Accuracy of second trimester prediction of preterm preeclampsia by three different screening algorithms

Epigenetic alterations in preeclampsia: a focus on microRNA149 and tetrahydrofolate reductase gene polymorphisms in Egyptian women

BACKGROUND

Preeclampsia (PE) poses a substantial risk to prenatal and maternal health. Folic acid (FA) and methylenetetrahydrofolate reductase (MTHFR) play roles in DNA methylation and genomic integrity maintenance, with MTHFR polymorphisms potentially impacting PE occurrence. Human microRNA 149 (miR-149) remains underexplored in PE despite its involvement in folate metabolism. This study seeks to evaluate serum miR-149 levels with the MTHFR C677T polymorphism for diagnosing PE.

METHODS

Seventy females aged 28-40 gestational weeks were divided into control and Preeclampsia groups. Serum miR-149 and MTHFR gene levels were evaluated using real-time PCR.

RESULTS

Preeclamptic patients showed significantly lower serum miR-149 levels than healthy controls (P ≤ 0.01). PE cases showed a higher frequency of the TT genotype and T allele of the C677T polymorphism (OR = 0.181, 2.882, respectively), implicating them as genetic risk factors. The CT genotype also increased PE risk (OR = 0.26), while no significant difference was observed in the CC genotype.

CONCLUSION

Merging miR-149 and MTHFR polymorphism assessment improves discrimination between healthy and PE groups, offering valuable insights into PE pathogenesis and potential diagnostic strategies.

Comparison of National Factor-Based Models for Preeclampsia Screening

OBJECTIVE

 This study aimed to compare the predictive values of the American College of Obstetricians and Gynecologists (ACOG), the National Institute for Health and Care Excellence (NICE), and the Society of Obstetricians and Gynecologists of Canada (SOGC) factor-based models for preeclampsia (PE) screening.

STUDY DESIGN

 We conducted a secondary analysis of maternal and birth data from 32 hospitals. For each delivery, we calculated the risk of PE according to the ACOG, the NICE, and the SOGC models. Our primary outcomes were PE and preterm PE (PE combined with preterm birth) using the ACOG criteria. We calculated the detection rate (DR or sensitivity), the false positive rate (FPR or 1 - specificity), the positive (PPV) and negative (NPV) predictive values of each model for PE and for preterm PE using receiver operator characteristic (ROC) curves.

RESULTS

 We used 130,939 deliveries including 4,635 (3.5%) cases of PE and 823 (0.6%) cases of preterm PE. The ACOG model had a DR of 43.6% for PE and 50.3% for preterm PE with FPR of 15.6%; the NICE model had a DR of 36.2% for PE and 41.3% for preterm PE with FPR of 12.8%; and the SOGC model had a DR of 49.1% for PE and 51.6% for preterm PE with FPR of 22.2%. The PPV for PE of the ACOG (9.3%) and NICE (9.4%) models were both superior than the SOGC model (7.6%; p < 0.001), with a similar trend for the PPV for preterm PE (1.9 vs. 1.9 vs. 1.4%, respectively; p < 0.01). The area under the ROC curves suggested that the ACOG model is superior to the NICE for the prediction of PE and preterm PE and superior to the SOGC models for the prediction of preterm PE (all with p < 0.001).

CONCLUSION

 The current ACOG factor-based model for the prediction of PE and preterm PE, without considering race, is superior to the NICE and SOGC models.

KEY POINTS

· Clinical factor-based model can predict PE in approximately 44% of the cases for a 16% false positive.. · The ACOG model is superior to the NICE and SOGC models to predict PE.. · Clinical factor-based models are better to predict PE in parous than in nulliparous..

Development and validation of prediction models for fetal growth restriction and birthweight: an individual participant data meta-analysis

Background

Fetal growth restriction is associated with perinatal morbidity and mortality. Early identification of women having at-risk fetuses can reduce perinatal adverse outcomes.

Objectives

To assess the predictive performance of existing models predicting fetal growth restriction and birthweight, and if needed, to develop and validate new multivariable models using individual participant data.

Design

Individual participant data meta-analyses of cohorts in International Prediction of Pregnancy Complications network, decision curve analysis and health economics analysis.

Participants

Pregnant women at booking. External validation of existing models (9 cohorts, 441,415 pregnancies); International Prediction of Pregnancy Complications model development and validation (4 cohorts, 237,228 pregnancies).

Predictors

Maternal clinical characteristics, biochemical and ultrasound markers.

Primary outcomes

fetal growth restriction defined as birthweight <10th centile adjusted for gestational age and with stillbirth, neonatal death or delivery before 32 weeks' gestation birthweight.

Analysis

First, we externally validated existing models using individual participant data meta-analysis. If needed, we developed and validated new International Prediction of Pregnancy Complications models using random-intercept regression models with backward elimination for variable selection and undertook internal-external cross-validation. We estimated the study-specific performance (c-statistic, calibration slope, calibration-in-the-large) for each model and pooled using random-effects meta-analysis. Heterogeneity was quantified using τ2 and 95% prediction intervals. We assessed the clinical utility of the fetal growth restriction model using decision curve analysis, and health economics analysis based on National Institute for Health and Care Excellence 2008 model.

Results

Of the 119 published models, one birthweight model (Poon) could be validated. None reported fetal growth restriction using our definition. Across all cohorts, the Poon model had good summary calibration slope of 0.93 (95% confidence interval 0.90 to 0.96) with slight overfitting, and underpredicted birthweight by 90.4 g on average (95% confidence interval 37.9 g to 142.9 g). The newly developed International Prediction of Pregnancy Complications-fetal growth restriction model included maternal age, height, parity, smoking status, ethnicity, and any history of hypertension, pre-eclampsia, previous stillbirth or small for gestational age baby and gestational age at delivery. This allowed predictions conditional on a range of assumed gestational ages at delivery. The pooled apparent c-statistic and calibration were 0.96 (95% confidence interval 0.51 to 1.0), and 0.95 (95% confidence interval 0.67 to 1.23), respectively. The model showed positive net benefit for predicted probability thresholds between 1% and 90%. In addition to the predictors in the International Prediction of Pregnancy Complications-fetal growth restriction model, the International Prediction of Pregnancy Complications-birthweight model included maternal weight, history of diabetes and mode of conception. Average calibration slope across cohorts in the internal-external cross-validation was 1.00 (95% confidence interval 0.78 to 1.23) with no evidence of overfitting. Birthweight was underestimated by 9.7 g on average (95% confidence interval -154.3 g to 173.8 g).

Limitations

We could not externally validate most of the published models due to variations in the definitions of outcomes. Internal-external cross-validation of our International Prediction of Pregnancy Complications-fetal growth restriction model was limited by the paucity of events in the included cohorts. The economic evaluation using the published National Institute for Health and Care Excellence 2008 model may not reflect current practice, and full economic evaluation was not possible due to paucity of data.

Future work

International Prediction of Pregnancy Complications models' performance needs to be assessed in routine practice, and their impact on decision-making and clinical outcomes needs evaluation.

Conclusion

The International Prediction of Pregnancy Complications-fetal growth restriction and International Prediction of Pregnancy Complications-birthweight models accurately predict fetal growth restriction and birthweight for various assumed gestational ages at delivery. These can be used to stratify the risk status at booking, plan monitoring and management.

Study registration

This study is registered as PROSPERO CRD42019135045.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 17/148/07) and is published in full in Health Technology Assessment; Vol. 28, No. 14. See the NIHR Funding and Awards website for further award information.

Prospective Validation of First-Trimester Screening for Preterm Preeclampsia in Nulliparous Women (PREDICTION Study)

BACKGROUND

Fetal Medicine Foundation (FMF) studies suggest that preterm preeclampsia can be predicted in the first trimester by combining biophysical, biochemical, and ultrasound markers and prevented using aspirin. We aimed to evaluate the FMF preterm preeclampsia screening test in nulliparous women.

METHODS

We conducted a prospective multicenter cohort study of nulliparous women recruited at 11 to 14 weeks. Maternal characteristics, mean arterial blood pressure, PAPP-A (pregnancy-associated plasma protein A), PlGF (placental growth factor) in maternal blood, and uterine artery pulsatility index were collected at recruitment. The risk of preterm preeclampsia was calculated by a third party blinded to pregnancy outcomes. Receiver operating characteristic curves were used to estimate the detection rate (sensitivity) and the false-positive rate (1-specificity) for preterm (<37 weeks) and for early-onset (<34 weeks) preeclampsia according to the FMF screening test and according to the American College of Obstetricians and Gynecologists criteria.

RESULTS

We recruited 7554 participants including 7325 (97%) who remained eligible after 20 weeks of which 65 (0.9%) developed preterm preeclampsia, and 22 (0.3%) developed early-onset preeclampsia. Using the FMF algorithm (cutoff of ≥1 in 110 for preterm preeclampsia), the detection rate was 63.1% for preterm preeclampsia and 77.3% for early-onset preeclampsia at a false-positive rate of 15.8%. Using the American College of Obstetricians and Gynecologists criteria, the equivalent detection rates would have been 61.5% and 59.1%, respectively, for a false-positive rate of 34.3%.

CONCLUSIONS

The first-trimester FMF preeclampsia screening test predicts two-thirds of preterm preeclampsia and three-quarters of early-onset preeclampsia in nulliparous women, with a false-positive rate of ≈16%.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT02189148.

Effects of race and ethnicity on perinatal outcomes in high-income and upper-middle-income countries: an individual participant data meta-analysis of 2 198 655 pregnancies

BACKGROUND

Existing evidence on the effects of race and ethnicity on pregnancy outcomes is restricted to individual studies done within specific countries and health systems. We aimed to assess the impact of race and ethnicity on perinatal outcomes in high-income and upper-middle-income countries, and to ascertain whether the magnitude of disparities, if any, varied across geographical regions.

METHODS

For this individual participant data (IPD) meta-analysis we used data from the International Prediction of Pregnancy Complications (IPPIC) Network of studies on pregnancy complications; the full dataset comprised 94 studies, 53 countries, and 4 539 640 pregnancies. We included studies that reported perinatal outcomes (neonatal death, stillbirth, preterm birth, and small-for-gestational-age babies) in at least two racial or ethnic groups (White, Black, south Asian, Hispanic, or other). For our two-step random-effects IPD meta-analysis, we did multiple imputations for confounder variables (maternal age, BMI, parity, and level of maternal education) selected with a directed acyclic graph. The primary outcomes were neonatal mortality and stillbirth. Secondary outcomes were preterm birth and a small-for-gestational-age baby. We estimated the association of race and ethnicity with perinatal outcomes using a multivariate logistic regression model and reported this association with odds ratios (ORs) and 95% CIs. We also did a subgroup analysis of studies by geographical region.

FINDINGS

51 studies from 20 high-income and upper-middle-income countries, comprising 2 198 655 pregnancies, were eligible for inclusion in this IPD meta-analysis. Neonatal death was twice as likely in babies born to Black women than in babies born to White women (OR 2·00, 95% CI 1·44-2·78), as was stillbirth (2·16, 1·46-3·19), and babies born to Black women were at increased risk of preterm birth (1·65, 1·46-1·88) and being small for gestational age (1·39, 1·13-1·72). Babies of women categorised as Hispanic had a three-times increased risk of neonatal death (OR 3·34, 95% CI 2·77-4·02) than did those born to White women, and those born to south Asian women were at increased risk of preterm birth (OR 1·26, 95% CI 1·07-1·48) and being small for gestational age (1·61, 1·32-1·95). The effects of race and ethnicity on preterm birth and small-for-gestational-age babies did not vary across regions.

INTERPRETATION

Globally, among underserved groups, babies born to Black women had consistently poorer perinatal outcomes than White women after adjusting for maternal characteristics, although the risks varied for other groups. The effects of race and ethnicity on adverse perinatal outcomes did not vary by region.

FUNDING

National Institute for Health and Care Research, Wellbeing of Women.

Maternal race and pre-eclampsia: Cohort study and systematic review with meta-analysis

OBJECTIVES

To examine the association between race and pre-eclampsia and gestational hypertension after adjustment for factors in maternal characteristics and medical history in a screening study from the Fetal Medicine Foundation (FMF) in England, and to perform a systematic review and meta-analysis of studies on pre-eclampsia.

DESIGN

Prospective observational study and systematic review with meta-analysis.

SETTING

Two UK maternity hospitals.

POPULATION

A total of 168 966 women with singleton pregnancies attending for routine ultrasound examination at 11-13 weeks of gestation without major abnormalities delivering at 24 weeks or more of gestation.

METHODS

Regression analysis examined the association between race and pre-eclampsia or gestational hypertension in the FMF data. Literature search to December 2021 was carried out to identify peer-reviewed publications on race and pre-eclampsia.

MAIN OUTCOME MEASURE

Relative risk of pre-eclampsia and gestational hypertension in women of black, South Asian and East Asian race by comparison to white women.

RESULTS

In black women, the respective risks of total-pre-eclampsia and preterm-pre-eclampsia were 2-fold and 2.5-fold higher, respectively, and risk of gestational hypertension was 25% higher; in South Asian women there was a 1.5-fold higher risk of preterm pre-eclampsia but not of total-pre-eclampsia and in East Asian women there was no statistically significant difference in risk of hypertensive disorders. The literature search identified 19 studies that provided data on several million pregnancies, but 17 were at moderate or high-risk of bias and only three provided risks adjusted for some maternal characteristics; consequently, these studies did not provide accurate contributions on different racial groups to the prediction of pre-eclampsia.

CONCLUSION

In women of black and South Asian origin the risk of pre-eclampsia, after adjustment for confounders, is higher than in white women.

Validation and development of models using clinical, biochemical and ultrasound markers for predicting pre-eclampsia: an individual participant data meta-analysis

BACKGROUND

Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk is needed to plan management.

OBJECTIVES

To assess the performance of existing pre-eclampsia prediction models and to develop and validate models for pre-eclampsia using individual participant data meta-analysis. We also estimated the prognostic value of individual markers.

DESIGN

This was an individual participant data meta-analysis of cohort studies.

SETTING

Source data from secondary and tertiary care.

PREDICTORS

We identified predictors from systematic reviews, and prioritised for importance in an international survey.

PRIMARY OUTCOMES

Early-onset (delivery at < 34 weeks' gestation), late-onset (delivery at ≥ 34 weeks' gestation) and any-onset pre-eclampsia.

ANALYSIS

We externally validated existing prediction models in UK cohorts and reported their performance in terms of discrimination and calibration. We developed and validated 12 new models based on clinical characteristics, clinical characteristics and biochemical markers, and clinical characteristics and ultrasound markers in the first and second trimesters. We summarised the data set-specific performance of each model using a random-effects meta-analysis. Discrimination was considered promising for C-statistics of ≥ 0.7, and calibration was considered good if the slope was near 1 and calibration-in-the-large was near 0. Heterogeneity was quantified using I ² and τ². A decision curve analysis was undertaken to determine the clinical utility (net benefit) of the models. We reported the unadjusted prognostic value of individual predictors for pre-eclampsia as odds ratios with 95% confidence and prediction intervals.

RESULTS

The International Prediction of Pregnancy Complications network comprised 78 studies (3,570,993 singleton pregnancies) identified from systematic reviews of tests to predict pre-eclampsia. Twenty-four of the 131 published prediction models could be validated in 11 UK cohorts. Summary C-statistics were between 0.6 and 0.7 for most models, and calibration was generally poor owing to large between-study heterogeneity, suggesting model overfitting. The clinical utility of the models varied between showing net harm to showing minimal or no net benefit. The average discrimination for IPPIC models ranged between 0.68 and 0.83. This was highest for the second-trimester clinical characteristics and biochemical markers model to predict early-onset pre-eclampsia, and lowest for the first-trimester clinical characteristics models to predict any pre-eclampsia. Calibration performance was heterogeneous across studies. Net benefit was observed for International Prediction of Pregnancy Complications first and second-trimester clinical characteristics and clinical characteristics and biochemical markers models predicting any pre-eclampsia, when validated in singleton nulliparous women managed in the UK NHS. History of hypertension, parity, smoking, mode of conception, placental growth factor and uterine artery pulsatility index had the strongest unadjusted associations with pre-eclampsia.

LIMITATIONS

Variations in study population characteristics, type of predictors reported, too few events in some validation cohorts and the type of measurements contributed to heterogeneity in performance of the International Prediction of Pregnancy Complications models. Some published models were not validated because model predictors were unavailable in the individual participant data.

CONCLUSION

For models that could be validated, predictive performance was generally poor across data sets. Although the International Prediction of Pregnancy Complications models show good predictive performance on average, and in the singleton nulliparous population, heterogeneity in calibration performance is likely across settings.

FUTURE WORK

Recalibration of model parameters within populations may improve calibration performance. Additional strong predictors need to be identified to improve model performance and consistency. Validation, including examination of calibration heterogeneity, is required for the models we could not validate.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42015029349.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 72. See the NIHR Journals Library website for further project information.

Serum leukotriene B4 and hydroxyeicosatetraenoic acid in the prediction of pre-eclampsia

INTRODUCTION

Pre-eclampsia (PE) affects 2-8% of pregnancies worldwide. Despite identification of numerous possible biomarkers, accurate prediction and early diagnosis of PE remain challenging. We examined the potential of leukotriene B4 (LTB4) and 15-hydroxyeicosatetraenoic acid (15(S)-HETE) as biomarkers of PE by comparing serum levels at three gestational age (GA) groups between normotensive pregnancies and asymptomatic women who subsequently developed preterm or term-PE.

METHODS

This is a case-control study drawn from a prospective study of adverse pregnancy outcomes with serum samples collected at 19-24 weeks (n = 48), 30-34 weeks (n = 101) and 35-37 weeks (n = 54) GA. LTB4 and 15(S)-HETE levels were determined by ELISA. Serum level multiples of the median (MoM) were compared between normal and PE-pregnancies. Association between LTB4 and 15(S)-HETE and GA at delivery was investigated with Cox proportional-hazards models.

RESULTS

Serum LTB4 levels were lower in women of East-Asian ethnicity, higher in women with PE history, and increased with GA in normotensive pregnancies, but not in PE. LTB4 was elevated at 19-24 weeks in women who developed preterm-PE. There was a negative association between LTB4 MoM and interval between sampling and delivery with PE at 19-24 weeks only. Serum 15(S)-HETE levels were not influenced by GA at testing and were elevated in women of South-Asian ethnicity. Median 15(S)-HETE levels were unchanged in preterm and term-PE at any GA.

DISCUSSION

LTB4 was higher at 19-24 weeks in pregnancies that developed preterm-PE versus unaffected pregnancies, suggesting it is a potentially useful predictive marker of preterm PE in the second trimester.

Prediction of preterm pre-eclampsia at midpregnancy using a multivariable screening algorithm

BACKGROUND

Competing risk models used for midpregnancy prediction of preterm pre-eclampsia have shown detection rates (DR) of 85%, at fixed false-positive rate (FPR) of 10%. The full algorithm used between 19⁺⁰ and 24⁺⁶  weeks includes maternal factors, mean arterial pressure (MAP), mean uterine artery pulsatility index (UtAPI), serum placental growth factor (PlGF) level in multiples of the median (MoM), and soluble Fms-like tyrosine kinase-1 (sFlt-1) level in MoM.

AIMS

To assess performance of the Fetal Medicine Foundation (FMF) algorithm at midpregnancy to screen for preterm (<37 weeks) pre-eclampsia. The outcome measured was preterm pre-eclampsia.

MATERIALS AND METHODS

This is a prospective study including singleton pregnancies at 19-22 weeks gestation. Maternal bloods were collected and analysed using three different immunoassay platforms. Maternal characteristics, medical history, MAP, mean UtAPI, serum PlGF MoM and serum sFlt-1 MoM were used for risk assessment. DR and FPR were calculated, and receiver operating characteristic curves produced.

RESULTS

Five hundred and twelve patients were included. Incidence of preterm pre-eclampsia was 1.6%. Using predicted risk of pre-eclampsia of one in 60 or more and one in 100 or higher, as given by the FMF predictive algorithm, the combination with the best predictive performance for preterm pre-eclampsia included maternal factors, MAP, UtAPI and PlGF MoM, giving DRs of 100% and 100%, respectively, and FPRs of 9.3 for all platforms and 12.9-13.5, respectively. Addition of sFlt-1 to the algorithm did not appear to improve performance. sFlt-1 MoM and PlGF MoM values obtained on the different platforms performed very similarly.

CONCLUSIONS

Second trimester combined screening for preterm pre-eclampsia by maternal history, MAP, mean UtAPI and PlGF MoM using the FMF algorithm performed very well in this patient population.

Lipid profiling in maternal and fetal circulations in preeclampsia and fetal growth restriction-a prospective case control observational study

Background

While many risk factors for preeclampsia, such as increased body mass index, advanced maternal age, chronic hypertension, diabetes, are now established in clinical practice, maternal lipid profile has not been included in the risk assessment for preeclampsia. We aim to characterize the serum levels of Total Cholesterol (TC), High density lipoprotein (HDL), Low density lipoprotein (LDL), Triglycerides (TG), Apolipoprotein A1, Apolipoprotein B and their ratios TC/HDL and ApoB/ApoA1 in the maternal and fetal circulations of normal pregnancy, preeclampsia (PE), fetal growth restriction (FGR) and PE + FGR.

Methods

A prospective cross-sectional case control study was conducted measuring maternal and fetal lipid levels by enzymatic analysis and immune-turbidimetric enzymatic assays. FGR was defined by elevated umbilical artery Doppler resistance in association with estimated fetal weight < 10%. Kruskal Wallis non-parametric analysis of variance was used to test for homogeneity across the clinical groups for each of the variables, Mann-Whitney tests for pairwise comparisons and Spearman rank correlation were used to quantify gestational age-related changes.

Results

(1) TG levels were elevated in maternal PE and cord blood PE + FGR groups compared to normal pregnancies. (2) A statistically significant elevation of fetal ApoB levels was observed in PE, FGR and PE + FGR compared to normal pregnancies. Apolipoprotein levels A1 and B were not different between maternal groups. (3) TC, HDL, LDL and TC/HDL levels did not show any significant gestational variation or between clinical groups in the maternal or fetal circulation.

Conclusions

Elevation in maternal TG levels may have a role in the pathogenesis of PE. The implications of elevated maternal and fetal TG levels and elevated fetal Apolipoprotein B levels deserves further exploration of their role in long term cardiovascular risk in the mother as well as the offspring.

Prediction of pre-eclampsia in nulliparous women using routinely collected maternal characteristics: a model development and validation study

Background

Guidelines recommend identifying in early pregnancy women at elevated risk of pre-eclampsia. The aim of this study was to develop and validate a pre-eclampsia risk prediction model for nulliparous women attending routine antenatal care “the Western Sydney (WS) model”; and to compare its performance with the National Institute of Health and Care Excellence (NICE) risk factor-list approach for classifying women as high-risk.

Methods

This retrospective cohort study included all nulliparous women who gave birth in three public hospitals in the Western-Sydney-Local-Health-District, Australia 2011–2014. Using births from 2011 to 2012, multivariable logistic regression incorporated established maternal risk factors to develop and internally validate the WS model. The WS model was then externally validated using births from 2013 to 2014, assessing its discrimination and calibration. We fitted the final WS model for all births from 2011 to 2014, and compared its accuracy in predicting pre-eclampsia with the NICE approach.

Results

Among 12,395 births to nulliparous women in 2011–2014, there were 293 (2.4%) pre-eclampsia events. The WS model included: maternal age, body mass index, ethnicity, multiple pregnancy, family history of pre-eclampsia, autoimmune disease, chronic hypertension and chronic renal disease. In the validation sample (6201 births), the model c-statistic was 0.70 (95% confidence interval 0.65–0.75). The observed:expected ratio for pre-eclampsia was 0.91, with a Hosmer-Lemeshow goodness-of-fit test p-value of 0.20. In the entire study sample of 12,395 births, 374 (3.0%) women had a WS model-estimated pre-eclampsia risk ≥8%, the pre-specified risk-threshold for considering aspirin prophylaxis. Of these, 54 (14.4%) developed pre-eclampsia (sensitivity 18% (14–23), specificity 97% (97–98)). Using the NICE approach, 1173 (9.5%) women were classified as high-risk, of which 107 (9.1%) developed pre-eclampsia (sensitivity 37% (31–42), specificity 91% (91–92)). The final model showed similar accuracy to the NICE approach when using lower risk-threshold of ≥4% to classify women as high-risk for pre-eclampsia.

Conclusion

The WS risk model that combines readily-available maternal characteristics achieved modest performance for prediction of pre-eclampsia in nulliparous women. The model did not outperform the NICE approach, but has the advantage of providing individualised absolute risk estimates, to assist with counselling, inform decisions for further testing, and consideration of aspirin prophylaxis.