A prospective study of screening for hypertensive disorders of pregnancy at 11-13 weeks in a Scandinavian population

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.

A meta-analysis on first-trimester blood count parameters-is the neutrophil-to-lymphocyte ratio a potentially novel method for first-trimester preeclampsia screening?

Objective

Meta-analysis focusing on the role of first-trimester neutrophil-to-lymphocyte ratio (NLR) in the prediction of preeclampsia.

Data sources

PubMed, Scopus, Web of Science, Cochrane Library, and Embase databases were queried from inception up to December 31, 2022.

Study eligibility criteria

The study included all types of original research that was conducted in humans and values of NLR were measured during the first trimester, among patients who later developed preeclampsia, compared to the values of control groups.

Study appraisal and synthesis methods

Two reviewers independently performed data abstraction and quality appraisal, and disagreements were resolved by consensus and, if necessary, by the opinion of a third reviewer. During the analysis, PRISMA and MOOSE guidelines were followed. All statistical analyses were made with R.

Results

For the research on the predictive role of NLR values in the first trimester for preeclampsia, a total of 6 studies were selected for analysis, covering 2,469 patients. The meta-analysis revealed a 95% confidence interval (CI) for the effect size of 0.641 to 1.523, with a prediction interval of 0.027 to 2.137.

Conclusion

Based on the analysis, NLR is a promising biochemical marker for future pieces of research that try to find new screening methods for first-trimester preeclampsia. We encourage other researchers to examine NLR's predictive value combined with other markers in preeclampsia screening, this way being able to find new and affordable protocols for first-trimester preeclampsia screening.

Systematic review registration

identifier CRD42023392663.

Higher PAPP-A Values in Pregnant Women Complicated with Preeclampsia Than with Gestational Hypertension

The purpose of this study is to compare the levels of maternal serum pregnancy-associated plasma protein-A at the first trimester in pregnancies complicated by impaired placental diseases, such as preeclampsia (PE), intrauterine fetal growth restriction (IUGR), and gestational hypertension (GH), with those in pregnancies without the development of any of these outcomes to expand the knowledge of how this protein behaves in the different impaired placental diseases. This current work is an observational study based on a prospective cohort. Pregnancy-associated plasma protein-A was measured in 422 patients who had completed maternal-perinatal outcomes. Comparisons of pregnancy characteristics and the biomarker between outcome groups (PE, IUGR, gestational hypertension, and not impaired placental outcomes) were analyzed. PAPP-A MoM in the IUGR (0.8 IQR: 0.6-0.9) and GH groups (0.5 IQR: 0.3-1.4) compared to the PE group (1.06 IQR: 0.66-1.52) was significantly lower (p < 0.005). Pregnant women who developed early-onset PE (1.11 IQR 1.08-1.18) presented significant differences with the IUGR group (0.83 IQR: 0.59-0.98; p = 0.002) and those who developed preterm-PE (1.19 IQR: 0.66-1.58; p = 0.045). The results demonstrate that the levels of PAPP-A at first trimester in the sample of women who developed PE, and specially term-PE, were higher than those in women who developed GH or IUGR. The GH group had the lowest PAPP-A values in this sample of pregnant women. Research in a population with a high prevalence of preeclampsia is still lacking and deserves more extended studies to define if these patients could have different rates of PAPP-A.

Diagnostic Value of IGFBP-2 in Predicting Preeclampsia before 20 Weeks of Pregnancy: A Prospective Nested Case-Control Study

Purpose

To identify novel biomarker insulin-like growth factor binding protein-2 (IGFBP-2) associated with preeclampsia (PE) before 20 weeks of gestation and to explore the predictive value of plasma IGFBP-2 in PE.

Methods

A prospective nested case-control investigation involving 122 PE patients and 122 normal controls (NC) that were matched 1 : 1 in terms of age and week of pregnancy was carried out in Guangzhou Women and Children's Medical Center (Guangzhou, China, 2018030306) from April 2016 to December 2019. At 8 to 20 weeks, blood samples from the mother were taken. To calculate the correlations, univariate conditional logistic regression was employed.

Results

Herein, 12 clinical indices were significantly different between the PE and NC groups (uric acid (UA), cystatin C (Cys C), aspartate aminotransferase (AST), glutamyl transpeptidase (γ-GT), total bilirubin (TB), prothrombin time (PT), red blood cell (RBC), hematocrit (HCT), red cell distribution width (RDW), platelets (PLT), mean platelet volume (MPV), and thrombocytocrit (PCT)). Compared with the NC group (36.79 ± 19.91 pg/mL), the expression level of IGFBP2 in the PE group (19.76 ± 19.40 pg/mL) before 20 weeks of pregnancy was significantly decreased (P < 0.01). Two high-risk factors were found to be significantly associated with PE independently of confounders: anemia 4.35 (2.20-8.45) (P < 0.01) and cesarean section history 8.25 (2.67-26.67) (P < 0.01). As a result of the univariate logistic regression analysis, the following three variables were included in the final logistic regression model.: Y = −18.841 − 0.085 × (IGFBP‐2) + 0.630 × (RDW) + 0.165 × (AST) + 0.863 × (MPV). In comparison to IGFBP-2 alone as an independent predictor of PE (AUC = 0.897, 95% CI 0.830–0.964), the model's discriminatory power was considerably higher (AUC = 0.953, 95% CI 0.911–0.995).

Conclusion

Plasma IGFBP-2 before 20 weeks of pregnancy combined with high-risk factors and routine blood indexes has a high early predictive value for PE.

Elevated mid-trimester 4-h postprandial triglycerides for predicting late-onset preeclampsia: a prospective screening study

Background

Abnormal maternal lipid concentrations are associated with increased risk of preeclampsia. However, previous studies mainly focused on fasting lipid concentrations, scarce data have been published on the relationship between postprandial triglyceride (TG) concentrations in the second trimester and the risk of preeclampsia. Our aim is to evaluate the potential of triglyceride (TG) concentrations at the time of oral lipid tolerance test (OLTT) measurement in the second trimester to predict preeclampsia and to elucidate the lipid metabolic changes related to these diseases.

Methods

This is a prospective cohort study of Pregnant women at 12–24 weeks of gestation undergone an OLTT in a university affiliated hospital between May 2019 and January 2020. Data were stratified into binaries according to the OLTT results. The receiver operating characteristic (ROC) curve analysis was conducted to determine the optimal cut-off points of TG, HDL-C, LDL-C, sd-LDL, FFA, and BG for predicting preeclampsia.

Results

438 pregnant women were recruited to undergo an OLTT at 12–24 weeks of gestation. Among these, 24 women developed preeclampsia and 414 women remained normotensive. Women who subsequently developed preeclampsia had higher concentrations of 4-h postprandial TG than those who remained normotensive. In the linear logistic regression analyses of potential confounding factors, mid-trimester 4-h postprandial TG concentrations at the time of OLTT measurement were significantly higher in preeclamptic cases than in controls.

Conclusions

Dyslipidemia in the second trimester of pregnancy, particularly postprandial hypertriglyceridemia, appears to be associated with an increased risk of preeclampsia. Mid-trimester 4-h postprandial TG concentration at the time of OLTT measurement may be a potential predictive marker of preeclampsia.

Trial registration Data of registration: 2018/10/15. Date of initial participant enrollment: 2019/05/01. Clinical trial identification number: chiCTR1800018884. URL of the registration site: http://www.chictr.org.cn/showproj.aspx?proj=25526. Data sharing information: The data including individual participant data, detailed study protocols, statistical analysis plans will be shared upon request to the corresponding author.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03261-6.

Outcomes of 42 pregnancies in 14 women with cartilage-hair hypoplasia: a retrospective cohort study

BACKGROUND

Cartilage-hair hypoplasia (CHH) is a rare skeletal dysplasia characterized by disproportionate short stature, immunodeficiency, anemia and risk of malignancies. All these features can affect pregnancy and predispose to maternal and fetal complications. This study aimed to evaluate obstetric history and maternal and fetal outcomes in women with CHH.

METHODS

Among 47 Finnish women with CHH, we identified 14 women with ICD codes related to pregnancies, childbirth and puerperium in the National Hospital Discharge Registry and obtained detailed data on gynecologic and obstetric history with a questionnaire. Offspring birth length and weight were collected and compared with population-based normal values.

RESULTS

There were altogether 42 pregnancies in 14 women (median height 124 cm, range 105-139 cm; 4'1'', range 3'5''-4'7''). Twenty-six pregnancies (62%), including one twin pregnancy, led to a delivery. Miscarriages, induced abortions and ectopic pregnancies complicated 9, 5, and 2 pregnancies, respectively. Severe pregnancy-related complications were rare. All women with CHH delivered by cesarean section, mostly due to evident cephalo-pelvic disproportion, and in 25/26 cases at full-term. In the majority, the birth length (median 48 cm, range 45.5-50 cm; 1'7'', range 1'6''-1'8'') and weight (3010 g, range 2100-3320 g; 6.6 lb, range 4.6-7.3 lb) of the offspring in full-term singleton pregnancies was normal.

CONCLUSIONS

Despite CHH mothers' significant short stature and other potential CHH-related effects on pregnancy outcome, most pregnancies lead to a term cesarean section delivery. Since fetal growth was generally unaffected, cephalo-pelvic disproportion was evident and planned cesarean section should be contemplated in term pregnancies.

Development and Validation of a Nomogram for Predicting the Risk of Pregnancy-Induced Hypertension: A Retrospective Cohort Study

Objective: To develop and validate a prediction model for identifying pregnant women at risk of developing pregnancy-induced hypertension (PIH) to guide treatment decision and classification of management. Methods: This study retrospectively enrolled 907 consecutive pregnant women with de novo hypertension from the Antenatal Care Center of Henan Provincial People's Hospital between June 1, 2018 and May 31, 2019. The cohort was randomly divided into two subgroups: the development cohort (n = 635) and validation cohort (n = 272). Univariate analysis and backward elimination of multivariate logistic regression analyses were utilized to identify predictive factors, and a nomogram was established. The performance was assessed using the area under the curve (AUC), the mean AUC of k-fold cross-validation, and calibration plots. Based on the classification and regression tree model, risk classification was performed. Results: The score included five commonly available predictors: body mass index, proteinuria, age, uric acid, and mean arterial pressure (BPAUM score). When applied to internal validation, the score revealed good discrimination with stratified fivefold cross-validation in the development cohort (AUC = 0.91) and validation cohort (AUC: 0.89) at fixed 10% false-positive rates, and the calibration plots showed good calibration. The total score point was divided into three risk classifications: low risk (0 - 179 points), medium risk (179 - 204 points), and high risk (>204 points). Conclusions: This study established a prediction model for predicting PIH, which could be used in clinical decision-making to improve maternal health and birth outcomes.

The role of progestogen supplementation (dydrogesterone) in the prevention of preeclampsia

Our goal was determine the effects of dydrogesterone supplementation to reduce the incidence of preeclampsia (PE) in early pregnancy (from 6 to 20 weeks of gestation). A total of 406 pregnant women were involved into the study. The Study group enrolled 169 women, supplemented with dydrogesterone at a dose of 30 mg/d 6-20 weeks of gestation compared with the control group (237 subjects) - without dydrogesterone supplementation. The women were randomized by age, race, obstetrics complications, and their somatic history. The use of dydrogesterone in early pregnancy - before 20 weeks of gestation (at a dose of 30 mg/d) with high-risk factors of PE contributed to a statistically significant reduction in the frequency of this complication (13.1% and 71.4%, p < .001). It was seen, that women who took dydrogesterone developed significantly less such disorders like hypertension (3.2% and 71.2%, p < .001), proteinuria (0.0% and 66.18%, p < .001), fetal growth retardation syndrome (2.2% and 21.58%, p < .001), destroy of uteri-placenta velocity (3.2% and 21.58%, p < .001), preterm labor (8.6% and 53.95%, p < .001). Dydrogesterone supplementation in the first and second period of pregnancy (from 6 to 20 weeks of gestation) significantly reduced the incidence of PE in women with higher risk pregnancy.

Predictive Performance of PlGF (Placental Growth Factor) for Screening Preeclampsia in Asymptomatic Women: A Systematic Review and Meta-Analysis

Preeclampsia is a systemic syndrome that seems to originate from the placenta and is associated with an imbalance between angiogenic factors in the maternal circulation. One of the well-studied and widely used factors is PlGF (placental growth factor), the levels of which drop in women destined to develop preeclampsia. This drop is known to precede the development of actual signs and symptoms of preeclampsia, thus proving to be a useful screening tool in predicting the disease. The literature varies widely in terms of the clinical usefulness of the test. We conducted a meta-analysis to study the predictive accuracy of PlGF in asymptomatic women. Our analysis included 40 studies with 3189 cases of preeclampsia and 89 498 controls. The overall predictive odds ratio of the test was 9 (6-13). Subgroup analysis evaluating various PlGF thresholds demonstrated that the predictive values were highest for PlGF levels between 80 and 120 pg/mL with a high predictive odds ratio of 25 (7-88), a sensitivity of 0.78 (95% CI, 0.67-0.86), a specificity of 0.88 (95% CI, 0.75-0.95), a positive likelihood ratio of 6.3 (95% CI, 2.7-14.7), and a negative likelihood ratio of 0.26 (95% CI, 0.16-0.42). Additionally, the accuracy was higher when the test was performed after 14 weeks of gestation (OR, 10 [7-15]) and for prediction of early onset preeclampsia (OR, 18 [9-37]). We conclude that PlGF is a useful screening tool to predict preeclampsia. Nonetheless, its utility should be judged with caution and randomized controlled trials are warranted to explore if its implementation improves perinatal outcomes in asymptomatic women.

Prediction models for preeclampsia: A systematic review

BACKGROUND

Preeclampsia is a disease specific to pregnancy that can cause severe maternal and foetal morbidity and mortality. Early identification of women at higher risk for preeclampsia could potentially aid early prevention and treatment. Although a plethora of preeclampsia prediction models have been developed in recent years, individualised prediction of preeclampsia is rarely used in clinical practice.

OBJECTIVES

The objective of this systematic review was to provide an overview of studies on preeclampsia prediction.

STUDY DESIGN

Relevant research papers were identified through a MEDLINE search up to 1 January 2017. Prognostic studies on the prediction of preeclampsia or preeclampsia-related disorders were included. Quality screening was performed with the Quality in Prognostic Studies (QUIPS) tool.

RESULTS

Sixty-eight prediction models from 70 studies with 425,125 participants were selected for further review. The number of participants varied and the gestational age at prediction varied widely across studies. The most frequently used predictors were medical history, body mass index, blood pressure, parity, uterine artery pulsatility index, and maternal age. The type of predictor (maternal characteristics, ultrasound markers and/or biomarkers) was not clearly associated with model discrimination. Few prediction studies were internally (4%) or externally (6%) validated.

CONCLUSIONS

To date, multiple and widely varying models for preeclampsia prediction have been developed, some yielding promising results. The high degree of between-study heterogeneity impedes selection of the best model, or an aggregated analysis of prognostic models. Before multivariable preeclampsia prediction can be clinically implemented universally, further validation and calibration of well-performing prediction models is needed.

Macular choroidal thickness in highly myopic women during pregnancy and postpartum: a longitudinal study

Background

High myopia, a cause of serious visual impairment, is a significant global public health concern. We investigate longitudinal changes in macular choroidal thickness (CT) during pregnancy and 6-months postpartum in women with high myopia (HM).

Methods

A prospective longitudinal study was conducted in HM-pregnant women during the course of pregnancy (n = 42 eyes, 42 patients) and 6 months postpartum (n = 40 eyes, 40 patients, two cases lost).Macular CT was measured via enhanced-depth imaging (EDI)-optical coherence tomography (OCT) (EDI-OCT). Intraocular pressure (IOP), axial length (AL), refractive error, mean arterial pressure (MAP), mean ocular perfusion pressure (MOPP), and body mass index (BMI) were also measured.

Results

Macular CTs of HM pregnant women (214.3 ± 52.3 μm) had increased significantly during the third trimester of pregnancy compared with postpartum women (192.7 ± 51.9 μm, p = 0.014). No significant differences in AL, refractive error, or MAP were found between pregnant and postpartum groups (p > 0.05 for all parameters).During pregnancy, macular CT was negatively correlated with AL (first trimester: p = 0.010; second trimester: p = 0.013; and third trimester: p = 0.008) and positively correlated with refractive error (first trimester: p = 0.038; second trimester: p = 0.024; and third trimester: p = 0.010). No correlations between macular CT and age, IOP, MOPP, MAP, or BMI were found.

Conclusions

Our study revealed the presence of a significantly thicker choroid during the third trimester of pregnancy compared with 6-mo postpartum in HM women. Macular CT positively correlated with refractive error and negatively correlated with AL during pregnancy, but did not correlate with gestational age, MOPP, IOP, MAP, or BMI.

Galectin-1 as a novel risk factor for both gestational hypertension and preeclampsia, specifially its expression at a low level in the second trimester and a high level after onset

Our aim was to evaluate whether the serum level of galectin-1 (Gal-1) at 18-24 and 27-31 weeks of gestation is a risk factor for predicting the later occurrence of not only preeclampsia (PE) but also gestational hypertension (GH). We measured serum levels of soluble fms-like tyrosine kinase 1 (sFlt-1), placental growth factor (PlGF), and Gal-1 using an enzyme-linked immunosorbent assay in 81 and 73 normal pregnant women, 22 and 16 women with a later onset of GH, and 37 and 29 women with a later onset of PE at 18-24 and 27-31 weeks, respectively. We also measured Gal-1 in 33 women with GH and 78 women with PE after the onset. The levels of Gal-1 after the onset of GH, late-onset PE (onset at ⩾34 weeks), and early-onset PE (onset at <34 weeks) were significantly higher than those in normal pregnant women at 27-31 weeks. However, the low levels of Gal-1 (<8.1 ng ml^-1) at 18-24 weeks, but not at 27-31 weeks, predicted the later occurrence of not only early-onset PE and late-onset PE but also GH. The low level of Gal-1 at 18-24 weeks was an independent risk factor for the later occurrence of GH and PE, after adjusting for the effects of a high BP and increased sFlt-1/PlGF ratio at 18-24 weeks. In conclusion, the serum level of Gal-1 is a novel risk factor for both GH and PE, specifically its expression at a low level in the second trimester and a high level after onset.

Early prediction of hypertension during pregnancy in a low-resource setting

OBJECTIVE

To evaluate the role of maternal factors, biomarkers, and uterine-artery Doppler in the prediction of hypertension during pregnancy.

METHODS

A prospective cohort study was performed between December 2012 and November 2014. All singleton pregnancies between 11 weeks and 13 weeks, 6 days of pregnancy were included. Patients had their body mass index (BMI, calculated as weight in kilograms divided by the square of height in meters), mean arterial pressure, uterine-artery Doppler pulsatility index, and pregnancy-associated plasma protein A (PAPP-A) and free β-human chorionic gonadotropin levels recorded. Any patients diagnosed with hypertension during follow-up were assigned to the case cohort; all other patients were assigned to the control group.

RESULTS

Hypertension during pregnancy was observed in 198 (9.7%) of 2042 patients that attended follow-up. The mean BMI, mean arterial pressure, uterine-artery Doppler pulsatility index, and the PAPP-A level at study enrollment were all significantly correlated with the later development of hypertension (P<0.001 for all variables). The combined sensitivity, specificity, positive predictive value, and negative predictive value of using the investigated parameters to predict hypertension was 76%, 80%, 31%, and 93%, respectively.

CONCLUSION

Patient BMI, mean arterial pressure, PAPP-A, and pulsatility index were found to be effective predictors of hypertension during pregnancy. Combining these predictors may be beneficial in selecting individuals for close monitoring and early intervention during pregnancy.

Distinct First Trimester Cytokine Profiles for Gestational Hypertension and Preeclampsia

OBJECTIVE

Gestational hypertension and preeclampsia involve dysregulated maternal inflammatory responses to pregnancy, but whether such responses differ between the disorders has not been determined. We aimed to investigate disease-specific early pregnancy serum cytokine profiles of women subsequently developing gestational hypertension or preeclampsia for new insight into the underlying pathogeneses and differences between the disorders.

APPROACH AND RESULTS

The study cohort consisted of 548 pregnant Norwegian women who were either multiparous with previous gestational hypertension or preeclampsia or were nulliparous. Maternal sera at gestational weeks 11(0)-13(6) were assayed for 27 cytokines, C-reactive protein, total cholesterol, high-density lipoprotein, triglyceride, creatinine, calcium, uric acid, and placental growth factor. Compared with normotensive women, women with both hypertensive conditions presented an atherogenic lipid profile at early gestation, but only those later developing gestational hypertension had significantly higher serum levels of interleukin (IL)-5 and IL-12. Comparing the 2 hypertensive pregnancy disorders, women subsequently developing gestational hypertension had higher serum levels of IL-1β, IL-5, IL-7, IL-8, IL-13, basic fibroblast growth factor, and vascular endothelial growth factor than the women subsequently developing preeclampsia.

CONCLUSIONS

This study identifies early pregnancy differences in serum cytokine profiles for gestational hypertension and preeclampsia.

First Trimester Urine and Serum Metabolomics for Prediction of Preeclampsia and Gestational Hypertension: A Prospective Screening Study

Hypertensive disorders of pregnancy, including preeclampsia, are major contributors to maternal morbidity. The goal of this study was to evaluate the potential of metabolomics to predict preeclampsia and gestational hypertension from urine and serum samples in early pregnancy, and elucidate the metabolic changes related to the diseases. Metabolic profiles were obtained by nuclear magnetic resonance spectroscopy of serum and urine samples from 599 women at medium to high risk of preeclampsia (nulliparous or previous preeclampsia/gestational hypertension). Preeclampsia developed in 26 (4.3%) and gestational hypertension in 21 (3.5%) women. Multivariate analyses of the metabolic profiles were performed to establish prediction models for the hypertensive disorders individually and combined. Urinary metabolomic profiles predicted preeclampsia and gestational hypertension at 51.3% and 40% sensitivity, respectively, at 10% false positive rate, with hippurate as the most important metabolite for the prediction. Serum metabolomic profiles predicted preeclampsia and gestational hypertension at 15% and 33% sensitivity, respectively, with increased lipid levels and an atherogenic lipid profile as most important for the prediction. Combining maternal characteristics with the urinary hippurate/creatinine level improved the prediction rates of preeclampsia in a logistic regression model. The study indicates a potential future role of clinical importance for metabolomic analysis of urine in prediction of preeclampsia.

TRAIL Is Decreased Before 20 Weeks Gestation in Women with Hypertensive Disorders of Pregnancy

Objective

The present study evaluated maternal plasma protein profiles before the onset of hypertensive disorders of pregnancy (HDP) to assess the relationship between maternal plasma tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and HDP before 20 weeks gestation and to evaluate the discriminatory performance of plasma TRAIL levels for HDP.

Methods

A 2-phase discovery/validation study was designed. In the discovery phase, a nested case-controlled study was performed using plasma sampled at 8 to 20 weeks gestation from 20 women who later developed HDP and from 20 age- and gestational week-matched controls. Plasma was analyzed using a human protein microarray technology designed to simultaneously detect 507 proteins. The functional annotation and clustering of the differentially expressed proteins were performed using DAVID and the GO database. TRAIL levels were further validated in an independent study using plasma obtained at 8 to 20 weeks gestation from 53 women who later developed HDP and from 106 matched controls, and 62 clinical risk factors were investigated.

Results

In the protein microarray analysis, 23 proteins were differentially expressed between the two groups. The ELISA showed that women who later developed HDP had significantly lower TRAIL levels compared to women with uncomplicated pregnancies. The multivariable Cox regression analysis identified the following three factors that were entered into the final Cox regression model: gravidity (OR = 2.02, 95% CI 1.00–4.09), pre-pregnancy BMI (OR = 1.46, 95% CI 1.21–1.76) and TRAIL levels (OR = 0.97, 95% CI 0.94–0.99). The model had a significantly better discriminatory power (AUC = 0.83, 95% CI 0.75–0.88) compared to TRAIL alone as an independent predictor of HDP (AUC = 0.59, 95% CI 0.51–0.67).

Conclusion

Twenty-three differentially expressed proteins before 20 weeks gestation might be associated with the pathogenesis of HDP. Plasma TRAIL levels were associated with the development of HDP, and the combination of plasma TRAIL levels with pre-pregnancy BMI and gravidity had a good discriminatory performance for HDP before 20 weeks gestation.

The first trimester: prediction and prevention of the great obstetrical syndromes

A number of groups are currently examining the potential of screening for pre-eclampsia and gestational diabetes at 12 weeks' gestation. This can be performed at the time of combined first-trimester screening for aneuploidy using a similar method of regression analysis to combine multiple demographic and investigative factors. At present, research into the prediction of pre-eclampsia is more robust and is associated with the potential for therapeutic intervention that can reduce the prevalence of early-onset pre-eclampsia and improve maternal and neonatal outcomes.