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

Prediction of pre-eclampsia using maternal hemodynamic parameters at 12 + 0 to 15 + 6 weeks

OBJECTIVES

To compare the maternal hemodynamic profile at 12 + 0 to 15 + 6 weeks' gestation in women who subsequently developed pre-eclampsia (PE) and those who did not, and to assess the screening performance of maternal hemodynamic parameters for PE in combination with the Fetal Medicine Foundation (FMF) triple test, including maternal factors (MF), mean arterial pressure (MAP), uterine artery pulsatility index and placental growth factor.

METHODS

This was a prospective case-control study involving Chinese women with a singleton pregnancy who underwent preterm PE screening at 11 + 0 to 13 + 6 weeks' gestation using the FMF triple test, between February 2020 and February 2023. Women identified as being at high risk (≥ 1:100) for preterm PE by the FMF triple test were matched 1:1 with women identified as low risk (< 1:100) for maternal age ± 3 years, maternal weight ± 5 kg and date of screening ± 14 days. Two-dimensional transthoracic echocardiography was performed at 12 + 0 to 15 + 6 weeks to evaluate maternal hemodynamic parameters (heart rate (HR), stroke volume (SV), cardiac output (CO) and systemic vascular resistance (SVR)). Maternal hemodynamic parameters were expressed as multiples of the median (MoM) values, determined by linear regression models to adjust for gestational age (GA) and MF. The distribution of log10 MoM values of maternal hemodynamic parameters in cases of PE and unaffected pregnancies, and the association between these hemodynamic parameters and GA at delivery, were assessed. The risks of preterm PE (delivery before 37 weeks) and any-onset PE (delivery at any time) were reassessed using Bayes' theorem after maternal hemodynamic parameters were added to the FMF triple test. The screening performance for preterm PE and any-onset PE was determined by the area under the receiver-operating-characteristics curve (AUC) and detection rate at a 10% fixed false-positive rate (FPR). Differences in AUC (ΔAUC) were assessed using DeLong's test.

RESULTS

A total of 743 cases were analyzed, of whom 39 (5.2%) subsequently developed PE, including 29 (3.9%) cases of preterm PE and 10 (1.3%) cases of term PE. Mean log10 SVR MoM was significantly higher in cases of preterm PE and any-onset PE compared with unaffected pregnancies. Mean log10 SV MoM and log10 CO MoM were significantly lower in cases of preterm PE and any-onset PE compared with unaffected pregnancies. Mean log10 HR MoM was not significantly different between the study groups. Mean log10 CO MoM and log10 SVR MoM were not significantly correlated with GA at delivery in preterm PE and any-onset PE. For the prediction of preterm PE and any-onset PE, adding CO or SVR or replacing MAP with CO and SVR in the FMF triple test achieved an identical or greater AUC compared with the FMF triple test, but ΔAUC was not significantly different. In addition, adding CO or SVR or replacing MAP by CO and SVR in the FMF triple test did not improve the detection rate for preterm PE and any-onset PE at a fixed FPR of 10%.

CONCLUSIONS

Women with preterm PE or any-onset PE exhibited increased SVR and decreased CO before the clinical manifestations of PE became apparent. These changes may serve as early indicators of cardiovascular maladaptation. However, assessment of maternal hemodynamics at 12 + 0 to 15 + 6 weeks does not enhance the screening performance for preterm PE and any-onset PE of these parameters. The FMF triple test remains superior to other biomarker combinations for predicting PE. © 2025 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Risk and decision-making: Communication between health professionals and pregnant women at risk of preeclampsia in Catalonia

The biomedical model of attention focuses on preventive risk assessment to mitigate the apparition of future diseases. In the event of a pregnancy classified "at risk" of preeclampsia, screening undertaken in first-term ultrasound controls determines which patients receive preventive treatment. This article examines women's narratives on the communication dynamics with health professionals by drawing on an eight-month ethnographic fieldwork, between 2022 and 2023, in a Barcelona hospital's obstetrics department and 24 semi-structured interviews with women in the postpartum period. The participants of this study had been classified at high risk of developing preeclampsia, which is determined through a screening undertaken during the first trimester of pregnancy, or had a diagnosis of preeclampsia. The results suggest that risk classification significantly impacts the decision-making process and the technical parameters. As we contend, participants experienced difficulties receiving quality information and communicating with professionals, making shared decision-making challenging. As we conclude, doctor-patient dialogue and shared decisions are increasingly replaced by institutional protocols where patients feel their knowledge and experiences have little room.

A review of ethnic disparities in preeclampsia

PURPOSE OF REVIEW

Recent reports have reiterated the inequities in maternal morbidity and mortality for minority ethnic groups, with preeclampsia being a significant concern. Females of Black and South Asian ethnicity have an increased risk of preeclampsia with disproportionately higher adverse outcomes compared to white females.

RECENT FINDINGS

This review will explore ethnic disparities in preeclampsia outcomes, prediction, diagnosis, prevention and management. Recent evidence has demonstrated that biochemical and biophysical markers that are used for preeclampsia prediction and diagnosis vary for females of different ethnic groups. This needs careful consideration given the current need for accurate prediction models. Furthermore, recent reports have highlighted the disparity in maternal morbidity for those of minority ethnic groups. The reasons for this are multifactorial but underlying biases and racism have been attributed as major contributors to poor care and adverse outcomes.

SUMMARY

Exploring disparities in preeclampsia care is essential to address ethnic inequities that lead to increased adverse outcomes. We must alter current clinical practice to break down the barriers that result in substandard care for females from minority ethnic backgrounds.

Development and validation of the placenta-QUS model for the detection of placenta-mediated diseases using quantitative ultrasound measurements: An Ex Vivo proof-of-concept study

INTRODUCTION

Placenta-mediated diseases are associated with structural changes in the placenta. Quantitative Ultrasound (QUS) imaging measures the acoustic properties of the tissue, which are correlated to the underlying tissue structure. We aimed to develop and validate a diagnostic prediction model using QUS measurements for pre-eclampsia (PE) and small-for-gestational-age (SGA) fetuses/neonates.

METHODS

For this prospective case-control study, placentas were collected from a group of women who delivered via cesarean section at BC Women's Hospital, Vancouver, Canada. Ultrasound data were collected and processed to compute three QUS parameters, namely, attenuation coefficient estimate (ACE), integrated backscatter coefficient (IBC), and effective scatterer diameter (ESD) from the placentas. We developed a logistic regression model using QUS parameters as predictors. The primary outcome was the occurrence of SGA and PE.

RESULTS

The dataset consisted of 47 placentas, of which 25 placentas were complicated by SGA/PE. The final placenta-QUS model included quadratic and interaction terms of ACE, IBC, and ESD parameters. The placenta-QUS model was well-calibrated, with a calibration slope of 0.99 (0.57-1.05) and a calibration intercept of 0.003 (-0.02 - 0.22). The model predicted the SGA/PE complicated pregnancies with an apparent Area Under the Receive Operating Characteristic Curve (AUROC) of 0.89 (95 % CI: 0.78-0.98). The optimism-adjusted AUROC was 0.88 (95 % CI: 0.78-0.98).

DISCUSSION

A model for SGA and PE has been developed using QUS measures from the placenta ex vivo. The model showed promising performance in detecting SGA/PE. Future studies will be performed to assess the model performance using QUS measures in utero.

Lateral Flow Assay for Preeclampsia Screening Using DNA Hairpins and Surface-Enhanced Raman-Active Nanoprobes Targeting hsa-miR-17-5p

Preeclampsia (PE) is a serious complication that poses risks to both mothers and their children. This condition is typically asymptomatic until the second or even third trimester, which can lead to poor outcomes and can be costly. Detection is particularly challenging in low- and middle-income countries, where a lack of centralized testing facilities coincides with high rates of PE-related maternal mortality. Variations in the levels of hsa-miR-17-5p have been identified as constituting a potential early indicator for distinguishing between individuals with PE and those without PE during the first trimester. Thus, developing a screening test to measure hsa-miR-17-5p levels would not only facilitate rapid detection in the early stages of pregnancy but also help democratize testing globally. Here, we present a proof-of-principle lateral-flow assay (LFA) designed to measure hsa-miR-17-5p levels using DNA-hairpin recognition elements for enhanced specificity and nanoprobes for sensitive surface-enhanced resonance Raman scattering (SERS) signal transduction. The theoretical limit of detection for hsa-miR-17-5p was 3.84 × 10-4 pg/µL using SERS.

Feasibility of Universal Screening for Preeclampsia Risk and Aspirin Recommendation in the Ultrasound Unit

OBJECTIVE

 To evaluate the feasibility and impact of using the first-trimester ultrasound visit to identify and counsel women at increased risk of preeclampsia about the benefits of low-dose aspirin (LDA) for preventing preeclampsia. We also assessed patient-reported utilization of LDA, perceived risk for preeclampsia, and clinical outcomes.

STUDY DESIGN

 Women presenting for routine first-trimester nuchal-translucency (NT) ultrasounds were screened for clinical preeclampsia risks using a self-administered risk assessment. Women at moderate or high risk for preeclampsia were counseled to take LDA, if not already taking it. LDA utilization and perceived risk for preeclampsia were assessed during the second-trimester ultrasound. Factors associated with LDA utilization were analyzed. Pregnancy outcomes were compared between those who used LDA and those who did not.

RESULTS

 Slightly more than 20% of patients (765/3,669) screened at increased risk for developing preeclampsia. Of those, 67.8% (519/765) had not received LDA recommendations from their referring obstetrician and 97 had not been taking LDA despite being advised to do so. Combined, 94.6% (583/616) of these patients eligible to start LDA prophylaxis received the indicated counseling during the ultrasound visit. A total of 61.4% (358/583) of women completed the follow-up form and of those 77.9% (279/358) reported taking LDA. Screening at increased risk for preeclampsia and perception of increased risk were positively associated with LDA utilization, whereas concerns for LDA safety were negatively associated with use. African American/Black patients and Medicaid recipients were less likely to use LDA. Pregnancy outcomes were similar between those who used LDA and those who did not.

CONCLUSION

 Assessing preeclampsia risk and counseling patients about LDA at the time of the NT ultrasound are feasible in the ultrasound unit and led to good LDA utilization among women at increased risk for preeclampsia. This intervention may standardize patient care and help close the disparity in maternal health.

KEY POINTS

· A simple intervention captured 2/3 of eligible patients.. · Aspirin utilization rate was good after the intervention.. · Screening high risk for preeclampsia and self-perception of risk correlated with aspirin use..

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.

Classification of preeclampsia according to molecular clusters with the goal of achieving personalized prevention

The prevention of pre-eclampsia is difficult due to the syndromic nature and multiple underlying mechanisms of this severe complication of pregnancy. The current clinical distinction between early- and late-onset disease, although clinically useful, does not reflect the true nature and complexity of the pathologic processes leading to pre-eclampsia. The current gaps in knowledge on the heterogeneous molecular pathways of this syndrome and the lack of adequate, specific diagnostic methods are major obstacles to early screening and tailored preventive strategies. The development of novel diagnostic tools for detecting the activation of the identified disease pathways would enable early, accurate screening and personalized preventive therapies. We implemented a holistic approach that includes the utilization of different proteomic profiling methods of maternal plasma samples collected from various ethnic populations and the application of systems biology analysis to plasma proteomic, maternal demographic, clinical characteristic, and placental histopathologic data. This approach enabled the identification of four molecular subclasses of pre-eclampsia in which distinct and shared disease mechanisms are activated. The current review summarizes the results and conclusions from these studies and the research and clinical implications of our findings.

The role of genetics in maternal susceptibility to preeclampsia in women of African ancestry

Racial disparities exist in the prevalence of preeclampsia (PE), with women of African ancestry suffering the highest rates of morbidity and mortality. Genetic changes may play a role in the preponderance of PE among women of African ancestry. This review discusses 30 genes with variants that have been studied in PE in women of African ancestry. These studies found that a single gene is not responsible for PE susceptibility as 13 genes have been implicated. These genes subserve endothelial, immune, hemodynamic, homeostatic, thrombophilic, oxidative stress, and lipid metabolic pathways. Notably, maternal-fetal gene interactions also contribute to the susceptibility of the disease. For instance, the maternal KIR AA genotype and paternally inherited fetal HLA-C2 genotype confer risk for developing PE. Additionally, genetic changes such as epigenetic modulation of expression of the MTHFR gene through DNA methylation is also associated with the occurrence of PE. In contrast, some genes such as the KIR B centromeric region protect against development of PE in some women. The soluble fms-like tyrosine kinase 1 (sFlt-1) contributes to the development of PE and is a potential novel therapeutic option for targeted gene silencing of anti-angiogenic sFLT-1 gene. Additionally, NOS3 gene is an important target for pharmacogenomics because it is responsible for the production of endothelial nitric oxide. In conclusion, maternal genetic and epigenetic variants confer susceptibility to PE, indicating the need for further studies to develop a screening tool incorporating maternal genetic variants to identify women at high risk for PE and offer them a preventive therapy.

Multi-centre deep learning for placenta segmentation in obstetric ultrasound with multi-observer and cross-country generalization

The placenta is crucial to fetal well-being and it plays a significant role in the pathogenesis of hypertensive pregnancy disorders. Moreover, a timely diagnosis of placenta previa may save lives. Ultrasound is the primary imaging modality in pregnancy, but high-quality imaging depends on the access to equipment and staff, which is not possible in all settings. Convolutional neural networks may help standardize the acquisition of images for fetal diagnostics. Our aim was to develop a deep learning based model for classification and segmentation of the placenta in ultrasound images. We trained a model based on manual annotations of 7,500 ultrasound images to identify and segment the placenta. The model's performance was compared to annotations made by 25 clinicians (experts, trainees, midwives). The overall image classification accuracy was 81%. The average intersection over union score (IoU) reached 0.78. The model's accuracy was lower than experts' and trainees', but it outperformed all clinicians at delineating the placenta, IoU = 0.75 vs 0.69, 0.66, 0.59. The model was cross validated on 100 2nd trimester images from Barcelona, yielding an accuracy of 76%, IoU 0.68. In conclusion, we developed a model for automatic classification and segmentation of the placenta with consistent performance across different patient populations. It may be used for automated detection of placenta previa and enable future deep learning research in placental dysfunction.

Diagnostic Accuracy of Gestosis Score in Comparison to multi-marker Screening as a Predictor of Preeclampsia at 11-14 Weeks of Pregnancy: A Cohort Study

BACKGROUND

Pre-eclampsia is a pregnancy-specific multisystemic disorder associated with adverse feto-maternal outcomes. Low-dose Aspirin therapy started in early pregnancy in high-risk women, has significantly reduced the chances of developing PE. Therefore, screening and identification of at-risk mothers are crucial. The present study was planned to study the predictive ability of gestosis score in predicting early-onset pre-eclampsia by comparing it with the multi-marker model.

MATERIAL AND METHODS

One hundred sixteen women, more than 19 years of age, with live singleton pregnancy at 11-13 weeks of gestation were recruited from the antenatal outpatient department and formed the study cohort. After a detailed history, screening for pre-eclampsia was performed both by multi-marker screening and by gestosis score. Diagnostic accuracy was compared for the two methods of screening.

RESULTS

The incidence of pre-eclampsia in the present study cohort was 26.7%. The sensitivity of gestosis score >/= 3 was 84.38% (67.21-94.72) and specificity was 93.18% (85.75-97.46 %). The positive predictive value was 81.82% (67.2%-90.81%), and the negative predictive value was 94.25 (87.98 - 97.35%). The diagnostic accuracy of the gestosis score was 90.83%.

CONCLUSION

Gestosis scoring is a potential tool that can be used as a cost-effective screening method for pre-eclampsia at 11-14 weeks of gestation in low-resource settings. The sensitivity and negative predictive value of the gestosis score is comparable to multi-marker screening using maternal factors, MAP, Uterine artery PI, PAPP-A, and PlGF.