Prediction of preeclampsia utilizing the first trimester screening examination

Aspirin for evidence-based preeclampsia prevention trial: effects of aspirin on maternal serum pregnancy-associated plasma protein A and placental growth factor trajectories in pregnancy

BACKGROUND

The exact mechanism by which aspirin prevents preeclampsia remains unclear. Its effects on serum placental biomarkers throughout pregnancy are also unknown.

OBJECTIVE

To investigate the effects of aspirin on serum pregnancy-associated plasma protein A and placental growth factor trajectories using repeated measures from women at increased risk of preterm preeclampsia.

STUDY DESIGN

This was a longitudinal secondary analysis of the Combined Multimarker Screening and Randomized Patient Treatment with Aspirin for Evidence-based Preeclampsia Prevention trial using repeated measures of pregnancy-associated plasma protein A and placental growth factor. In the trial, 1620 women at increased risk of preterm preeclampsia were identified using the Fetal Medicine Foundation algorithm at 11 to 13+6 weeks of gestation, of whom 798 were randomly assigned to receive aspirin 150 mg and 822 to receive placebo daily from before 14 weeks to 36 weeks of gestation. Serum biomarkers were measured at baseline and follow-up visits at 19 to 24, 32 to 34, and 36 weeks of gestation. Generalized additive mixed models with treatment by gestational age interaction terms were used to investigate the effect of aspirin on biomarker trajectories over time.

RESULTS

Overall, there were 5507 pregnancy-associated plasma protein A and 5523 placental growth factor measurements. Raw pregnancy-associated plasma protein A values increased over time, and raw placental growth factor increased until 32 weeks of gestation followed by a decline. The multiple of the median mean values of the same biomarkers were consistently below 1.0 multiple of the median, reflecting the high-risk profile of the study population. Trajectories of mean pregnancy-associated plasma protein A and placental growth factor multiple of the median values did not differ significantly between the aspirin and placebo groups (aspirin treatment by gestational age interaction P values: .259 and .335, respectively).

CONCLUSION

In women at increased risk of preterm preeclampsia, aspirin 150 mg daily had no significant effects on pregnancy-associated plasma protein A or placental growth factor trajectories when compared to placebo.

Therapeutic Value of Low-Dose Acetylsalicylic Acid for the Prevention of Preeclampsia in High-Risk Bulgarian Women

Introduction Preeclampsia (PE) is a syndrome that affects pregnant women after 20 weeks of gestation and involves numerous organ systems. Screening for PE is essential to prevent complications and guide management. Some existing guidelines for screening have limitations in terms of detection rates and false positives. The aim of this study is to assess the therapeutic value of low-dose acetylsalicylic acid (ASA) for the prevention of PE in high-risk Bulgarian women. Methodology A prospective cohort research was carried out, encompassing women who were recruited from several routine consultations, such as booking, scanning, and regular prenatal visits. We utilized the purposive sampling technique to carefully choose potential participants. The study was conducted by a maternal-fetal medicine center located in Plovdiv, Bulgaria. The data-gathering period spanned from January 2018 to November 2020. At the appointment, the following procedures were conducted: 1) recording history; 2) assessing height, weight, and blood pressure; 3) collecting blood specimens for biochemical markers; and 4) ultrasound examination. Results A total sample size of 1,383 individuals was categorized into two distinct groups: high-risk patients (n = 506) and low-risk patients (n = 877). The mean uterine artery pulsatility index (UtA-PI) and mean arterial pressure (MAP) ratios were all greater in high-risk group women (p < 0.05). The data revealed that a significant number of high-risk women failed to adhere to the prescribed dosage or regular use of ASA as recommended by their doctor. There were only 384 (75.9%) high-risk women who took low-dose ASA regularly. Conclusion The findings emphasize the importance of personalized prenatal care and early risk assessment to improve maternal and fetal outcomes. Therefore, it is crucial to educate pregnant women, considering the benefits and risks of low-dose ASA when appropriately indicated.

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.

Machine Learning Algorithms Versus Classical Regression Models in Pre-Eclampsia Prediction: A Systematic Review

PURPOSE OF REVIEW

Machine learning (ML) approaches are an emerging alternative for healthcare risk prediction. We aimed to synthesise the literature on ML and classical regression studies exploring potential prognostic factors and to compare prediction performance for pre-eclampsia.

RECENT FINDINGS

From 9382 studies retrieved, 82 were included. Sixty-six publications exclusively reported eighty-four classical regression models to predict variable timing of onset of pre-eclampsia. Another six publications reported purely ML algorithms, whilst another 10 publications reported ML algorithms and classical regression models in the same sample with 8 of 10 findings that ML algorithms outperformed classical regression models. The most frequent prognostic factors were age, pre-pregnancy body mass index, chronic medical conditions, parity, prior history of pre-eclampsia, mean arterial pressure, uterine artery pulsatility index, placental growth factor, and pregnancy-associated plasma protein A. Top performing ML algorithms were random forest (area under the curve (AUC) = 0.94, 95% confidence interval (CI) 0.91-0.96) and extreme gradient boosting (AUC = 0.92, 95% CI 0.90-0.94). The competing risk model had similar performance (AUC = 0.92, 95% CI 0.91-0.92) compared with a neural network. Calibration performance was not reported in the majority of publications. ML algorithms had better performance compared to classical regression models in pre-eclampsia prediction. Random forest and boosting-type algorithms had the best prediction performance. Further research should focus on comparing ML algorithms to classical regression models using the same samples and evaluation metrics to gain insight into their performance. External validation of ML algorithms is warranted to gain insights into their generalisability.

Externally validated prediction models for pre-eclampsia: systematic review and meta-analysis

OBJECTIVE

This systematic review and meta-analysis aimed to evaluate the performance of existing externally validated prediction models for pre-eclampsia (PE) (specifically, any-onset, early-onset, late-onset and preterm PE).

METHODS

A systematic search was conducted in five databases (MEDLINE, EMBASE, Emcare, CINAHL and Maternity & Infant Care Database) and using Google Scholar/reference search to identify studies based on the Population, Index prediction model, Comparator, Outcome, Timing and Setting (PICOTS) approach until 20 May 2023. We extracted data using the CHARMS checklist and appraised the risk of bias using the PROBAST tool. A meta-analysis of discrimination and calibration performance was conducted when appropriate.

RESULTS

Twenty-three studies reported 52 externally validated prediction models for PE (one preterm, 20 any-onset, 17 early-onset and 14 late-onset PE models). No model had the same set of predictors. Fifteen any-onset PE models were validated externally once, two were validated twice and three were validated three times, while the Fetal Medicine Foundation (FMF) competing-risks model for preterm PE prediction was validated widely in 16 different settings. The most common predictors were maternal characteristics (prepregnancy body mass index, prior PE, family history of PE, chronic medical conditions and ethnicity) and biomarkers (uterine artery pulsatility index and pregnancy-associated plasma protein-A). The FMF model for preterm PE (triple test plus maternal factors) had the best performance, with a pooled area under the receiver-operating-characteristics curve (AUC) of 0.90 (95% prediction interval (PI), 0.76-0.96), and was well calibrated. The other models generally had poor-to-good discrimination performance (median AUC, 0.66 (range, 0.53-0.77)) and were overfitted on external validation. Apart from the FMF model, only two models that were validated multiple times for any-onset PE prediction, which were based on maternal characteristics only, produced reasonable pooled AUCs of 0.71 (95% PI, 0.66-0.76) and 0.73 (95% PI, 0.55-0.86).

CONCLUSIONS

Existing externally validated prediction models for any-, early- and late-onset PE have limited discrimination and calibration performance, and include inconsistent input variables. The triple-test FMF model had outstanding discrimination performance in predicting preterm PE in numerous settings, but the inclusion of specialized biomarkers may limit feasibility and implementation outside of high-resource settings. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Prediction of preeclampsia in asymptomatic women

Preeclampsia is a major cause of maternal and perinatal morbidity and mortality. It is important to identify women who are at high risk of developing this disorder in their first trimester of pregnancy to allow timely therapeutic intervention. The use of low-dose aspirin initiated before 16 weeks of gestation can significantly reduce the rate of preterm preeclampsia by 62 %. Effective screening recommended by the Fetal Medicine Foundation (FMF) consists of a combination of maternal risk factors, mean arterial pressure, uterine artery pulsatility index (UtA-PI) and placental growth factor (PLGF). The current model has detection rates of 90 %, 75 %, and 41 % for early, preterm, and term preeclampsia, respectively at 10 % false-positive rate. Similar risk assessment can be performed during the second trimester in all pregnant women irrespective of first trimester screening results. The use of PLGF, UtA-PI, sFlt-1 combined with other investigative tools are part of risk assessment.

Machine-learning predictive model of pregnancy-induced hypertension in the first trimester

In the first trimester of pregnancy, accurately predicting the occurrence of pregnancy-induced hypertension (PIH) is important for both identifying high-risk women and adopting early intervention. In this study, we used four machine-learning models (LASSO logistic regression, random forest, backpropagation neural network, and support vector machines) to predict the occurrence of PIH in a prospective cohort. Candidate features for predicting the occurrence of middle and late PIH were acquired using a LASSO algorithm. The performance of predictive models was assessed using receiver operating characteristic analysis. Finally, a nomogram was established with the model scores, age, and nulliparity. Calibration, clinical usefulness, and internal validation were used to assess the performance of the nomogram. In the training set (2258 pregnant women), eleven candidate factors in the first trimester were significantly associated with the occurrence of PIH (P < 0.001 in the training set). Four models showed AUCs from 0.780 to 0.816 in the training set. For the validation set (939 pregnant women), AUCs varied from 0.516 to 0.795. The nomogram showed good discrimination, with an AUC of 0.847 (95% CI: 0.805-0.889) in the training set and 0.753 (95% CI: 0.653-0.853) in the validation set. Decision curve analysis suggested that the model was clinically useful. The model developed using LASSO logistic regression achieved the best performance in predicting the occurrence of PIH. The derived nomogram, which incorporates the model score and maternal risk factors, can be used to predict PIH in clinical practice. We develop a model with good performance for clinical prediction of PIH in the first trimester.

Ophthalmic artery Doppler for pre-eclampsia prediction at the first trimester: a Bayesian survival-time model

OBJECTIVE

To develop a Bayesian survival-time model for the prediction of pre-eclampsia (PE) at the first trimester using a combination of established biomarkers including maternal characteristics and history, mean arterial pressure (MAP), uterine artery Doppler pulsatility index (UtA-PI), and Placental Growth Factor (PlGF)) with an ophthalmic artery Doppler peak ratio (PR) analysis.

METHODS

The receiving operator curve (ROC) analysis was used to determine the area under the curve (AUC), detection rate (DR), and positive screening cut-off value of the model in predicting the occurrence of early-onset PE (< 34 weeks' gestation) and preterm PE (< 37 weeks' gestation).

RESULTS

Of the 946 eligible participants, 71 (7.49%) subjects were affected by PE. The incidences of early-onset and preterm PE were 1% and 2.2%, respectively. At a 10% false-positive rate, using the high-risk cut-off 1:49, with AUC 0.981 and 95%CI 0.965-0.998, this model had an 100% of DR in predicting early-onset PE. The DR of this model in predicting preterm PE is 71% when using 1:13 as the cut-off, with AUC 0.919 and 95%CI 0.875-0.963.

CONCLUSION

Combination ophthalmic artery Doppler PR with the previously established biomarkers could improve the accuracy of early and preterm PE prediction at the first trimester screening.

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.

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.

Study on the Effect of B-Ultrasound NT Scan in Early Pregnancy Combined with Serum Screening in Early and Middle Pregnancy for Down Syndrome

Objective

Down syndrome (DS), also known as trisomy 21 syndrome, is a common and most harmful congenital chromosomal genetic disease. This study is aimed at exploring the effect of B-ultrasound NT scan in early pregnancy combined with serum screening in early and middle pregnancy for Down syndrome.

Methods

A total of 168 pregnant women who were diagnosed and treated in the obstetric clinic of our hospital from January 2019 to December 2021 were selected as the research objects. B-ultrasound NT scanning and serum detection in the early and middle trimester of pregnancy were performed, respectively. The accuracy of single detection and combined detection was analyzed and compared with the results of amniotic fluid cell chromosome examination as the gold standard.

Results

There were 4 cases of DS and 165 cases of non-DS. The serum PAPP-A, AFP, and UE levels in DS group were lower than those in non-DS group. β-HCG level and NT value were higher than those in non-DS group (all p < 0.05). Among 168 pregnant women, 5 cases were diagnosed as abnormal by ultrasonography, and 1 case was diagnosed as normal. By serological test, 20 cases with high risk of DS were diagnosed in 4 cases, and 148 cases with low risk of DS were diagnosed in 2 cases. Among 168 cases examined by serology combined with ultrasound, 10 cases with high risk of DS were found, and 4 cases were diagnosed; 158 cases had low risk of DS, and 0 cases were diagnosed. The negative predictive value, specificity, and coincidence rate of DS screening by the three methods were higher, and the positive predictive value and coincidence rate of combined screening were the highest (p < 0.05). The screening risk of Down syndrome was correlated with pregnancy outcome. The abnormal pregnancy rate in high-risk group was significantly higher than that in low-risk group, and the difference was statistically significant (p < 0.05). ROC curve showed that the sensitivity, specificity, and AUC of the combined detection were greater than those of serology and NT.

Conclusion

The application of B-ultrasound NT scan in early pregnancy combined with early and mid-term serum comprehensive screening in the screening of Down's infants is helpful to improve the diagnostic coincidence rate and reduce the occurrence of misdiagnosis.

Development and Validation of Multi-Stage Prediction Models for Pre-eclampsia: A Retrospective Cohort Study on Chinese Women

Objective

The aim of this study is to develop multistage prediction models for pre-eclampsia (PE) covering almost the entire pregnancy period based on routine antenatal measurements and to propose a risk screening strategy.

Methods

This was a retrospective cohort study that included 20582 singleton pregnant women with the last menstruation between January 1, 2013 and December 31, 2019. Of the 20582 women, 717 (3.48%) developed pre-eclampsia, including 46 (0.22%) with early-onset pre-eclampsia and 119 (0.58%) preterm pre-eclampsia. We randomly divided the dataset into the training set (N = 15665), the testing set (N = 3917), and the validation set (N = 1000). Least Absolute Shrinkage And Selection Operator (LASSO) was used to do variable selection from demographic characteristics, blood pressure, blood routine examination and biochemical tests. Logistic regression was used to develop prediction models at eight periods: 5-10 weeks, 11-13 weeks, 14-18 weeks, 19-23 weeks, 24-27 weeks, 28-31 weeks, 32-35 weeks, and 36-39 weeks of gestation. We calculated the AUROC (Area Under the Receiver Operating Characteristic Curve) on the test set and validated the screening strategy on the validation set.

Results

We found that uric acid tested from 5-10 weeks of gestation, platelets tested at 18-23 and 24-31 weeks of gestation, and alkaline phosphatase tested at 28-31, 32-35 and 36-39 weeks of gestation can further improve the prediction performance of models. The AUROC of the optimal prediction models on the test set gradually increased from 0.71 at 5-10 weeks to 0.80 at 24-27 weeks, and then gradually increased to 0.95 at 36-39 weeks of gestation. At sensitivity level of 0.98, our screening strategy can identify about 94.8% of women who will develop pre-eclampsia and reduce about 40% of the healthy women to be screened by 28-31 weeks of pregnancy.

Conclusion

We developed multistage prediction models and a risk screening strategy, biomarkers of which were part of routine test items and did not need extra costs. The prediction window has been advanced to 5-10 weeks, which has allowed time for aspirin intervention and other means for PE high-risk groups.

Alternatives of Risk Prediction Models for Preeclampsia in a Low Middle-Income Setting

Abstract Objectives:  To  develop prediction models for the first-trimester prediction of PE (PE) using the established biomarkers including maternal characteristics and history, mean arterial pressure (MAP), uterine artery Doppler pulsatility index (UtA-PI ), and Placental Growth Factor (PlGF)) in combination with Ophthalmic artery Doppler peak ratio (PR). Methods:  This was a  prospective observational study in women attending a first-trimester screening at 11-14 weeks’  gestation. Maternal characteristics and history, measurement of MAP, ultrasound examination for UtA-PI measurement, maternal ophthalmic PR Doppler measurement, and serum  PlGF collection were performed during the visit. Logistic regression  analysis was used to determine if the maternal factor had a significant contribution in predicting PE. The Receiving Operator Curve (ROC) analysis was used to determine the area under the curve  (AUC), positive predictive value  (PPV), negative prefictive value (NPV) and positive screening cut-off in predicting the occurrence of PE at any gestational age.   Results: Of the 946 eligible participants, 71 (7,49%) subjects were affected by PE. Based on the ROC curves, optimal high-risk cutoff value for prediction of preeclampsia at any gestational age for model 2 (primary care model) in this Indonesia study population were 63% with the sensitivity and specificity of 71.8% and 71.2%, respectively. Both sensitivity and specificity for model 3 (complete model) were 70.4% and 74.9%, respectively for the cutoff value 58%. The area under the curve of model 2, model 3 was 0.7651 (95% CI: 0.7023-0.8279)) and 0.7911 (95% CI: 0.7312-0.8511), respectively, for predicting PE. In addition, PPV and NPV for model 2 were 16.8% and 96.9%, respectively. PPV and NPV for model 3 were 18.55 and 96.9%, respectively.   Conclusion: The prediction models of preeclampsia vary depending upon healthcare resource. Complete model is clinically superior to primary care model but it is not statistically significant.  Prognostic models should be easy to use, informative and low cost with great potential to improve maternal and neonatal health in Low Middle Income Country settings. 

First trimester preeclampsia screening and prediction

Preeclampsia is a major cause of maternal and perinatal morbidity and mortality. Early-onset disease requiring preterm delivery is associated with a higher risk of complications in both mothers and babies. Evidence suggests that the administration of low-dose aspirin initiated before 16 weeks' gestation significantly reduces the rate of preterm preeclampsia. Therefore, it is important to identify pregnant women at risk of developing preeclampsia during the first trimester of pregnancy, thus allowing timely therapeutic intervention. Several professional organizations such as the American College of Obstetricians and Gynecologists (ACOG) and National Institute for Health and Care Excellence (NICE) have proposed screening for preeclampsia based on maternal risk factors. The approach recommended by ACOG and NICE essentially treats each risk factor as a separate screening test with additive detection rate and screen-positive rate. Evidence has shown that preeclampsia screening based on the NICE and ACOG approach has suboptimal performance, as the NICE recommendation only achieves detection rates of 41% and 34%, with a 10% false-positive rate, for preterm and term preeclampsia, respectively. Screening based on the 2013 ACOG recommendation can only achieve detection rates of 5% and 2% for preterm and term preeclampsia, respectively, with a 0.2% false-positive rate. Various first trimester prediction models have been developed. Most of them have not undergone or failed external validation. However, it is worthy of note that the Fetal Medicine Foundation (FMF) first trimester prediction model (namely the triple test), which consists of a combination of maternal factors and measurements of mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor, has undergone successful internal and external validation. The FMF triple test has detection rates of 90% and 75% for the prediction of early and preterm preeclampsia, respectively, with a 10% false-positive rate. Such performance of screening is superior to that of the traditional method by maternal risk factors alone. The use of the FMF prediction model, followed by the administration of low-dose aspirin, has been shown to reduce the rate of preterm preeclampsia by 62%. The number needed to screen to prevent 1 case of preterm preeclampsia by the FMF triple test is 250. The key to maintaining optimal screening performance is to establish standardized protocols for biomarker measurements and regular biomarker quality assessment, as inaccurate measurement can affect screening performance. Tools frequently used to assess quality control include the cumulative sum and target plot. Cumulative sum is a sensitive method to detect small shifts over time, and point of shift can be easily identified. Target plot is a tool to evaluate deviation from the expected multiple of median and the expected median of standard deviation. Target plot is easy to interpret and visualize. However, it is insensitive to detecting small deviations. Adherence to well-defined protocols for the measurements of mean arterial pressure, uterine artery pulsatility index, and placental growth factor is required. This article summarizes the existing literature on the different methods, recommendations by professional organizations, quality assessment of different components of risk assessment, and clinical implementation of the first trimester screening for preeclampsia.

Prospective Evaluation of International Prediction of Pregnancy Complications Collaborative Network Models for Prediction of Preeclampsia: Role of Serum sFlt-1 at 11-13 Weeks' Gestation

The study aimed to investigate whether serum sFlt-1 (soluble fms-like tyrosine kinase-1) at 11-13 weeks' gestation in pregnancies that subsequently developed preeclampsia was different from those without preeclampsia and compare screening performance of the International Prediction of Pregnancy Complications (IPPIC) reported models, which include various combinations of maternal factors, systolic blood pressure, diastolic blood pressure, PlGF (placental growth factor) and sFlt-1 and the competing risk (CR) models, which include various combinations of maternal factors, mean arterial pressure (MAP) and PlGF for predicting any-onset, early-onset, and late-onset preeclampsia. This was a prospective multicenter study in 7877 singleton pregnancies. The differences of the predictive performance between the IPPIC and CR models were compared. There were 141 women (1.79%) who developed preeclampsia, including 13 cases (0.17%) of early-onset preeclampsia and 128 cases (1.62%) of late-onset preeclampsia. In pregnancies that developed preeclampsia compared to unaffected pregnancies, median serum sFlt-1 levels and its MoMs were not significantly different (p>0.05). There was no significant association between gestational age at delivery and log₁₀ sFlt-1 and log₁₀ sFlt-1 MoM (p>0.05). The areas under the curve of CR models were significantly higher than the IPPIC models for the prediction of any-onset and late-onset preeclampsia but not for early-onset preeclampsia. In conclusion, there are no significant differences in the maternal serum sFlt-1 levels at 11-131 weeks' gestation between women who subsequently develop preeclampsia and those who do not. Moreover, the CR models for the prediction of any-onset and late-onset preeclampsia perform better than the IPPIC reported model.

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.

ACC-AHA Diagnostic Criteria for Hypertension in Pregnancy Identifies Patients at Intermediate Risk of Adverse Outcomes

OBJECTIVE

The aim of the study is to compare maternal and neonatal outcomes among patients who are normotensive, hypertensive by Stage I American College of Cardiology-American Heart Association (ACC-AHA) criteria, and hypertensive by American College of Obstetricians and Gynecologists (ACOG) criteria.

STUDY DESIGN

Secondary analysis of a prospective first trimester cohort study between 2007 and 2010 at three institutions in Baltimore, MD, was conducted. Blood pressure at 11 to 14 weeks' gestation was classified as (1) normotensive (systolic blood pressure [SBP] <130 mm Hg and diastolic blood pressure [DBP] <80 mm Hg); (2) hypertensive by Stage I ACC-AHA criteria (SBP 130-139 mm Hg or DBP 80-89 mm Hg); or (3) hypertensive by ACOG criteria (SBP ≥140 mm Hg or DBP ≥90 mm Hg). Primary outcomes included preeclampsia, small for gestational age (SGA) neonate, and preterm birth.

RESULTS

Among 3,422 women enrolled, 2,976 with delivery data from singleton pregnancies of nonanomalous fetuses were included. In total, 20.2% met hypertension criteria (Stage I ACC-AHA n = 254, 8.5%; ACOG n = 347, 11.7%). The Stage I ACC-AHA group's risk for developing preeclampsia was threefold higher than the normotensive group (adjusted relative risk [aRR] 3.70, 95% confidence interval [CI] 2.40-5.70). The Stage I ACC-AHA group had lower preeclampsia risk than the ACOG group but the difference was not significant (aRR 0.87, 95% CI 0.55-1.37). The Stage I ACC-AHA group was more likely than the normotensive group to deliver preterm (aRR 1.44, 95% CI 1.02-2.01) and deliver an SGA neonate (aRR 1.51, 95% CI 1.07-2.12). The Stage I ACC-AHA group was less likely to deliver preterm compared with the ACOG group (aRR 0.65, 95% CI 0.45-0.93), but differences in SGA were not significant (aRR 1.31, 95% CI 0.84-2.03).

CONCLUSION

Pregnant patients with Stage I ACC-AHA hypertension in the first trimester had higher rates of preeclampsia, preterm birth, and SGA neonates compared with normotensive women. Adverse maternal and neonatal outcomes were numerically lower in the Stage I ACC-AHA group compared with the ACOG group, but these comparisons only reached statistical significance for preterm birth. Optimal pregnancy management for first trimester Stage I ACC-AHA hypertension requires active study.

KEY POINTS

· Women with first trimester American College of Cardiology-American Heart Association (ACC-AHA) Stage I hypertension were more likely to develop preeclampsia, deliver preterm, and deliver a small-for-gestational age neonate than normotensive women.. · Women with first trimester American College of Obstetricians and Gynecologists (ACOG) hypertension (consistent with stage II ACC-AHA hypertension) had the highest numeric rate of adverse outcomes; however, compared with Stage I ACC-AHA hypertension, there was only statistically significant difference for preterm delivery.. · The risk profile for pregnant women with Stage I ACC-AHA hypertension and women with hypertension by conventional ACOG criteria may be more similar than previously understood..

Model for Early Prediction of Preeclampsia: A Nested Case Controlled Study in Indian Women

Purpose

Preeclampsia (PE) affects 5-7% of the pregnancies worldwide, and is one of the most dreaded disorders of pregnancy contributing to maternal and neonatal mortality. PE is mostly presented in the third trimester of pregnancy. Here, we used serum placental growth factor (PIGF) and soluble fms-like tyrosine kinase-1 (sFlt-1) to develop a model for predicting PE in Indian women in early second trimester.

Methods

In this case-control study, a total 1452 healthy pregnant women were recruited. Blood samples were collected at the following gestational weeks (GWs), 12-20 (GW1), 21-28 (GW2) and 29-term (GW3), and post-delivery. Body mass index (BMI) was calculated by anthropometric measurements. Serum sFlt-1, PIGF and VEGF were analyzed by ELISA. A predictive model for PE was developed using multivariable logistic regression analysis.

Results

In PE cases, serum PlGF and VEGF levels were significantly lower at each GW, while serum sFlt-1 was lower only at GW1, relative to age-matched controls, (n = 132/group). Age-matched comparison between PE cases and controls indicated that sFlt-1 was associated with decreased PE outcome (Odds ratio. OR = 0.988, CI = 0.982-0.993), whereas sFlt-1/PlGF ratio (OR = 1.577, CI = 1.344-1.920) and BMI (OR = 1.334, CI = 1.187-1.520) were associated with increased PE outcome. Logistic regression was used to develop a predictive model for PE at GW1. Using testing dataset, model was externally validated which resulted in 88% accuracy in predicting PE cases at 0.5 probability cutoff.

Conclusion

Prediction model using sFlt-1, sFlt-1/PlGF ratio and BMI may be useful to predict PE as early as 12-20 weeks in women with optimal sensitivity and specificity.

External validation of prognostic models predicting pre-eclampsia: 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 during pregnancy is required to plan management. Although there are many published prediction models for pre-eclampsia, few have been validated in external data. Our objective was to externally validate published prediction models for pre-eclampsia using individual participant data (IPD) from UK studies, to evaluate whether any of the models can accurately predict the condition when used within the UK healthcare setting.

METHODS

IPD from 11 UK cohort studies (217,415 pregnant women) within the International Prediction of Pregnancy Complications (IPPIC) pre-eclampsia network contributed to external validation of published prediction models, identified by systematic review. Cohorts that measured all predictor variables in at least one of the identified models and reported pre-eclampsia as an outcome were included for validation. We reported the model predictive performance as discrimination (C-statistic), calibration (calibration plots, calibration slope, calibration-in-the-large), and net benefit. Performance measures were estimated separately in each available study and then, where possible, combined across studies in a random-effects meta-analysis.

RESULTS

Of 131 published models, 67 provided the full model equation and 24 could be validated in 11 UK cohorts. Most of the models showed modest discrimination with summary C-statistics between 0.6 and 0.7. The calibration of the predicted compared to observed risk was generally poor for most models with observed calibration slopes less than 1, indicating that predictions were generally too extreme, although confidence intervals were wide. There was large between-study heterogeneity in each model's calibration-in-the-large, suggesting poor calibration of the predicted overall risk across populations. In a subset of models, the net benefit of using the models to inform clinical decisions appeared small and limited to probability thresholds between 5 and 7%.

CONCLUSIONS

The evaluated models had modest predictive performance, with key limitations such as poor calibration (likely due to overfitting in the original development datasets), substantial heterogeneity, and small net benefit across settings. The evidence to support the use of these prediction models for pre-eclampsia in clinical decision-making is limited. Any models that we could not validate should be examined in terms of their predictive performance, net benefit, and heterogeneity across multiple UK settings before consideration for use in practice.

TRIAL REGISTRATION

PROSPERO ID: CRD42015029349 .

The competing risk approach for prediction of preeclampsia

The established method of the assessment of the risk for development of preeclampsia is to identify risk factors from maternal demographic characteristics and medical history; in the presence of such factors, the patient is classified as high risk and in their absence as low risk. Although this approach is simple to perform, it has poor performance of the prediction of preeclampsia and does not provide patient-specific risks. This review describes a new approach that allows the estimation of patient-specific risks of delivery with preeclampsia before any specified gestational age by maternal demographic characteristics and medical history with biomarkers obtained either individually or in combination at any stage in pregnancy. In the competing risks approach, every woman has a personalized distribution of gestational age at delivery with preeclampsia; whether she experiences preeclampsia or not before a specified gestational age depends on competition between delivery before or after the development of preeclampsia. The personalized distribution comes from the application of Bayes theorem to combine a previous distribution, which is determined from maternal factors, with likelihoods from biomarkers. As new data become available, what were posterior probabilities take the role as the previous probability, and data collected at different stages are combined by repeating the application of Bayes theorem to form a new posterior at each stage, which allows for dynamic prediction of preeclampsia. The competing risk model can be used for precision medicine and risk stratification at different stages of pregnancy. In the first trimester, the model has been applied to identify a high-risk group that would benefit from preventative therapeutic interventions. In the second trimester, the model has been used to stratify the population into high-, intermediate-, and low-risk groups in need of different intensities of subsequent monitoring, thereby minimizing unexpected adverse perinatal events. The competing risks model can also be used in surveillance of women presenting to specialist clinics with signs or symptoms of hypertensive disorders; combination of maternal factors and biomarkers provide patient-specific risks for preeclampsia that lead to personalized stratification of the intensity of monitoring, with risks updated on each visit on the basis of biomarker measurements.

First-trimester maternal serum alpha fetoprotein is associated with ischemic placental disease

BACKGROUND

While elevated second-trimester maternal serum alpha fetoprotein has been associated with adverse pregnancy outcomes, the utility of first-trimester maternal serum alpha fetoprotein in predicting these outcomes is limited. Some laboratories have been including maternal serum alpha fetoprotein as part of the first-trimester analyte screening for aneuploidy and preeclampsia, offering its potential utility in predicting pregnancy outcomes.

OBJECTIVE

Our primary objective was to determine the association between elevated first-trimester maternal serum alpha fetoprotein and preeclampsia as well as ischemic placental disease (a composite of preeclampsia, fetal growth restriction, and/or placental abruption). Secondary outcomes included early-onset preeclampsia requiring delivery at <34 weeks gestation, fetal growth restriction, placental abruption, preterm delivery, fetal demise, and spontaneous abortion.

STUDY DESIGN

An institutional review board-approved multisite retrospective cohort study was performed including all patients with first-trimester maternal serum alpha fetoprotein as part of routine first-trimester aneuploidy screening from April 2015 through January 2017. Pregnancies with multiple gestations, known structural or chromosomal abnormalities, known malignancy, and incomplete delivery records were excluded. Delivery records were reviewed for baseline characteristics and adverse pregnancy outcomes. The optimal cutoff point for first-trimester maternal serum alpha fetoprotein to predict these outcomes was assessed, and an elevated maternal serum alpha fetoprotein was considered >2.0 multiple of the median. A Fisher exact test and odds ratios were used to determine the association between elevated first-trimester maternal serum alpha fetoprotein and adverse pregnancy outcomes. Spearman correlation coefficient assessed the relationship between first- and second-trimester maternal serum alpha fetoprotein.

RESULTS

Of 1478 patients with first-trimester maternal serum alpha fetoprotein, 1280 had complete records available for review (86.6%). There was no association demonstrated between elevated first-trimester maternal serum alpha fetoprotein (>2.0 multiple of the median) and the primary outcome, overall preeclampsia (5.8% vs 4.6%, odds ratio, 1.29, 95% confidence interval, 0.58-2.91). However, there was an increased incidence of ischemic placental disease, 15.8% vs 7.7% (odds ratio, 2.26, 95% confidence interval, 1.33-3.87) in those with an elevated alpha fetoprotein. Also, elevated first-trimester maternal serum alpha fetoprotein was associated with a higher incidence of fetal growth restriction (7.5% vs 2.3%, odds ratio, 3.40, 95% confidence interval, 1.56-7.42) and preterm birth (18.3% vs 10.3%, odds ratio, 1.95, 95% confidence interval, 1.18-3.21). Also, a positive correlation between first- and second-trimester maternal serum alpha fetoprotein was demonstrated (rho = 0.46, P < .0001).

CONCLUSION

Elevated first-trimester maternal serum alpha fetoprotein is associated with ischemic placental disease, fetal growth restriction, and preterm birth. This suggests that elevated maternal serum alpha fetoprotein may help to identify high risk pregnancies as early as the first trimester of pregnancy. Future studies are necessary to determine whether the addition of first-trimester maternal serum alpha fetoprotein to existing algorithms can improve the early detection of ischemic placental disease.

Systematic review of prediction models for gestational hypertension and preeclampsia

INTRODUCTION

Prediction models for gestational hypertension and preeclampsia have been developed with data and assumptions from developed countries. Their suitability and application for low resource settings have not been tested. This review aimed to identify and assess the methodological quality of prediction models for gestational hypertension and pre-eclampsia with reference to their application in low resource settings.

METHODS

Using combinations of keywords for gestational hypertension, preeclampsia and prediction models seven databases were searched to identify prediction models developed with maternal data obtained before 20 weeks of pregnancy and including at least three predictors (Prospero registration CRD 42017078786). Prediction model characteristics and performance measures were extracted using the CHARMS, STROBE and TRIPOD checklists. The National Institute of Health quality assessment tools for observational cohort and cross-sectional studies were used for study quality appraisal.

RESULTS

We retrieved 8,309 articles out of which 40 articles were eligible for review. Seventy-seven percent of all the prediction models combined biomarkers with maternal clinical characteristics. Biomarkers used as predictors in most models were pregnancy associated plasma protein-A (PAPP-A) and placental growth factor (PlGF). Only five studies were conducted in a low-and middle income country.

CONCLUSIONS

Most of the studies evaluated did not completely follow the CHARMS, TRIPOD and STROBE guidelines in prediction model development and reporting. Adherence to these guidelines will improve prediction modelling studies and subsequent application of prediction models in clinical practice. Prediction models using maternal characteristics, with good discrimination and calibration, should be externally validated for use in low and middle income countries where biomarker assays are not routinely available.

Gottesfeld-Hohler Memorial Foundation Risk Assessment for Early-Onset Preeclampsia in the United States: Think Tank Summary

Preeclampsia is responsible for significant maternal and neonatal morbidity and is associated with a substantial economic burden. Aspirin has been shown to be effective in decreasing the risk of preterm preeclampsia; however, there is no consensus on the target population for aspirin prophylaxis. In May 2018, the Gottesfeld-Hohler Memorial Foundation organized a working group meeting with the goal of identifying the optimal preeclampsia risk-assessment strategy and consequent intervention in the United States. The meeting brought together experts from the leading professional societies. We discussed available literature and trends in preeclampsia risk assessment, current professional guidelines for identifying women at risk for preeclampsia, prophylactic use of aspirin in the United States and Europe, cost-effectiveness data, and feasibility of implementation of different assessment tools and preventive strategies in the United States. We identified specific knowledge gaps and future research directions in preeclampsia risk assessment and prevention that need to be addressed before practice change.

A comparison of first trimester blood pressures obtained at the time of first trimester pre-eclampsia screening and those obtained during prenatal care visits

OBJECTIVE

To determine if enrollment blood pressures in a study on first trimester preeclampsia prediction significantly differed from those obtained during routine prenatal care visits in the first trimester.

STUDY DESIGN

Women carrying a singleton gestation were prospectively enrolled in a first trimester study on preeclampsia prediction, and had systolic and diastolic blood pressure (SBP, DBP) measured at the time of enrollment. Blood pressure was also measured with the same technique by clinic nurses during the routine prenatal visits throughout the first trimester of pregnancy (9-14 weeks). The enrollment-BP (E-BP) and average first trimester-BP (aFT-BP) were compared using a paired samples t-test or Wilcoxon test, as appropriate. Smokers and patients on antihypertensive medications were excluded from the analysis. test.

RESULTS

644 women had prenatal care in the primary study center and met study criteria. The mean gestational age at study enrollment was 12.5 weeks. No significant difference was found between E-SBP and aFT-SBP (p = 0.10). Enrollment DBP and mean arterial pressure (MAP) were significantly lower than the aFT- DBP and -MAP (median DPB 67 vs 70 mm Hg and median MAP 83.7 vs 85 mmHg, respectively, p < 0.001). However, the difference was not clinically relevant (3 mmHg for DBP, and 1.3 mmHg for MAP).

CONCLUSIONS

Blood pressures obtained in a setting of preeclampsia screening are not higher than those obtained during regular prenatal care in the first trimester. This suggests that the setting in which pre-eclampsia screening is performed is unlikely to be a confounder for blood pressure measurements and the risk assessment.

FIRST TRIMESTER SCREENING FOR PREECLAMPSIA - A SYSTEMATIC REVIEW

Objective: To increase the detection rate of preterm preeclampsia (PE) first trimester combined screening tests are being developed. The aim of this review is to create an overview of the currently investigated screening markers, algorithms and their validations.Methods: Comprehensive review of the literature concerning first trimester screening for PEResults and conclusions: Studies investigating a total of 160 biochemical, 6 biophysical and 14 ultrasound markers could be identified. Of the 21 algorithms published, mainly the algorithm published by the Fetal Medicine Foundation London has been validated. This algorithm performes significantly better than screening by anamnestic risk factors only.

The prediction of early preeclampsia: Results from a longitudinal proteomics study

OBJECTIVES

To identify maternal plasma protein markers for early preeclampsia (delivery <34 weeks of gestation) and to determine whether the prediction performance is affected by disease severity and presence of placental lesions consistent with maternal vascular malperfusion (MVM) among cases.

STUDY DESIGN

This longitudinal case-control study included 90 patients with a normal pregnancy and 33 patients with early preeclampsia. Two to six maternal plasma samples were collected throughout gestation from each woman. The abundance of 1,125 proteins was measured using high-affinity aptamer-based proteomic assays, and data were modeled using linear mixed-effects models. After data transformation into multiples of the mean values for gestational age, parsimonious linear discriminant analysis risk models were fit for each gestational-age interval (8-16, 16.1-22, 22.1-28, 28.1-32 weeks). Proteomic profiles of early preeclampsia cases were also compared to those of a combined set of controls and late preeclampsia cases (n = 76) reported previously. Prediction performance was estimated via bootstrap.

RESULTS

We found that 1) multi-protein models at 16.1-22 weeks of gestation predicted early preeclampsia with a sensitivity of 71% at a false-positive rate (FPR) of 10%. High abundance of matrix metalloproteinase-7 and glycoprotein IIbIIIa complex were the most reliable predictors at this gestational age; 2) at 22.1-28 weeks of gestation, lower abundance of placental growth factor (PlGF) and vascular endothelial growth factor A, isoform 121 (VEGF-121), as well as elevated sialic acid binding immunoglobulin-like lectin 6 (siglec-6) and activin-A, were the best predictors of the subsequent development of early preeclampsia (81% sensitivity, FPR = 10%); 3) at 28.1-32 weeks of gestation, the sensitivity of multi-protein models was 85% (FPR = 10%) with the best predictors being activated leukocyte cell adhesion molecule, siglec-6, and VEGF-121; 4) the increase in siglec-6, activin-A, and VEGF-121 at 22.1-28 weeks of gestation differentiated women who subsequently developed early preeclampsia from those who had a normal pregnancy or developed late preeclampsia (sensitivity 77%, FPR = 10%); 5) the sensitivity of risk models was higher for early preeclampsia with placental MVM lesions than for the entire early preeclampsia group (90% versus 71% at 16.1-22 weeks; 87% versus 81% at 22.1-28 weeks; and 90% versus 85% at 28.1-32 weeks, all FPR = 10%); and 6) the sensitivity of prediction models was higher for severe early preeclampsia than for the entire early preeclampsia group (84% versus 71% at 16.1-22 weeks).

CONCLUSION

We have presented herein a catalogue of proteome changes in maternal plasma proteome that precede the diagnosis of preeclampsia and can distinguish among early and late phenotypes. The sensitivity of maternal plasma protein models for early preeclampsia is higher in women with underlying vascular placental disease and in those with a severe phenotype.

Aspirin delays the development of preeclampsia

BACKGROUND

In the Combined Multimarker Screening and Randomized Patient Treatment with Aspirin for Evidence-Based Preeclampsia Prevention trial, risks of preterm preeclampsia were obtained from the competing risk model. Consenting women with risks of greater than 1 in 100 were randomized to treatment with aspirin or placebo. The trial showed strong evidence of an effect (odds ratio, 0.38, 95% confidence interval, 0.20-0.74) on the incidence of preterm preeclampsia, which was the primary outcome of Aspirin for Evidence-Based Preeclampsia Prevention. There was a small and insignificant effect on the incidence of term preeclampsia, which was a secondary outcomes (odds ratio, 0.95, 95% confidence interval, 0.64-1.39). These differential effects on term and preterm preeclampsia could reflect a mechanism in which the action of aspirin is to delay the delivery with preeclampsia, thereby converting what would be, without treatment, preterm preeclampsia to term preeclampsia.

OBJECTIVE

The objective of the study was to examine the hypothesis that the effect of aspirin is to delay the time of delivery in women who have preeclampsia.

STUDY DESIGN

This was an unplanned exploratory analysis of data from the Aspirin for Evidence-Based Preeclampsia Prevention trial. The delay hypothesis predicts that in groups for which preterm preeclampsia, without aspirin, were infrequent relative to term preeclampsia, a reduction in term preeclampsia would be expected because few cases of preterm preeclampsia would be converted to term preeclampsia. In contrast, in groups for which preterm preeclampsia were frequent relative to term preeclampsia, the conversion of preterm preeclampsia to term preeclampsia by aspirin would reduce or even reverse any effect on the incidence term preeclampsia. This is examined using the Aspirin for Evidence-Based Preeclampsia Prevention trial data by analysis of the effect of aspirin on the incidence of term preeclampsia stratified according to the risk of preterm preeclampsia at randomization. Given that women were included in Aspirin for Evidence-Based Preeclampsia Prevention with risks of preterm preeclampsia >1 in 100, a risk cutoff if 1 in 50 was used to define higher risk and lower risk strata. A statistical model in which the effect of aspirin is to delay the gestational age at delivery was fitted to the Aspirin for Evidence-Based Preeclampsia Prevention trial data and the consistency of the predictions from this model with the observed incidence was demonstrated.

RESULTS

In the lower-risk group (<1 in 50), there was a reduction in the incidence of term preeclampsia (odds ratio, 0.62, 95% confidence interval, 0.29-1.30). In contrast, in the higher risk group (≥1 in 50) there was a small increase in the incidence of term- preeclampsia (odds ratio 1.11, 95% confidence interval, 0.71- .75). Although these effects fail to achieve significance, they are consistent with the delay hypothesis. Within the framework of the aspirin-related delay hypothesis, the effect of aspirin was to delay the gestational age at delivery with preeclampsia by an estimated 4.4 weeks (95% confidence interval, 1.4-7.1 weeks) for those that in the placebo group would be delivered at 24 weeks and the effect decreased by an estimated 0.23 weeks (95% confidence interval, 0.021-0.40 weeks) for each week of gestation so that at 40⁺⁰ weeks, the estimated delay was by 0.8 weeks (95% confidence interval, -0.03 to 1.7 weeks).

CONCLUSION

The Aspirin for Evidence-Based Preeclampsia Prevention trial data are consistent with the hypothesis that aspirin delays the gestational age at delivery with preeclampsia.

Screening for preeclampsia in the first trimester of pregnancy in routine clinical practice in Hungary

We aimed to evaluate the contribution of different factors in the Fetal Medicine Foundation algorithms for preeclampsia (PE) risk calculation during first-trimester screening in Hungary. We selected subjects for the nested case-control study from a prospective cohort of 2545 low-risk pregnancies. Eighty-two patients with PE and 82 gestational age-matched controls were included. Individual PE risk was calculated using two risk-assessing softwares. Using Astraia 2.3.1, considering maternal characteristics and biophysical parameters only, detection rates (DR) were 63.6% for early-PE and 67.6% for late-PE. When we added placenta associated plasma protein A (PAPP-A) to the risk calculation, DRs decreased to 54.5% and 64.8% respectively. Using Astraia 2.8.2 with maternal characteristics and biophysical parameters resulted in the DRs of 63.6% (early-PE) and 56.3% (late-PE). If we added PAPP-A to the risk calculation, DRs improved to 72.7% and 54.9%. The addition of placental growth factor (PlGF) did not increase detection rates in either calculation. In conclusion, using maternal characteristics, biophysical parameters, and PAPP-A, an acceptable screening efficacy could be achieved for early-PE during first-trimester screening. Since PlGF did not improve efficacy in our study, we suggest setting new standard curves for PlGF in Eastern European pregnant women, and the evaluation of novel biochemical markers.

External validation of prognostic models for preeclampsia in a Dutch multicenter prospective cohort

OBJECTIVE

To perform an external validation of all published prognostic models for first-trimester prediction of the risk of developing preeclampsia (PE).

METHODS

Women <14 weeks of pregnancy were recruited in the Netherlands. All systematically identified prognostic models for PE that contained predictors commonly available were eligible for external validation.

RESULTS

3,736 women were included; 87 (2.3%) developed PE. Calibration was poor due to overestimation. Discrimination of 9 models for LO-PE ranged from 0.58 to 0.71 and of 9 models for all PE from 0.55 to 0.75.

CONCLUSION

Only a few easily applicable prognostic models for all PE showed discrimination above 0.70, which is considered an acceptable performance.

Biochemical Markers for Prediction of Hypertensive Disorders of Pregnancy

Background

Gestational hypertension (GH) and pre eclampsia (PE) are the most common gestational complications. Several placental biochemical markers are used to predict GH/PE, but with conflicting results.

Methods

The study aim was to estimate the biochemical markers’ ability to predict hypertensive disorders in pregnancy. On the first ultrasonographic examination, 104 healthy pregnant women were recruited. At the regular pregnancy check-ups, BMI, blood pressure, occurrence of gestational hypertension (early or late onset), preeclampsia, eclampsia and other complications were recorded. Serum concentrations (in multiples of median – MoM) of human chorionic gonadotropin (HCG) and pregnancyassociated plasma protein A (PAPPA) were measured from the 11th to 14th gestational week, while HCG, alpha feto protein (AFP), estriol and inhibin were determined between the 16th and 19th gestational week.

Results

Hypertensive disorders throughout pregnancy were diagnosed in 20.2% women. Early-onset GH was registered in 7 and PE in 6 patients, while 14 had late-onset GH and 10 additional women PE. There were no significant differences (p≥0.05) in biochemical markers concentrations between women with and without GH/PE. PAPPA levels in the first and HCG in the second trimester correlated with early and late GH/PE. Moreover, higher AFP concentrations were registered in women with preeclampsia signs/symptoms. According to ROC analysis, AFP>1.05 MoM properly identified 80% of GH/PE cases. Obtained models imply that HCG, PAPPA and AFP should be used for GH/PE prediction.

Conclusions

Biochemical markers HCG, PAPPA and AFP could be useful in predicting gestational hypertension and preeclampsia. However, different markers should be used for early and late onset GH/PE.

Two-stage screening for preterm preeclampsia at 11-13 weeks' gestation

BACKGROUND

Screening for preeclampsia at 11-13 weeks' gestation by a combination of maternal factors, mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor (triple test) can predict about 90% of preeclampsia, with delivery at <32 weeks (early-preeclampsia), and 75% of preeclampsia with delivery at <37 weeks (preterm preeclampsia), at a screen-positive rate of 10%. In pregnancies identified as being at high risk for preeclampsia by such screening, administration of aspirin (150 mg/d from 11 to 14 weeks' gestation to 36 weeks) reduces the rate of early preeclampsia by about 90% and preterm preeclampsia by about 60%. Recording of maternal history and blood pressure are part of routine prenatal care, but measurement of uterine artery pulsatility index and placental growth factor require additional costs.

OBJECTIVE

To explore the possibility of carrying out first-stage screening in the whole population by maternal factors alone or a combination of maternal factors, mean arterial pressure and uterine artery pulsatility index or maternal factors, mean arterial pressure, and placental growth factor and proceeding to second-stage screening by the triple test only for a subgroup of the population selected on the basis of the risk derived from first-stage screening.

STUDY DESIGN

The data for this study were derived from prospective nonintervention screening for preeclampsia at 11⁺⁰ to 13⁺⁶ weeks' gestation in 61,174 singleton pregnancies. Patient-specific risks of delivery with preeclampsia at <37 and <32 weeks' gestation were calculated using the competing risks model to combine the prior distribution of the gestational age at delivery with preeclampsia, obtained from maternal characteristics and medical history, with various combinations of multiple of the median values of mean arterial pressure, uterine artery pulsatility index, and placental growth factor. We estimated the detection rate of preterm-preeclampsia and early-preeclampsia at overall screen-positive rate of 10%, 15%, and 20% from a policy in which first-stage screening of the whole population is carried out by some of the components of the triple test and second-stage screening by the full triple test on women selected on the basis of results from first-stage screening.

RESULTS

If the method of first-stage screening is maternal factors, then measurements of mean arterial pressure, uterine artery pulsatility index, and placental growth factor can be reserved for only 70% of the population, achieving similar detection rate and screen-positive rate as with screening the whole population with the triple test. In the case of first-stage screening by maternal factors, mean arterial pressure, and uterine artery pulsatility index, then measurement of placental growth factor can be reserved for only 30-40% of the population, and if first-stage screening is by maternal factors, mean arterial pressure, and placental growth factor, measurement of uterine artery pulsatility index can be reserved for only 20-30% of the population. Empirical results were consistent with model-based performance.

CONCLUSION

Two-stage screening and biomarker testing for only part of the population will have financial benefits over conducting the test for the entire population.

Predictive performance of the competing risk model in screening for preeclampsia

BACKGROUND

The established method of screening for preeclampsia is to identify risk factors from maternal demographic characteristics and medical history; in the presence of such factors the patient is classified as high risk and in their absence as low risk. However, the performance of such an approach is poor. We developed a competing risks model, which allows combination of maternal factors (age, weight, height, race, parity, personal and family history of preeclampsia, chronic hypertension, diabetes mellitus, systemic lupus erythematosus or antiphospholipid syndrome, method of conception and interpregnancy interval), with biomarkers to estimate the individual patient-specific risks of preeclampsia requiring delivery before any specified gestation. The performance of this approach is by far superior to that of the risk scoring systems.

OBJECTIVE

The objective of the study was to examine the predictive performance of the competing risks model in screening for preeclampsia by a combination of maternal factors, mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor, referred to as the triple test, in a training data set for the development of the model and 2 validation studies.

STUDY DESIGN

The data for this study were derived from 3 previously reported prospective, nonintervention, multicenter screening studies for preeclampsia in singleton pregnancies at 11⁺⁰ to 13⁺⁶ weeks' gestation. In all 3 studies, there was recording of maternal factors and biomarkers and ascertainment of outcome by appropriately trained personnel. The first study of 35,948 women, which was carried out between February 2010 and July 2014, was used to develop the competing risks model for prediction of preeclampsia and is therefore considered to be the training set. The 2 validation studies were comprised of 8775 and 16,451 women, respectively, and they were carried out between February and September 2015 and between April and December 2016, respectively. Patient-specific risks of delivery with preeclampsia at <34, <37, and <41⁺³ weeks' gestation were calculated using the competing risks model and the performance of screening for preeclampsia by maternal factors alone and the triple test in each of the 3 data sets was assessed. We examined the predictive performance of the model by first, the ability of the model to discriminate between the preeclampsia and no-preeclampsia groups using the area under the receiver operating characteristic curve and the detection rate at fixed screen-positive rate of 10%, and second, calibration by measurements of calibration slope and calibration in the large.

RESULTS

The detection rate at the screen-positive rate of 10% of early-preeclampsia, preterm-preeclampsia, and all-preeclampsia was about 90%, 75%, and 50%, respectively, and the results were consistent between the training and 2 validation data sets. The area under the receiver operating characteristic curve was >0.95, >0.90, and >0.80, respectively, demonstrating a very high discrimination between affected and unaffected pregnancies. Similarly, the calibration slopes were very close to 1.0, demonstrating a good agreement between the predicted risks and observed incidence of preeclampsia. In the prediction of early-preeclampsia and preterm-preeclampsia, the observed incidence in the training set and 1 of the validation data sets was consistent with the predicted one. In the other validation data set, which was specifically designed for evaluation of the model, the incidence was higher than predicted, presumably because of better ascertainment of outcome. The incidence of all-preeclampsia was lower than predicted in all 3 data sets because at term many pregnancies deliver for reasons other than preeclampsia, and therefore, pregnancies considered to be at high risk for preeclampsia that deliver for other reasons before they develop preeclampsia can be wrongly considered to be false positives.

CONCLUSION

The competing risks model provides an effective and reproducible method for first-trimester prediction of early preeclampsia and preterm preeclampsia as long as the various components of screening are carried out by appropriately trained and audited practitioners. Early prediction of preterm preeclampsia is beneficial because treatment of the high-risk group with aspirin is highly effective in the prevention of the disease.

Maternal blood-pressure trends throughout pregnancy and development of pre-eclampsia in women receiving first-trimester aspirin prophylaxis

OBJECTIVES

To study women who initiated aspirin in the first trimester for high risk of pre-eclampsia, and compare blood-pressure trends throughout pregnancy between those with normal outcome and those who subsequently developed pre-eclampsia.

METHODS

Women were enrolled into a prospective observational study at 9-14 weeks' gestation. This was a secondary analysis of those who started daily doses of 81 mg of aspirin before 16 weeks for increased risk of pre-eclampsia based on maternal history and bilateral uterine artery notching. Enrollment characteristics and blood-pressure measurements throughout gestation were compared between women who did and those who did not develop pre-eclampsia.

RESULTS

Of the 237 women who initiated first-trimester aspirin prophylaxis, 29 (12.2%) developed pre-eclampsia. A total of 2881 serial blood-pressure measurements obtained between 4 and 41 weeks' gestation (747 in the first trimester, 1008 in the second and 1126 in the third) showed that women with pre-eclampsia started pregnancy with higher blood pressure and maintained this trend despite taking aspirin (mean arterial blood pressure in women with pre-eclampsia = (0.13 × gestational age (weeks)) + 93.63, vs (0.11 × gestational age (weeks)) + 82.61 in those without; P < 0.005). First-trimester diastolic and second-trimester systolic blood pressure were independent risk factors for pre-eclampsia (β = 1.087 and 1.050, respectively; r²  = 0.24, P < 0.0001). When average first-trimester diastolic blood pressure was >74 mmHg, the odds ratio for pre-eclampsia was 6.5 (95% CI, 2.8-15.1; P < 0.001) and that for pre-eclampsia before 34 weeks was 14.6 (95% CI, 1.72-123.5; P = 0.004). If, in addition, average second-trimester systolic blood pressure was >125 mmHg, the odds ratio for pre-eclampsia was 9.4 (95% CI, 4.1-22.4; P < 0.001) and that for early-onset disease was 34.6 (95% CI, 4.1-296.4; P = 0.004).

CONCLUSION

In women treated with prophylactic aspirin from the first trimester, those who develop pre-eclampsia have significantly and sustained higher blood pressure from the onset of pregnancy compared with those who do not develop pre-eclampsia. This raises the possibility that mildly elevated blood pressure predisposes women to abnormal placentation, which then acts synergistically with elevated blood pressure to predispose such women to pre-eclampsia to a degree that is incompletely mitigated by aspirin. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

Evaluation of serum biomarkers for detection of preeclampsia severity in pregnant women

Objectives

To determine serum biomarkers in detection of preeclampsia severity among pregnant women.

Methods

Among 450 pregnant women with various severity of preeclampsia, serum biomarkers ofaspartate aminotransferase (AST), alanine aminotransferase (ALT), lactate dehydrogenase (LDH), hemoglobin (Hb), platelet count (PLT), uric acid, direct bilirubin, total bilirubin, creatinine, and alkaline phosphatase were compared using area under the Receiver operating characteristic (ROC) curve and Area Under the Curve (AUC).

Results

The mean age of women was 30.63±6.43 years and with mean gestational age of 34.69±3.97 weeks. The mean level of LDH, ALT, uric acid, and creatinine were significantly higher in the women with severe type of preeclampsia compared to those with mild type. LDH level had ROC and AUC of more than 0.80, with highest sensitivity, and moderatespecificityin comparison to other markers.

Conclusion

Biomarkers such as ALT, uric acid, and LDH were shown to be prognostic in detection of theseverity of preeclampsia. LDH was demonstrated to significantly be a better prognostic test in detection of preeclampsia severity.

Prediction and prevention of pre-eclampsia in Asian subpopulation

The benefit of the early administration of aspirin to reduce preterm pre-eclampsia among screened positive European women from multivariate algorithmic approach (ASPRE trial) has opened an intense debate on the feasibility of universal screening. This review aims to assess the new perspectives in the combined screening of pre-eclampsia in the first trimester of pregnancy and the chances for prevention using low-dose aspirin with special emphasis on the particularities of the Asian population. PubMed, CENTRAL and Embase databases were searched from inception until 15 November 2017 using combinations of the search terms: preeclampsia, Asian, prenatal screening, early prediction, ultrasonography, pregnancy, biomarker, mean arterial pressure, soluble fms-like tyrosine kinase-1, placental growth factor, pregnancy-associated plasma protein-A and pulsatility index. This is not a systematic review or meta-analysis, so the risk of bias of the selected published articles and heterogeneity among the studies need to be considered. The prevalence of pre-eclampsia and serum levels of biochemical markers in Asian are different from Caucasian women; hence, Asian ethnicity needs to be corrected for in the algorithmic assessment of multiple variables to improve the screening performance. Aspirin prophylaxis may still be viable in Asian women, but resource implication needs to be considered. Asian ethnicity should be taken into account before implementing pre-eclampsia screening strategies in the region. The variables included can be mixed and matched to achieve an optimal performance that is appropriate for economical restriction in individual countries.

First-trimester screening for early and late preeclampsia using maternal characteristics, biomarkers, and estimated placental volume

BACKGROUND

Preeclampsia is a major cause of perinatal morbidity and mortality. First-trimester screening has been shown to be effective in selecting patients at an increased risk for preeclampsia in some studies.

OBJECTIVE

We sought to evaluate the feasibility of screening for preeclampsia in the first trimester based on maternal characteristics, medical history, biomarkers, and placental volume.

STUDY DESIGN

This is a prospective observational nonintervention cohort study in an unselected US population. Patients who presented for an ultrasound examination between 11-13+6 weeks' gestation were included. The following parameters were assessed and were used to calculate the risk of preeclampsia: maternal characteristics (demographic, anthropometric, and medical history), maternal biomarkers (mean arterial pressure, uterine artery pulsatility index, placental growth factor, pregnancy-associated plasma protein A, and maternal serum alpha-fetoprotein), and estimated placental volume. After delivery, medical records were searched for the diagnosis of preeclampsia. Detection rates for early-onset preeclampsia (<34 weeks' gestation) and later-onset preeclampsia (≥34 weeks' gestation) for 5% and 10% false-positive rates using various combinations of markers were calculated.

RESULTS

We screened 1288 patients of whom 1068 (82.99%) were available for analysis. In all, 46 (4.3%) developed preeclampsia, with 13 (1.22%) having early-onset preeclampsia and 33 (3.09%) having late-onset preeclampsia. Using maternal characteristics, serum biomarkers, and uterine artery pulsatility index, the detection rate of early-onset preeclampsia for either 5% or 10% false-positive rate was 85%. With the same protocol, the detection rates for preeclampsia with delivery <37 weeks were 52% and 60% for 5% and 10% false-positive rates, respectively. Based on maternal characteristics, the detection rates for late-onset preeclampsia were 15% and 48% for 5% and 10%, while for preeclampsia at ≥37 weeks' gestation the detection rates were 24% and 43%, respectively. The detection rates for late-onset preeclampsia and preeclampsia with delivery at >37 weeks' gestation were not improved by the addition of biomarkers.

CONCLUSION

Screening for preeclampsia at 11-13+6 weeks' gestation using maternal characteristics and biomarkers is associated with a high detection rate for a low false-positive rate. Screening for late-onset preeclampsia yields a much poorer performance. In this study the utility of estimated placental volume and mean arterial pressure was limited but larger studies are needed to ultimately determine the effectiveness of these markers.

How do maternal factors impact preeclampsia prediction in Brazilian population?

Objective: To evaluate the impacts of maternal risk factors described by the Fetal Medicine Foundation's 2012 algorithm (FMF2012) in a Brazilian population. Methods: All singleton pregnancies submitted to first-trimester preeclampsia (PE) screening using the FMF2012 algorithm were considered for study inclusion. Maternal factors, recorded via a patient questionnaire, were described and compared between PE outcome groups. A Gaussian regression model was derived to measure the effects of maternal factors, and to identify factors that contributed significantly (p < .05) to the alteration of gestational age at delivery, in pregnancies with PE. Results: Of the 1934 cases considered for study inclusion, the final sample consisted of 1531 cases. The sample included 120 (7.8%) cases of PE, of which 26 (1.7%) were preterm PE (PE < 37 weeks) and 11 (0.72%) were early PE (PE < 34 weeks). The PE rate did not differ according to ethnicity, smoking, family history of PE, or use of assisted reproductive technology. Significant differences (p < .05) between the normal and PE groups in maternal age, maternal weight, previous history of PE, chronic hypertension, and types 1 and 2 diabetes were detected. Conclusions: The significance and magnitude of associations of maternal factors in our sample differed from those incorporated in the FMF2012 model, implying the need to derive a fitted model for our population.

sFlt-1/PlGF for prediction of early-onset pre-eclampsia: STEPS (Study of Early Pre-eclampsia in Spain)

OBJECTIVE

A high ratio of soluble fms-like tyrosine kinase-1 (sFlt-1) to placental growth factor (PlGF) has been linked to pre-eclampsia (PE). We evaluated the sFlt-1/PlGF ratio as a predictive marker for early-onset PE in women at risk of PE.

METHODS

This prospective, Spanish, multicenter study included pregnant women with a risk factor for PE, including intrauterine growth restriction, PE, eclampsia or hemolysis, elevated liver enzymes and low platelet count syndrome in previous pregnancy, pregestational diabetes or abnormal uterine artery Doppler. The primary objective was to show that the sFlt-1/PlGF ratio at 20, 24 and 28 weeks' gestation was predictive of early-onset PE (< 34 + 0 weeks). Serum sFlt-1 and PlGF were measured at 20, 24 and 28 weeks. Multivariate logistic regression was used to develop a predictive model.

RESULTS

A total of 819 women were enrolled, of which 729 were suitable for analysis. Of these, 78 (10.7%) women developed PE (24 early onset and 54 late onset). Median sFlt-1/PlGF ratio at 20, 24 and 28 weeks was 6.3 (interquartile range (IQR), 4.1-9.3), 4.0 (IQR, 2.6-6.3) and 3.3 (IQR, 2.0-5.9), respectively, for women who did not develop PE (controls); 14.5 (IQR, 5.5-43.7), 18.4 (IQR, 8.2-57.9) and 51.9 (IQR, 11.5-145.6) for women with early-onset PE; and 6.7 (IQR, 4.6-9.9), 4.7 (IQR, 2.8-7.2) and 6.0 (IQR, 3.8-10.5) for women with late-onset PE. Compared with early-onset PE, the sFlt-1/PlGF ratio was significantly lower in controls (P < 0.001 at each timepoint) and in women with chronic hypertension (P < 0.001 at each timepoint), gestational hypertension (P < 0.001 at each timepoint) and late-onset PE (P < 0.001 at each timepoint). A prediction model for early-onset PE was developed, which included the sFlt-1/PlGF ratio plus mean arterial pressure, being parous and previous PE, with areas under the receiver-operating characteristics curves of 0.86 (95% CI, 0.77-0.95), 0.91 (95% CI, 0.85-0.97) and 0.93 (95% CI, 0.86-0.99) at 20, 24 and 28 weeks, respectively, and was superior to models using the sFlt-1/PlGF ratio alone or uterine artery mean pulsatility index.

CONCLUSIONS

The sFlt-1/PlGF ratio can improve prediction of early-onset PE for women at risk of this condition. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

External validation of preexisting first trimester preeclampsia prediction models

OBJECTIVE

To validate the increasing number of prognostic models being developed for preeclampsia using our own prospective study.

STUDY DESIGN

A systematic review of literature that assessed biomarkers, uterine artery Doppler and maternal characteristics in the first trimester for the prediction of preeclampsia was performed and models selected based on predefined criteria. Validation was performed by applying the regression coefficients that were published in the different derivation studies to our cohort. We assessed the models discrimination ability and calibration.

RESULTS

Twenty models were identified for validation. The discrimination ability observed in derivation studies (Area Under the Curves) ranged from 0.70 to 0.96 when these models were validated against the validation cohort, these AUC varied importantly, ranging from 0.504 to 0.833. Comparing Area Under the Curves obtained in the derivation study to those in the validation cohort we found statistically significant differences in several studies.

CONCLUSION

There currently isn't a definitive prediction model with adequate ability to discriminate for preeclampsia, which performs as well when applied to a different population and can differentiate well between the highest and lowest risk groups within the tested population. The pre-existing large number of models limits the value of further model development and future research should be focussed on further attempts to validate existing models and assessing whether implementation of these improves patient care.

Involvement of dysregulated IKCa and SKCa channels in preeclampsia

INTRODUCTION

Excessive constriction of placental chorionic plate arteries (CPAs) may be associated with preeclampsia (PE). Nitric oxide (NO) as well as intermediate and small Ca²⁺-activated K⁺ channels (IK_Ca and SK_Ca) plays vital roles in vasodilation of CPAs. We hypothesized that dysregulated IK_Ca and SK_Ca channels may be involved in the pathogenesis of PE mediated by the impaired NO system on CPAs.

METHODS

The location of IK_Ca and SK_Ca channels, activities of NO synthases (NOS), and expression levels of these molecules were studied on CPAs from 30 normal pregnancies and 30 PE. The vasodilating function of CPAs was measured under openers or blockers of IK_Ca/SK_Ca channels in the presence or absence of NO donor or inhibitor.

RESULTS

IK_Ca and SK_Ca channels were located both on endothelium and on smooth muscles of CPAs and the expressions of them were downregulated in PE women comparing to those in normal pregnant women. The protein expressions of endothelial NOS (eNOS) and inducible NOS (iNOS) were downregulated on CPAs in PE accompanied by decreased activity of eNOS. Notably, the vasodilatory functions mediated by IK_Ca/SK_Ca channels and by NO were aberrant on preeclamptic CPAs. In addition, IK_Ca and SK_Ca channels were responsible for nitric oxide (NO)-attributable vasorelaxation and activity modulation of NO synthases.

CONCLUSIONS

This study provides evidence that dysregulated IK_Ca and SK_Ca channels might contribute to fetal pathogenesis of PE through direct promotion of vascular constriction of CPAs and through affecting functions of NO and activities of NOS.

Revisiting the discriminatory accuracy of traditional risk factors in preeclampsia screening

BACKGROUND

Preeclampsia (PE) is associated with a high risk of perinatal morbidity and mortality. However, there is no consensus in the definition of high-risk women.

AIM

To question current definition of high PE risk and propose a definition that considers individual heterogeneity to improves risk classification.

METHODS

A stratified analysis by parity was conducted using the Swedish Birth Register between 2002-2010 including 626.600 pregnancies. The discriminatory accuracy (DA) of traditional definitions of high-risk women was compared with a new definition based on 1) specific combinations of individual variables and 2) a centile cut-off of the probability of PE predicted by a multiple logistic regression model.

RESULTS

None of the classical risk-factors alone reached an acceptable DA. In multiparous, any combination of a risk-factor with previous PE or HBP reached a +LR>10. The combination of obesity and multiple pregnancy reached a good DA particularly in the presence of previous preeclampsia (positive likelihood ratio (LR+) = 26.5 or chronic hypertension (HBP) LR+ = 40.5. In primiparous, a LR+>15 was observed in multiple pregnancies with the simultaneous presence of obesity and diabetes mellitus or with HBP. Predicted probabilities above 97 centile in multiparous and 99 centile in primiparous provided high (LR+ = 12.5), and moderate (LR+ = 5.85), respectively. No one risk factor alone or in combination provided a LR- sufficiently low to rule-out the disease.

CONCLUSIONS

In preeclampsia prediction the combination of specific risk factors provided a better discriminatory accuracy than traditional single risk approach. Our results contribute to a more personalized risk estimation of preeclampsia.

Risk assessment of hypertensive disorders in pregnancy with maternal characteristics in early gestation: A single-center cohort study

OBJECTIVE

Hypertensive disorders in pregnancy are major causes of maternal mortality and morbidity. Although the combined risk assessments of maternal history, blood pressure, uterine artery Doppler, and maternal serum marker seem to be highly predictive of the development of hypertensive disorders, this method is a little complicated to be performed on many low-risk pregnant women. The aim of this study is to evaluate the use of maternal characteristics, and physical findings early in the second trimester, as predictive factors of hypertensive disorders.

MATERIALS AND METHODS

This is a retrospective cohort study undertaken in a single tertiary care center in Japan. Singleton pregnant women without underlying disease and evaluated before 14 weeks of gestation were included. We conducted multivariate logistic regression analysis and decision tree analysis to elucidate the potential risk factors of hypertensive disorders, including gestational hypertension and preeclampsia.

RESULTS

In total, 1986 women were evaluated, of whom 863 were nulliparous and 1123 were multiparous, and 166 (8.3%) were diagnosed with hypertensive disorders. In multivariate analysis, maternal age ≥ 40 years, prepregnancy BMI ≥ 30 kg/m(2), in vitro fertilization and embryo transfer (IVF-ET), family history of hypertension, and blood pressure ≥ 130/85 mmHg at first visit were independent risk factors for the nulliparous women. Maternal age ≥ 40 years, a history of previous hypertensive disorders, and blood pressure ≥ 130/85 mmHg at first visit were independent risk factors for the multiparous women. According to the decision tree analysis, high-risk populations were as follows: women ≥ 40 years old who conceived thorough IVF-ET and women with prepregnancy BMI ≥ 30 kg/m(2) who conceived spontaneously in nulliparous women; women with a history of hypertensive disorders and women with blood pressure ≥ 130/85 mmHg in the absence of the previous history.

CONCLUSION

The combination of maternal background and physical findings is useful to identify the population with a high risk of hypertensive disorders.

The role of aspirin dose on the prevention of preeclampsia and fetal growth restriction: systematic review and meta-analysis

BACKGROUND

Preeclampsia and fetal growth restriction are major causes of perinatal death and handicap in survivors. Randomized clinical trials have reported that the risk of preeclampsia, severe preeclampsia, and fetal growth restriction can be reduced by the prophylactic use of aspirin in high-risk women, but the appropriate dose of the drug to achieve this objective is not certain.

OBJECTIVE

We sought to estimate the impact of aspirin dosage on the prevention of preeclampsia, severe preeclampsia, and fetal growth restriction.

STUDY DESIGN

We performed a systematic review and meta-analysis of randomized controlled trials comparing the effect of daily aspirin or placebo (or no treatment) during pregnancy. We searched MEDLINE, Embase, Web of Science, and Cochrane Central Register of Controlled Trials up to December 2015, and study bibliographies were reviewed. Authors were contacted to obtain additional data when needed. Relative risks for preeclampsia, severe preeclampsia, and fetal growth restriction were calculated with 95% confidence intervals using random-effect models. Dose-response effect was evaluated using meta-regression and reported as adjusted R². Analyses were stratified according to gestational age at initiation of aspirin (≤16 and >16 weeks) and repeated after exclusion of studies at high risk of biases.

RESULTS

In all, 45 randomized controlled trials included a total of 20,909 pregnant women randomized to between 50-150 mg of aspirin daily. When aspirin was initiated at ≤16 weeks, there was a significant reduction and a dose-response effect for the prevention of preeclampsia (relative risk, 0.57; 95% confidence interval, 0.43-0.75; P < .001; R², 44%; P = .036), severe preeclampsia (relative risk, 0.47; 95% confidence interval, 0.26-0.83; P = .009; R², 100%; P = .008), and fetal growth restriction (relative risk, 0.56; 95% confidence interval, 0.44-0.70; P < .001; R², 100%; P = .044) with higher dosages of aspirin being associated with greater reduction of the 3 outcomes. Similar results were observed after the exclusion of studies at high risk of biases. When aspirin was initiated at >16 weeks, there was a smaller reduction of preeclampsia (relative risk, 0.81; 95% confidence interval, 0.66-0.99; P = .04) without relationship with aspirin dosage (R², 0%; P = .941). Aspirin initiated at >16 weeks was not associated with a risk reduction or a dose-response effect for severe preeclampsia (relative risk, 0.85; 95% confidence interval, 0.64-1.14; P = .28; R², 0%; P = .838) and fetal growth restriction (relative risk, 0.95; 95% confidence interval, 0.86-1.05; P = .34; R², not available; P = .563).

CONCLUSION

Prevention of preeclampsia and fetal growth restriction using aspirin in early pregnancy is associated with a dose-response effect. Low-dose aspirin initiated at >16 weeks' gestation has a modest or no impact on the risk of preeclampsia, severe preeclampsia, and fetal growth restriction. Women at high risk for those outcomes should be identified in early pregnancy.

Prediction of Gestational Diabetes Mellitus by Unconjugated Estriol Levels in Maternal Serum

The aim of this study was to evaluate the association between maternal serum estriol levels, which are routinely measured in the first trimester of pregnancy, and adverse pregnancy outcomes including gestational diabetes. We performed a retrospective chart analysis of women who delivered between July 1, 2007, and December 31, 2009, at Kangnam CHA Medical Center in Seoul, Korea. Only patients with available estriol measurements during their pregnancies and complete follow-up data were included in the study. The effect of estriol on the incidence of adverse pregnancy outcomes was examined using multinomial logistic regression analysis with age and pre-pregnancy body mass index (BMI) as covariates. The total number of subjects was 1,553, the mean age was 32.9 ± 3.7 years, and the mean pre-pregnancy BMI was 21.2 ± 3.0 kg/m². Unconjugated estriol > 95^th percentile of the screened population or unconjugated estriol ≥ 2.0 MoM (Multiple of the Median) was significantly associated with an increased risk for developing gestational diabetes mellitus (GDM), after adjusting for age and pre-pregnancy maternal weight. High levels of unconjugated estriol in the maternal serum during the early second trimester of pregnancy are a useful predictor of GDM development.