was 31.4 years, mean BMI 26.47 kg/m2, mean AMH 3.62 ng/ml and a mean AFC of 13. FET cycles were performed in 77 patients (NC protocol: 37.7%, HRT protocol: 62.2%). The overall pregnancy rate was 75%, (NC group: 79%, HRT-group 73%; not significant). No significant change of PI and RI was seen during hormonal stimulation. In FET cycles, there was a significant increase between cycle day 2/3 and ovulation/P4-start in the HRT-cycle, followed by a significant decrease until 12 weeks of gestation. The slope of the decrease in patients with a pregnancy in an HRT-approach was a bit steeper than in the NC-approach for both PI and RI, however, without a significant difference.

CONCLUSIONS

Early measurements of the blood flow parameters during the FET cycle do not reveal a difference between the NC- and the HRT-approach for FET, which could be predictive for development of pre-eclampsia.

Reviewing Accuracy of First Trimester Screening for Preeclampsia Using Maternal Factors and Biomarkers

Preeclampsia is a common and important complication of pregnancy, one with potentially significant morbidity and even mortality to both mother and baby. Identifying those at high risk of developing the condition is helpful as there is evidence that the incidence of preeclampsia can be reduced with low dose aspirin taken in pregnancy. Accurately predicting the risk of preeclampsia allows for more targeted aspirin prophylaxis and a greater opportunity for early detection of maternal and/or fetal complications associated with impaired placentation through a schedule of enhanced antenatal surveillance. Traditional preeclampsia prediction models use maternal characteristics and risk factors and have been shown to be of low predictive value. Multiparametric screening tests combine patient characteristics with serum biomarkers and ultrasound Doppler indices and have been shown to be more effective at detecting those at high risk of preeclampsia - more specifically, early-onset preeclampsia (onset of preeclampsia <34 weeks' gestation). Multiparametric screening has now been validated in different populations. The true cost effectiveness of a multiparametric screening model for preeclampsia screening is not yet fully known and will vary depending on the clinical setting. Despite the growing body of evidence for its improved detection rates, first trimester preeclampsia screening using multiparametric models is not widely implemented and is not part of the recommendations for antenatal screening from most international bodies. The International Federation of Gynecology and Obstetrics has advised universal preeclampsia screening using maternal risk factors and biomarkers and has strongly encouraged its promotion worldwide. Various barriers to implementation must be considered such as the immediate cost of equipment and training, the need for audit and quality control, and the expected benefit to the population. Low to middle income settings may require a pragmatic approach to the implementation of multiparametric screening given limited resources.

Factors Associated with the Severity of Pregnancy-Related Hypertensive Disorder: Significance of Clinical, Laboratory, and Histopathological Features

The purpose of this paper is to evaluate the association of maternal clinical and laboratory features and placental histopathological changes with disease severity in pregnancy-related hypertensive disorders. From January 2021 to December 2021, clinical and laboratory data at the time of delivery and histopathological features of the placenta were collected from pregnant women with pregnancy-related hypertensive disorders at a single institution. The women were classified according to the pregnancy-related hypertensive disorder clinical severity, and each variable was compared accordingly. Gestational age-matched normotensive groups were also compared. Univariate and multivariate regression analyses were used to identify factors influencing pregnancy-related hypertensive disorder severity. Fifty-eight pregnancies were analyzed. Maternal albumin levels before delivery (beta coefficient −0.83, p = 0.043) and increased placental syncytial knots (beta coefficient 0.71, p = 0.026) are important parameters that are closely related to disease severity in women with pregnancy-related hypertensive disorders. The combination of albumin, PAPP-A, total bilirubin, and eGFR levels appears to be optimal for predicting pregnancy-related hypertensive disorder severity.

Competing-risks model for pre-eclampsia and adverse pregnancy outcomes

OBJECTIVE

The competing-risks model for assessment of risk for pre-eclampsia (PE) at 35-37 weeks' gestation identifies the majority of women who are at high risk of subsequent delivery with PE. We aimed to examine the incidence and relative risk of adverse pregnancy outcomes in patient groups stratified according to the estimated risk of delivery with PE.

METHODS

This was a prospective non-interventional, observational study in women with a singleton pregnancy attending for a routine hospital visit at 35 + 0 to 36 + 6 weeks' gestation. The risk of delivery with PE for each patient in the study population was estimated using the competing-risks model, combining the prior distribution of gestational age at delivery with PE and the likelihood from multiples of the median values of mean arterial pressure, placental growth factor and soluble fms-like tyrosine kinase-1. The patients were assigned to one of the following five risk categories: Group A, ≥ 1 in 2; Group B, 1 in 5 to 1 in 3; Group C, 1 in 20 to 1 in 6; Group D, 1 in 50 to 1 in 21; and Group E, < 1 in 50. The outcome measures were delivery with PE, gestational hypertension (GH), small-for-gestational age (SGA) at birth, delivery by Cesarean section, stillbirth, neonatal death, perinatal death and admission to the neonatal unit (NNU) for at least 48 h. In each risk category, the proportion of women with each adverse outcome was determined and relative risks (RR) were calculated as compared with the lowest-risk Group E.

RESULTS

In the study population of 29 035 women, 1.6%, 2.7%, 8.2%, 9.8% and 77.8% were categorized into Groups A, B, C, D and E, respectively. Compared with women in Group E, women in the higher-risk groups were more likely to have an adverse outcome. The RR of delivery with PE in Group A compared with Group E was 65.5 (95% CI, 54.1-79.1) and the respective values were 11.9 (95% CI, 9.1-15.5) for GH, 1.8 (95% CI, 1.5-2.1) for delivery by emergency Cesarean section, 1.5 (95% CI, 1.2-1.8) for delivery by elective Cesarean section, 8.9 (95% CI, 7.4-10.8) for SGA with birth weight < 3^rd percentile, 4.8 (95% CI, 4.3-5.4) for SGA with birth weight < 10^th percentile, 5.3 (95% CI, 1.4-20.5) for stillbirth and 3.4 (95% CI, 2.8-4.2) for NNU admission for ≥ 48 h. The RR for these pregnancy complications in higher-risk groups (vs Group E) was particularly high for cases with delivery within 2 weeks after assessment. In terms of SGA, both for birth weight < 10^th and < 3^rd percentiles, the trend in all cases was stronger than that observed when the analysis was confined to normotensive pregnancies. The rates of neonatal death were too small to allow meaningful comparisons between risk groups.

CONCLUSION

Pregnant women identified by the competing-risks model to be at high risk of PE are also at increased risk of GH, Cesarean section, stillbirth, SGA and NNU admission for ≥ 48 h. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Development of a prediction model on preeclampsia using machine learning-based method: a retrospective cohort study in China

Objective: The aim of this study was to use machine learning methods to analyze all available clinical and laboratory data obtained during prenatal screening in early pregnancy to develop predictive models in preeclampsia (PE).

Material and Methods: Data were collected by retrospective medical records review. This study used 5 machine learning algorithms to predict the PE: deep neural network (DNN), logistic regression (LR), support vector machine (SVM), decision tree (DT), and random forest (RF). Our model incorporated 18 variables including maternal characteristics, medical history, prenatal laboratory results, and ultrasound results. The area under the receiver operating curve (AUROC), calibration and discrimination were evaluated by cross-validation.

Results: Compared with other prediction algorithms, the RF model showed the highest accuracy rate. The AUROC of RF model was 0.86 (95% CI 0.80–0.92), the accuracy was 0.74 (95% CI 0.74–0.75), the precision was 0.82 (95% CI 0.79–0.84), the recall rate was 0.42 (95% CI 0.41–0.44), and Brier score was 0.17 (95% CI 0.17–0.17).

Conclusion: The machine learning method in our study automatically identified a set of important predictive features, and produced high predictive performance on the risk of PE from the early pregnancy information.

Impact of replacing or adding pregnancy-associated plasma protein-A at 11-13 weeks on screening for preterm pre-eclampsia

OBJECTIVE

To assess whether pregnancy-associated plasma protein-A (PAPP-A) alters or provides equivalent screening performance as placental growth factor (PlGF) when screening for preterm pre-eclampsia (PE) at 11-13 weeks of gestation.

METHODS

This was a secondary analysis of a non-intervention screening study of 6546 singleton pregnancies that were screened prospectively for preterm PE in the first trimester between December 2016 and June 2018. Patient-specific risks for preterm PE were estimated by maternal history, mean arterial pressure (MAP), uterine artery pulsatility index (UtA-PI), PlGF and PAPP-A. A competing-risks model with biomarkers expressed as multiples of the median was used. All women and clinicians were blinded to the risk for preterm PE. The performance of screening for preterm PE using PlGF vs PAPP-A vs both PAPP-A and PlGF was assessed by comparing areas under the receiver-operating-characteristics (AUC) curves. McNemar's test was used to compare detection rate at a fixed false-positive rate (FPR) of 10%.

RESULTS

PlGF and PAPP-A were measured in 6546 women, of whom 37 developed preterm PE. The AUC and detection rate at 10% FPR using PlGF in combination with maternal history, MAP and UtA-PI were 0.854 and 59.46%, respectively. The respective values were 0.813 and 51.35% when replacing PlGF with PAPP-A and 0.855 and 59.46% when using both PAPP-A and PlGF. Statistically non-significant differences were noted in AUC when replacing PlGF with PAPP-A (ΔAUC, 0.04; P = 0.095) and when using both PAPP-A and PlGF (ΔAUC, 0.002; P = 0.423). However, on an individual case basis, screening using PlGF in conjunction with maternal history, MAP and UtA-PI identified three (8.1%) additional pregnancies that developed preterm PE and that were not identified when replacing PlGF with PAPP-A. Screening using PAPP-A in addition to maternal history and other biomarkers did not identify any additional pregnancies.

CONCLUSION

On an individual case basis, adoption of a screening strategy that uses PAPP-A instead of PlGF results in reduced detection of preterm PE, consistent with previous literature. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Preventing Stillbirth: A Review of Screening and Prevention Strategies

Stillbirth is a devastating pregnancy complication that still affects many women, particularly from low and middle-income countries. It is often labeled as "unexplained" and therefore unpreventable, despite the knowledge that placental dysfunction has been identified as a leading cause of antepartum stillbirth. Currently, screening for pregnancies at high-risk for placental dysfunction relies on checklists of maternal risk factors and serial measurement of symphyseal-fundal height to identify small for gestational age fetuses. More recently, the first-trimester combined screening algorithm developed by the Fetal Medicine Foundation has emerged as a better tool to predict and prevent early-onset placental dysfunction and its main outcomes of preterm preeclampsia, fetal growth restriction and stillbirth by the appropriate use of Aspirin therapy, serial growth scans and induction of labour from 40 weeks for women identified at high-risk by such screening. There is currently no equivalent to predict and prevent late-onset placental dysfunction, although algorithms combining an ultrasound-based estimation of fetal weight, assessment of maternal and fetal Doppler indices, and maternal serum biomarkers show promise as emerging new screening tools to optimize pregnancy monitoring and timing of delivery to prevent stillbirth. In this review we discuss the strategies to predict and prevent stillbirths based on first-trimester screening as well as fetal growth and wellbeing assessment in the second and third trimesters.

Cost-effectiveness analysis of implementing screening on preterm pre-eclampsia at first trimester of pregnancy in Germany and Switzerland

Objective

To assess the cost-effectiveness of preterm preeclampsia (PE) screening versus routine screening based on maternal characteristics in Germany and Switzerland.

Methods

A health economic model was used to analyse the cost-effectiveness of PE screening versus routine screening based on maternal characteristics. The analysis was conducted from the healthcare perspective with a time horizon of one year from the start of pregnancy. The main outcome measures were incremental health care costs and incremental costs per PE case averted.

Results

The incremental health care costs for PE screening versus routine screening per woman were €14 in Germany, and -CHF42 in Switzerland, the latter representing cost savings. In Germany, the incremental costs per PE case averted were €3,795. In Switzerland, PE screening was dominant. The most influential parameter in the one-way sensitivity analysis was the cost of PE screening (Germany) and the probability of preterm PE in routine screening (Switzerland). In Germany, at a willingness-to-pay for one PE case avoided of €4,200, PE screening had a probability of more than 50% of being cost-effective compared to routine screening. In Switzerland, at a willingness-to-pay of CHF0, PE screening had a 78% probability of being the most cost-effective screening strategy.

Conclusion

For Switzerland, PE screening is expected to be cost saving in comparison to routine screening. For Germany, the additional health care costs per woman were expected to be €14. Future cost-effectiveness studies should be conducted with a longer time horizon.

First trimester screening for gestational diabetes mellitus with maternal factors and biomarkers

Introduction: This study aimed to identify risk factors among maternal characteristics, obstetric history and first trimester preeclampsia-specific biomarkers that were associated with subsequent development of gestational diabetes mellitus (GDM) and evaluate the performance of the prediction models. Methods: Secondary analysis of a prospective cohort study. The performance of the prediction models was assessed by area under receiver operating characteristic curve (AUROC). Results: A total of 837 (8.9%) cases of GDM and 8535 (91.1%) unaffected cases were included. The AUROC of the prediction model combining maternal characteristics and obstetric history (0.735) was better than that of the model utilizing maternal characteristics (AUROC 0.708) and preeclampsia-specific biomarkers (AUROC 0.566). Amongst the preeclampsia-specific biomarkers, the mean arterial pressure (MAP) contributed to the increasing risk of GDM, however, its addition did not improve the AUROC of the model combining maternal characteristics and obstetric history (0.738). Conclusion: The first trimester prediction model for GDM with maternal characteristics and obstetric history achieves moderate predictability. The inclusion of MAP in the model combining maternal characteristics and obstetric history does not improve the screening performance for GDM. Future studies are needed to explore the effect of blood pressure control from early pregnancy on preventing GDM.

Ophthalmic artery Doppler at 11-13 weeks' gestation in prediction of pre-eclampsia

OBJECTIVES

To examine the potential value of maternal ophthalmic artery Doppler at 11-13 weeks' gestation, alone and in combination with the established first-trimester biomarkers of pre-eclampsia (PE), including uterine artery pulsatility index (UtA-PI), mean arterial pressure (MAP), serum placental growth factor (PlGF) and serum pregnancy-associated plasma protein-A (PAPP-A), in the prediction of subsequent development of PE.

METHODS

This was a prospective observational study in women attending for a routine hospital visit at 11 + 0 to 13 + 6 weeks' gestation. This visit included recording of maternal demographic characteristics and medical history, ultrasound examination for fetal anatomy and growth, assessment of flow velocity waveforms from the maternal ophthalmic arteries and calculation of the second-to-first peak systolic velocity (PSV) ratio, and measurement of MAP and serum PAPP-A. In addition, a case-control study was carried out for measurement of PlGF in stored samples from cases that developed PE and unaffected controls. The values of PSV ratio, UtA-PI, MAP, PAPP-A and PlGF were converted to multiples of the median or deltas to remove the effects of maternal characteristics and medical history. The competing-risks model was used to estimate the individual patient-specific risk of delivery with PE at < 37 and < 41 + 3 weeks' gestation for various combinations of markers. Performance was assessed using detection rates, at a fixed false-positive rate (FPR), and areas under the receiver-operating-characteristics curves. Modeled performance was also assessed.

RESULTS

The study population of 4066 pregnancies contained 114 (2.8%) that developed PE, including 25 (0.6%) that delivered with PE at < 37 weeks' gestation. The PSV ratio was significantly increased in PE pregnancies, and the effect of PE depended on gestational age at delivery, with the deviation from normal being greater for early than for late PE. Modeling demonstrated that the addition of PSV ratio improved the detection rate, at a 10% FPR, of preterm PE provided by maternal risk factors alone (from 46.3% to 58.4%), maternal factors, MAP and UtA-PI (65.9% to 70.6%), and maternal factors, MAP, UtA-PI and PlGF (74.6% to 76.7%). The PSV ratio did not improve the prediction of term PE provided by any combination of biomarkers.

CONCLUSION

Ophthalmic artery PSV ratio at 11-13 weeks' gestation is a potentially useful biomarker for prediction of subsequent development of preterm PE, but larger studies are needed to validate this finding. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

First-trimester prediction model for placental vascular disorders: An observational prospective study

This study aims to develop a multivariable predictive model for the risk of placental vascular complications (PVC), by using biochemical, biophysical, anamnestic and clinical maternal features available at the first trimester. PVC include gestational hypertension, preeclampsia, placenta abruption, intrauterine growth restriction (IUGR), and stillbirth. Prospective study that included all singleton pregnancies attending the first-trimester aneuploidy screening (11 +0-12 +6 weeks) at Obstetrics Unit of the University Hospital of Modena, in Northern Italy, between June 2018 and December 2019. In a total of 503 women included in the analysis, 40 patients were in the PVC group. The final prediction model for PVC included the following independent variables: pre-pregnancy BMI ≥ 30 (OR = 2.65, 95% CI = 1.04; 6.75, p = 0.0415), increasing values of mean arterial pressure (OR = 1.06, 95% CI = 1.02; 1.10, p = 0.0008), PAPP-A < 2.40465 U/L (OR = 0.43, 95% CI = 0.19; 0.96, p = 0.0388) and decreasing values of PlGf (MoM) (OR = 0.28, 95% CI = 0.10; 0.79, p = 0.0153). The area under the ROC curve was 79.4% indicating a satisfactory predictive accuracy. The best predictive cut-off for this score was equal to -2.562, which corresponds to a 7.2 % probability of having PVC. By using such a cut-off, the risk of PVC can be predicted in our sample with sensitivity equal to 82,4 % and specificity equal to 69,9 %. This model for early prediction of PVC is a promising tool to early identify women at greater risk for placenta vascular complications.

Preeclampsia: state of art and future perspectives. A special focus on possible preventions

Preeclampsia (PE) is characterised by the new onset of hypertension after the 20th week of pregnancy, with or without proteinuria or hypertension that leads to end-organ dysfunction. Since the only definitive treatment is delivery, PE still represents one of the leading causes of preterm birth and perinatal mobility and mortality. Therefore, any strategies that aim to reduce adverse outcomes are based on early primary prevention, prenatal surveillance and prophylactic interventions. In the last decade, intense research has been focussed on the study of predictive models in order to identify women at higher risk accurately. To date, the most effective screening model is based on the combination of anamnestic, demographic, biophysical and maternal biochemical factors. In this review, we provide a detailed discussion about the current and future perspectives in the field of PE. We will examine pathogenesis, risk factors and clinical features. Moreover, recent developments in screening and prevention strategies, novel therapies and healthcare management strategies will be discussed.

Early cost-effectiveness analysis of screening for preeclampsia in nulliparous women: A modelling approach in European high-income settings

Background

Preeclampsia causes substantial maternal and perinatal morbidity and mortality and significant societal economic impact. Effective screening would facilitate timely and appropriate prevention and management of preeclampsia.

Objectives

To develop an early cost-effectiveness analysis to assess both costs and health outcomes of a new screening test for preeclampsia from a healthcare payer perspective, in the United Kingdom (UK), Ireland, the Netherlands and Sweden.

Methods

A decision tree over a 9-month time horizon was developed to explore the cost-effectiveness of the new screening test for preeclampsia compared to the current screening strategy. The new test strategy is being developed so that it can stratify healthy low risk nulliparous women early in pregnancy to either a high-risk group with a risk of 1 in 6 or more of developing preeclampsia, or a low-risk group with a risk of 1 in 100 or less. The model simulated 25 plausible scenarios in a hypothetical cohort of 100,000 pregnant women, in which the sensitivity and specificity of the new test were varied to set a benchmark for the minimum test performance that is needed for the test to become cost-effective. The input parameters and costs were mainly derived from published literature. The main outcome was incremental costs per preeclampsia case averted, expressed as an incremental cost-effectiveness ratio (ICER). Deterministic and probabilistic sensitivity analyses were conducted to assess uncertainty.

Results

Base case results showed that the new test strategy would be more effective and less costly compared to the current situation in the UK. In the Netherlands, the majority of scenarios would be cost-effective from a threshold of €50,000 per preeclampsia case averted, while in Ireland and Sweden, the vast majority of scenarios would be considered cost-effective only when a threshold of €100,000 was used. In the best case analyses, ICERs were more favourable in all four participating countries. Aspirin effectiveness, prevalence of preeclampsia, accuracy of the new screening test and cost of regular antenatal care were identified as driving factors for the cost-effectiveness of screening for preeclampsia.

Conclusion

The results indicate that the new screening test for preeclampsia has potential to be cost-effective. Further studies based on proven accuracy of the test will confirm whether the new screening test is a cost-effective additional option to the current situation.

Endometriosis and Impaired Placentation: A Prospective Cohort Study Comparing Uterine Arteries Doppler Pulsatility Index in Pregnancies of Patients with and without Moderate-Severe Disease

The aim of this study was to evaluate if moderate-severe endometriosis impairs uterine arteries pulsatility index (UtA-PI) during pregnancy when compared to unaffected controls. In this prospective cohort study, pregnant women with stage III-IV endometriosis according to the revised American Fertility Society (r-AFS) classification were matched for body mass index and parity in a 1:2 ratio with unaffected controls. UtA-PIs were assessed at 11-14, 19-22 and 26-34 weeks of gestation following major reference guidelines. A General Linear Model (GLM) was implemented to evaluate the association between endometriosis and UtA-PI Z-scores. Significantly higher third trimester UtA-PI Z-scores were observed in patients with r-AFS stage III-IV endometriosis when compared to controls (p = 0.024). In the GLM, endometriosis (p = 0.026) and maternal age (p = 0.007) were associated with increased third trimester UtA-PI Z-scores, whereas conception by in-vitro fertilization with frozen-thawed embryo transfer significantly decreased UtA-PI measures (p = 0.011). According to these results, r-AFS stage III-IV endometriosis is associated with a clinically measurable impaired late placental perfusion. Closer follow-up may be recommended in pregnant patients affected by moderate-severe endometriosis in order to attempt prediction and prevention of adverse pregnancy and perinatal outcomes due to a defective late placental perfusion.

First-Trimester Fetal Hepatic Artery Examination for Adverse Outcome Prediction

Objective: To assess whether there are differences in first-trimester fetal hepatic artery flows depending on pregnancy outcomes. Methods: The prospective study conducted in 2012–2020 included 1841 fetuses from singleton pregnancies assessed during the routine first-trimester ultrasound examination (between 11- and 14-weeks’ gestation). Also, each fetus was examined to determine their hepatic artery flows by measuring the artery’s pulsatility index (HA-PI) and peak systolic velocity (HA-PSV). Results: The fetuses that were classified as belonging to the adverse pregnancy outcome group (those with karyotype abnormalities and congenital heart defects) were characterized by a significantly lower HA-PI and higher HA-PSV compared to normal outcome fetuses. Conclusion: Hepatic artery flow assessment proved to be a very useful tool in predicting adverse pregnancy outcomes, in particular karyotype abnormalities and congenital heart defects.

Effectiveness of Different Algorithms and Cut-off Value in Preeclampsia First Trimester Screening

Results

For the cut-off point >1 : 150, 86 women at an increased risk of eo-PE using algorithm 1 were identified. Of these 86 patients, 83 (96%) were identified using algorithm 2, 62 (72%) using algorithm 3, and 60 (69%) using algorithm 4. In addition, it was demonstrated that between 21% and 29% of women at a low risk of eo-PE could be given acetylsalicylic acid if a screening test was used that did not account for PlGF.

Conclusions

In order to provide the highest level of health care to pregnant women, it is extremely important that full screening for eo-PE should be ensured. The cheapest algorithm based only on MAP and UtPI resulted in our patients being unnecessarily exposed to complications.

First Trimester Prediction of Preterm Delivery in the Absence of Other Pregnancy-Related Complications Using Cardiovascular-Disease Associated MicroRNA Biomarkers

The aim of the study was to determine if aberrant expression profile of cardiovascular disease associated microRNAs would be able to predict within 10 to 13 weeks of gestation preterm delivery such as spontaneous preterm birth (PTB) or preterm prelabor rupture of membranes (PPROM) in the absence of other pregnancy-related complications (gestational hypertension, preeclampsia, fetal growth restriction, or small for gestational age). In addition, we assessed if aberrant expression profile of cardiovascular disease associated microRNAs would be able to predict preterm delivery before and after 34 weeks of gestation. The retrospective study was performed within the period November 2012 to March 2020. Whole peripheral blood samples were collected from 6440 Caucasian individuals involving 41 PTB and 65 PPROM singleton pregnancies. A control group, 80 singleton term pregnancies, was selected on the base of equal sample storage time. Gene expression of 29 selected cardiovascular disease associated microRNAs was studied using real-time RT-PCR. Downregulation of miR-16-5p, miR-20b-5p, miR-21-5p, miR-24-3p, miR-26a-5p, miR-92a-3p, miR-126-3p, miR-133a-3p, miR-145-5p, miR-146a-5p, miR-155-5p, miR-210-3p, miR-221-3p and miR-342-3p was observed in pregnancies with preterm delivery before 37 (≤36 + 6/7) weeks of gestation. Majority of downregulated microRNAs (miR-16-5p, miR-24-3p, miR-26a-5p, miR-92a-3p, miR-133a-3p, miR-145-5p, miR-146a-5p, miR-155-5p, miR-210-3p, and miR-342-3p) was associated with preterm delivery occurring before 37 (≤36 + 6/7) weeks of gestation. The only miR-210-3p was downregulated in pregnancies with preterm delivery before 34 (≤33 + 6/7) weeks of gestation. The type of preterm delivery also had impact on microRNA gene expression profile. Downregulation of miR-24-3p, miR-92a-3p, miR-155-5p, and miR-210-3p was a common feature of PTB and PPROM pregnancies. Downregulation of miR-16-5p, miR-20b-5p, miR-26a-5p, miR-126-3p, miR-133a-3p, miR-146a-5p, miR-221-3p, and miR-342-3p appeared just in PTB pregnancies. No microRNA was uniquely dysregulated in PPROM pregnancies. The combination of 12 microRNAs (miR-16-5p, miR-20b-5p, miR-21-5p, miR-24-3p, miR-26a-5p, miR-92a-3p, miR-133a-3p, miR-145-5p, miR-146a-5p, miR-155-5p, miR-210-3p, and miR-342-3p, AUC 0.818, p < 0.001, 74.53% sensitivity, 75.00% specificity, cut off > 0.634) equally as the combination of 6 microRNAs (miR-16-5p, miR-21-5p, miR-24-3p, miR-133a-3p, miR-155-5p, and miR-210-3p, AUC 0.812, p < 0.001, 70.75% sensitivity, 78.75% specificity, cut off > 0.652) can predict preterm delivery before 37 weeks of gestation in early stages of gestation in 52.83% pregnancies at 10.0% FPR. Cardiovascular disease associated microRNAs represent promising biomarkers with very good diagnostical potential to be implemented into the current routine first trimester screening programme to predict preterm delivery.

First-Trimester Screening for Fetal Growth Restriction and Small-for-Gestational-Age Pregnancies without Preeclampsia Using Cardiovascular Disease-Associated MicroRNA Biomarkers

The goal of the study was to determine the early diagnostical potential of cardiovascular disease-associated microRNAs for prediction of small-for-gestational-age (SGA) and fetal growth restriction (FGR) without preeclampsia (PE). The whole peripheral venous blood samples were collected within 10 to 13 weeks of gestation from singleton Caucasian pregnancies within the period November 2012 to March 2020. The case-control retrospective study, nested in a cohort, involved all pregnancies diagnosed with SGA (n = 37) or FGR (n = 82) without PE and 80 appropriate-for-gestational age (AGA) pregnancies selected with regard to equality of sample storage time. Gene expression of 29 cardiovascular disease-associated microRNAs was assessed using real-time RT-PCR. Upregulation of miR-16-5p, miR-20a-5p, miR-146a-5p, miR-155-5p, miR-181a-5p, and miR-195-5p was observed in SGA or FGR pregnancies at 10.0% false positive rate (FPR). Upregulation of miR-1-3p, miR-20b-5p, miR-126-3p, miR-130b-3p, and miR-499a-5p was observed in SGA pregnancies only at 10.0% FPR. Upregulation of miR-145-5p, miR-342-3p, and miR-574-3p was detected in FGR pregnancies at 10.0% FPR. The combination of four microRNA biomarkers (miR-1-3p, miR-20a-5p, miR-146a-5p, and miR-181a-5p) was able to identify 75.68% SGA pregnancies at 10.0% FPR in early stages of gestation. The detection rate of SGA pregnancies without PE increased 4.67-fold (75.68% vs. 16.22%) when compared with the routine first-trimester screening for PE and/or FGR based on the criteria of the Fetal Medicine Foundation. The combination of seven microRNA biomarkers (miR-16-5p, miR-20a-5p, miR-145-5p, miR-146a-5p, miR-181a-5p, miR-342-3p, and miR-574-3p) was able to identify 42.68% FGR pregnancies at 10.0% FPR in early stages of gestation. The detection rate of FGR pregnancies without PE increased 1.52-fold (42.68% vs. 28.05%) when compared with the routine first-trimester screening for PE and/or FGR based on the criteria of the Fetal Medicine Foundation. Cardiovascular disease-associated microRNAs represent promising early biomarkers with very suitable predictive potential for SGA or FGR without PE to be implemented into the routine screening programs.

Preeclampsia and Cerebral Palsy in Offspring

The aim of this systematic review and meta-analysis is to examine the association between exposure to preeclampsia during pregnancy and the occurrence of cerebral palsy in offspring. For this reason, the authors searched PubMed/Medline, EMBASE, and Google Scholar databases (end-of-search: 22 November 2021) and identified the most relevant studies. Then, a meta-analysis of all the eligible studies was performed. Subgroup and meta-regression analyses by study design, degree of adjustment, and geographical region were also conducted. A total of 10 studies were finally included, and no statistical significance was noted in the association between preeclampsia and cerebral palsy (pooled OR = 1.16, 95% CI: 0.77–1.74). The subgroup of studies that provided adjusted odds ratios for any variable except for gestational age showed a statistically significant association (pooled OR = 1.62, 95% CI: 1.36–1.93), whereas the association dissipated in studies also adjusting for gestational age (pooled OR = 1.63, 95% CI: 0.48–5.50). In conclusion, it seems that preeclampsia is not associated with cerebral palsy independently of gestational age; however, further research is needed to shed light on this topic.

Estimated fetal weight at mid-gestation in prediction of pre-eclampsia in singleton pregnancy

OBJECTIVE

To examine the distribution of birth weight according to gestational age in pregnancies complicated by pre-eclampsia (PE) and assess the potential value of sonographic estimated fetal weight (EFW) at mid-gestation as a predictor of PE.

METHODS

The data for this study were derived from prospective screening for adverse obstetric outcome in 93 911 women with a singleton pregnancy attending for routine pregnancy care at 19 + 0 to 24 + 6 weeks' gestation in two UK maternity hospitals. This visit included recording of maternal demographic characteristics and medical history, sonographic EFW and measurement of mean arterial pressure (MAP) and uterine artery pulsatility index (UtA-PI). The distribution of birth weight of pregnancies with and those without PE was assessed. The competing-risks model was used to estimate the individual, patient-specific risk of delivery with PE at < 32 and < 37 weeks' gestation and at any gestational age. The areas under the receiver-operating-characteristics curves and detection rates (DRs) of delivery with PE, at a 10% false-positive rate (FPR), were assessed for various combinations of maternal risk factors, EFW, MAP and UtA-PI. McNemar's test was used to determine the significance of difference in DR at a 10% FPR between screening with vs without EFW.

RESULTS

The study population contained 2843 (3.0%) pregnancies that subsequently developed PE, including 148 (0.2%) that delivered with PE at < 32 weeks' gestation and 654 (0.7%) that delivered with PE at < 37 weeks. Birth weight was < 10^th percentile in 82% of pregnancies with PE delivering at < 32 weeks' gestation and this decreased to 21% of those with PE delivering at ≥ 37 weeks. In screening for delivery with PE at < 32 and < 37 weeks' gestation, the DR, at a 10% FPR, achieved by maternal risk factors (51% and 46%, respectively) was improved by addition of EFW (69% and 51%, respectively). Similarly, addition of EFW improved the performance of screening by a combination of maternal risk factors and MAP from 72% to 80% for PE < 32 weeks and from 57% to 60% for PE < 37 weeks. EFW did not improve the predictive performance of screening by a combination of maternal risk factors, MAP and UtA-PI.

CONCLUSIONS

In pregnancies complicated by preterm PE, a high proportion of neonates are small-for-gestational age, and sonographic EFW at mid-gestation can improve the prediction of early and preterm PE provided by maternal risk factors and MAP but not the prediction provided by a combination of maternal risk factors, MAP and UtA-PI. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

Optimising Cardiometabolic Risk Factors in Pregnancy: A Review of Risk Prediction Models Targeting Gestational Diabetes and Hypertensive Disorders

Cardiovascular disease, especially coronary heart disease and cerebrovascular disease, is a leading cause of mortality and morbidity in women globally. The development of cardiometabolic conditions in pregnancy, such as gestational diabetes mellitus and hypertensive disorders of pregnancy, portend an increased risk of future cardiovascular disease in women. Pregnancy therefore represents a unique opportunity to detect and manage risk factors, prior to the development of cardiovascular sequelae. Risk prediction models for gestational diabetes mellitus and hypertensive disorders of pregnancy can help identify at-risk women in early pregnancy, allowing timely intervention to mitigate both short- and long-term adverse outcomes. In this narrative review, we outline the shared pathophysiological pathways for gestational diabetes mellitus and hypertensive disorders of pregnancy, summarise contemporary risk prediction models and candidate predictors for these conditions, and discuss the utility of these models in clinical application.