Accuracy of angiogenic biomarkers at ⩽20weeks’ gestation in predicting the risk of pre-eclampsia: A WHO multicentre study

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.

Real-world evidence for the utility of serum soluble fms-like tyrosine kinase 1/placental growth factor test for routine clinical evaluation of hospitalized women with hypertensive disorders of pregnancy

BACKGROUND

An imbalance of the antiangiogenic factor, soluble fms-like tyrosine kinase-1, and proangiogenic factor, placental growth factor, in the circulation is a reliable predictor for the development of preeclampsia with severe features and related adverse outcomes. In 2023, the US Food and Drug Administration approved a serum soluble fms-like tyrosine kinase-1/placental growth factor test at a cutoff of 40 to aid in the risk assessment of women hospitalized for hypertensive disorders of pregnancy for the progression to preeclampsia with severe features between 23 and 35 weeks.

OBJECTIVE

This study aimed to generate real-world evidence for clinical utility for serum soluble fms-like tyrosine kinase-1/placental growth factor test when made available to clinicians in a timely fashion as an aid in risk stratification of development of preeclampsia with severe features within 2 weeks of testing among hospitalized patients with hypertensive disorders of pregnancy.

STUDY DESIGN

Hospitalized patients with hypertensive disorders of pregnancy between 23 weeks to 34 weeks and 6 days of gestation were prospectively studied from June 2023 to January 2024 after the implementation of serum soluble fms-like tyrosine kinase-1/placental growth factor testing into routine clinical practice. Serum samples were obtained from patients via venipuncture and analyzed on an automated immunoassay platform (placental growth factor and soluble fms-like tyrosine kinase-1 assays; Thermo Fisher Scientific). Before implementation, physicians were educated on appropriate use and management guidelines on the basis of biomarkers but made pragmatic management decisions independently. Results of soluble fms-like tyrosine kinase-1/placental growth factor tests were available to clinicians within 24 hours of venipuncture. The association between soluble fms-like tyrosine kinase-1/placental growth factor ≥40 and progression to preeclampsia with severe features and adverse maternal/perinatal outcomes were assessed.

RESULTS

Of the 65 patient encounters, 36 had a soluble fms-like tyrosine kinase-1/placental growth factor <40 (55.4%). The rate of delivery for indications related to hypertensive disorders of pregnancy within 2 weeks was significantly lower among encounters with a low ratio vs high ratio (2/36 [5.6%] vs 21/29 [72.4%]) even after controlling for relevant confounders (adjusted hazard ratio, 7.52; 95% confidence interval, 3.05-18.54; P<.001). A diagnosis of preeclampsia with severe features within 2 weeks of testing was also less likely among the encounters with soluble fms-like tyrosine kinase-1/placental growth factor ratio <40 when compared with soluble fms-like tyrosine kinase-1/placental growth factor ratio ≥40 (2/36 [5.6%] vs 23/29 [79.3%], P<.001; positive predictive value of 79% [95% confidence interval, 0.65-0.94] and negative predictive value of 0.94 [95% confidence interval, 0.87-1.00]). The positive and negative likelihood ratios for the development of preeclampsia with severe features within 2 weeks of testing were 6.13 and 0.09, respectively. Encounters with a soluble fms-like tyrosine kinase-1/placental growth factor ratio <40 were less likely to experience a maternal or fetal adverse event as compared with encounters with soluble fms-like tyrosine kinase-1/placental growth factor ratio ≥40 (3/36 [8.3%] vs 10/29 [34.5%], P=.01). Among 36 encounters involving low soluble fms-like tyrosine kinase-1/placental growth factor values, 22 had had equivocal clinical or laboratory criteria resembling preeclampsia at presentation but were expectantly managed on the basis of biomarkers, and none developed preeclampsia with severe features or adverse outcomes at 2 weeks. The median latency defined as days between biomarker measurement and delivery in patients with a low biomarker ratio was 33 (interquartile ratio, 23-47) vs 7 (interquartile ratio, 4-14) days among patients with a high ratio (P<.001). Corticosteroid use within 2 weeks was also significantly reduced in the low biomarker group when compared with the high biomarker group (8/35 [22.9%] vs 24/29 [82.8%], P<.001).

CONCLUSION

In this study, the incorporation of soluble fms-like tyrosine kinase-1/placental growth factor ratio into clinical practice serves as a dependable supplement in assessing risk for progression to preeclampsia with severe features and adverse outcomes in patients with hypertensive disorders of pregnancy in the United States. Among patients with a low ratio, pregnancy may be prolonged, which results in better neonatal outcomes without harm to the mother.

A dynamic prediction model for preeclampsia using the sFlt-1/PLGF ratio combined with multiple factors

OBJECTIVE

Preeclampsia (PE) is a pregnancy-related multi-organ disease and a significant cause of incidence rate and mortality of pregnant women and newborns worldwide. Delivery remains the only available treatment for PE. This study aims to establish a dynamic prediction model for PE.

METHODS

A total of 737 patients who visited our hospital from January 2021 to June 2022 were identified according to the inclusion and exclusion criteria, forming the primary dataset. Additionally, 176 singleton pregnant women who visited our hospital from July 2022 to November 2022 comprised the verification set. We investigated different gestational weeks of sFlt-1/PLGF (soluble FMS-like tyrosine kinase-1, placental growth factor) ratio combined with maternal characteristics and routine prenatal laboratory results in order to predict PE in each trimester. Multivariate logistic regression was used to establish the prediction model for PE at different gestational weeks. The discrimination, calibration, and clinical validity were utilized to evaluate predictive models as well as models in external validation queues.

RESULTS

At 20-24 weeks, the obtained prediction model for PE yielded an area under the curve of 0.568 (95% confidence interval, 0.479-0.657). At 25-29 weeks, the obtained prediction model for PE yielded an area under the curve of 0.773 (95% confidence interval, 0.703-0.842)and 0.731 (95% confidence interval, 0.653-0.809) at 30-34 weeks. After adding maternal factors, uterine artery pulsation index(Ut-IP), and other laboratory indicators to the sFlt-1/PLGF ratio, the predicted performance of PE improved. It found that the AUC improved to 0.826(95% confidence interval, 0.748 ∼ 0.904) at 20-24 weeks, 0.879 (95% confidence interval, 0.823 ∼ 0.935) at 25-29 weeks, and 0.862(95% confidence interval, 0.799 ∼ 0.925) at 30-34 weeks.The calibration plot of the prediction model indicates good predictive accuracy between the predicted probability of PE and the observed probability. Furthermore, decision-curve analysis showed an excellent clinical application value of the models.

CONCLUSION

Using the sFlt-1/PLGF ratio combined with multiple factors at 25-29 weeks can effectively predict PE, but the significance of re-examination in late pregnancy is not significant.

Correlation Between Maternal-Fetus Interface and Placenta-Mediated Complications

Pregnancy is a highly regulated biological phenomenon that involves the development of a semi-allogeneic fetus inside the uterus of the mother. The maternal-fetal interface is a critical junction where communication takes place between the fetal and maternal immune systems, which determine the outcome of the pregnancy. The interface is composed of the decidua and placenta. The main cells present at the maternal-fetal interface include invading trophoblasts, maternal immune cells, and decidual stromal cells. Although maternal tolerance is crucial for maintaining a successful pregnancy, the role of the placenta in pregnancy is also important. Dysregulation of the placenta leads to various placenta-mediated complications, such as preeclampsia, intrauterine growth restriction, and placental abruption. Although the exact mechanism involving these complications is unclear, research has elucidated various factors involved in these pregnancy disorders. This review aimed to provide a summary of the maternal-fetal interface and immune mechanisms involved in placenta-mediated complications.

Predicting Preterm Birth Using Proteomics

The complexity of preterm birth (PTB), both spontaneous and medically indicated, and its various etiologies and associated risk factors pose a significant challenge for developing tools to accurately predict risk. This review focuses on the discovery of proteomics signatures that might be useful for predicting spontaneous PTB or preeclampsia, which often results in PTB. We describe methods for proteomics analyses, proteomics biomarker candidates that have so far been identified, obstacles for discovering biomarkers that are sufficiently accurate for clinical use, and the derivation of composite signatures including clinical parameters to increase predictive power.

Accuracy of placental growth factor alone or in combination with soluble fms-like tyrosine kinase-1 or maternal factors in detecting preeclampsia in asymptomatic women in the second and third trimesters: a systematic review and meta-analysis

OBJECTIVE

This study aimed to: (1) identify all relevant studies reporting on the diagnostic accuracy of maternal circulating placental growth factor) alone or as a ratio with soluble fms-like tyrosine kinase-1), and of placental growth factor-based models (placental growth factor combined with maternal factors±other biomarkers) in the second or third trimester to predict subsequent development of preeclampsia in asymptomatic women; (2) estimate a hierarchical summary receiver-operating characteristic curve for studies reporting on the same test but different thresholds, gestational ages, and populations; and (3) select the best method to screen for preeclampsia in asymptomatic women during the second and third trimester of pregnancy by comparing the diagnostic accuracy of each method.

DATA SOURCES

A systematic search was performed through MEDLINE, Embase, CENTRAL, ClinicalTrials.gov, and the World Health Organization International Clinical Trials Registry Platform databases from January 1, 1985 to April 15, 2021.

STUDY ELIGIBILITY CRITERIA

Studies including asymptomatic singleton pregnant women at >18 weeks' gestation with risk of developing preeclampsia were evaluated. We included only cohort or cross-sectional test accuracy studies reporting on preeclampsia outcome, allowing tabulation of 2×2 tables, with follow-up available for >85%, and evaluating performance of placental growth factor alone, soluble fms-like tyrosine kinase-1- placental growth factor ratio, or placental growth factor-based models. The study protocol was registered on the International Prospective Register Of Systematic Reviews (CRD 42020162460).

METHODS

Because of considerable intra- and interstudy heterogeneity, we computed the hierarchical summary receiver-operating characteristic plots and derived diagnostic odds ratios, β, θi, and Λ for each method to compare performances. The quality of the included studies was evaluated by the QUADAS-2 tool.

RESULTS

The search identified 2028 citations, from which we selected 474 studies for detailed assessment of the full texts. Finally, 100 published studies met the eligibility criteria for qualitative and 32 for quantitative syntheses. Twenty-three studies reported on performance of placental growth factor testing for the prediction of preeclampsia in the second trimester, including 16 (with 27 entries) that reported on placental growth factor test alone, 9 (with 19 entries) that reported on the soluble fms-like tyrosine kinase-1-placental growth factor ratio, and 6 (16 entries) that reported on placental growth factor-based models. Fourteen studies reported on performance of placental growth factor testing for the prediction of preeclampsia in the third trimester, including 10 (with 18 entries) that reported on placental growth factor test alone, 8 (with 12 entries) that reported on soluble fms-like tyrosine kinase-1-placental growth factor ratio, and 7 (with 12 entries) that reported on placental growth factor-based models. For the second trimester, Placental growth factor-based models achieved the highest diagnostic odds ratio for the prediction of early preeclampsia in the total population compared with placental growth factor alone and soluble fms-like tyrosine kinase-1-placental growth factor ratio (placental growth factor-based models, 63.20; 95% confidence interval, 37.62-106.16 vs soluble fms-like tyrosine kinase-1-placental growth factor ratio, 6.96; 95% confidence interval, 1.76-27.61 vs placental growth factor alone, 5.62; 95% confidence interval, 3.04-10.38); placental growth factor-based models had higher diagnostic odds ratio than placental growth factor alone for the identification of any-onset preeclampsia in the unselected population (28.45; 95% confidence interval, 13.52-59.85 vs 7.09; 95% confidence interval, 3.74-13.41). For the third trimester, Placental growth factor-based models achieved prediction for any-onset preeclampsia that was significantly better than that of placental growth factor alone but similar to that of soluble fms-like tyrosine kinase-1-placental growth factor ratio (placental growth factor-based models, 27.12; 95% confidence interval, 21.67-33.94 vs placental growth factor alone, 10.31; 95% confidence interval, 7.41-14.35 vs soluble fms-like tyrosine kinase-1-placental growth factor ratio, 14.94; 95% confidence interval, 9.42-23.70).

CONCLUSION

Placental growth factor with maternal factors ± other biomarkers determined in the second trimester achieved the best predictive performance for early preeclampsia in the total population. However, in the third trimester, placental growth factor-based models had predictive performance for any-onset preeclampsia that was better than that of placental growth factor alone but similar to that of soluble fms-like tyrosine kinase-1-placental growth factor ratio. Through this meta-analysis, we have identified a large number of very heterogeneous studies. Therefore, there is an urgent need to develop standardized research using the same models that combine serum placental growth factor with maternal factors ± other biomarkers to accurately predict preeclampsia. Identification of patients at risk might be beneficial for intensive monitoring and timing delivery.

The function and mechanism of action of uterine microecology in pregnancy immunity and its complications

The human microbiota influences physiology, disease, and metabolic reproduction. The origin of uterine bacteria is controversial. The main assumption is that the germs enter the uterine cavity from the vagina through the cervical canal, bloodstream, fallopian tubes, and gynecological surgical channels. Understanding the microbiota at various anatomical sites is critical to the female reproductive system and pregnancy. Today's study focuses on the role of uterine bacteria in pregnancy and embryo implantation. According to our findings, the uterine microbiome influences embryo implantation and pregnancy outcome. Pregnancy is a natural, evolutionarily selected approach to human reproduction. During pregnancy, the microbiota of the reproductive tract changes, facilitating the maintenance of pregnancy, and the human immune system undergoes a series of changes that recognize and adapt to the non-self. From the beginning of pregnancy, a non-self fetus must establish a placenta of embryonic origin to protect itself and promote growth; the VMB tends to be more stable and lactobacillus-dominated in late gestation than in early gestation. Any material that disrupts this connection, such as microbial changes, is associated with a higher risk of poor health and poor pregnancy outcomes in women (eclampsia). The presence of any material that disrupts this connection, such as microbial changes, is associated with a higher risk of poor health and poor pregnancy outcomes (preeclampsia, preterm birth, gestational diabetes, etc.). In this work, we review the last decade of relevant research to improve our understanding of the mechanisms by which the microbiota of the female reproductive tract influences female reproductive health. This work discusses the mechanisms associated with the reproductive tract microbiota and pregnancy immunity, as well as the impact of an abnormal microbiota on adverse pregnancy outcomes. Emphasis is placed on the characteristics and sources of the female vaginal, uterine, and placental microbiota and the importance of a well-stabilized local human microbiota and immune system for embryo implantation, placental development, fetal growth, and pregnancy outcome.

Multi-omics and machine learning for the prevention and management of female reproductive health

Females typically carry most of the burden of reproduction in mammals. In humans, this burden is exacerbated further, as the evolutionary advantage of a large and complex human brain came at a great cost of women's reproductive health. Pregnancy thus became a highly demanding phase in a woman's life cycle both physically and emotionally and therefore needs monitoring to assure an optimal outcome. Moreover, an increasing societal trend towards reproductive complications partly due to the increasing maternal age and global obesity pandemic demands closer monitoring of female reproductive health. This review first provides an overview of female reproductive biology and further explores utilization of large-scale data analysis and -omics techniques (genomics, transcriptomics, proteomics, and metabolomics) towards diagnosis, prognosis, and management of female reproductive disorders. In addition, we explore machine learning approaches for predictive models towards prevention and management. Furthermore, mobile apps and wearable devices provide a promise of continuous monitoring of health. These complementary technologies can be combined towards monitoring female (fertility-related) health and detection of any early complications to provide intervention solutions. In summary, technological advances (e.g., omics and wearables) have shown a promise towards diagnosis, prognosis, and management of female reproductive disorders. Systematic integration of these technologies is needed urgently in female reproductive healthcare to be further implemented in the national healthcare systems for societal benefit.

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.

Blood biomarkers to predict the onset of pre-eclampsia: A systematic review and meta-analysis

Pre-eclampsia is one of the most common pregnancy complications, and a major cause of fetal and maternal morbidity and mortality globally. Diagnosis currently takes place in the third trimester based on clinical symptoms. This systematic review and meta-analysis sought to determine the blood biomarkers that are associated with pre-eclampsia, and in particular, the biomarkers that could predict pre-eclampsia in early pregnancy. We searched the electronic databases (Medline, Embase, Cochrane Library) from inception up to March 2022. Prospective studies with 1000 or more participants that measured blood biomarkers to predict or diagnose pre-eclampsia have been included in this systematic review. Biomarkers' measurements were considered from the first up to the third trimester, but not during labor. Data concerning pre-eclampsia, biomarker measurements and study characteristics were extracted. Meta-analysis was performed when possible. We found a total of 43 studies (assessing 62 different biomarkers in 18,170 pregnancies, have been included in this systematic review, and a total of 6 studies (assessing 2 biomarkers have been included in the meta-analysis). Statistical analysis was performed for PlGF and sFlt-1. Mean difference in PlGF levels between pre-eclampsia and healthy pregnancies, appear to increase as the pregnancy progresses. Results of sFlt-1 meta-analysis were inconclusive. No significant publication bias was identified. This is the most comprehensive and up to date systematic review and meta-analysis on this important topic on blood biomarkers for the early prediction of pre-eclampsia. Further This research highlights the urgent needed for further discovery research to identify blood biomarkers that could predict the development of pre-eclampsia.

Dissecting the Roles of Lipids in Preeclampsia

Preeclampsia is a multisystem pregnancy disorder that is characterized by different degrees of placental malperfusion, with release of antiangiogenic factors into the circulation, leading to maternal vascular endothelial injury and high blood pressure. As a major cause of maternal and perinatal mortality and morbidity worldwide, once preeclampsia has been diagnosed, there are no curative treatments except for delivery. Lipids serve as ubiquitous and multifunctional metabolites that are integral and essential to many diverse functions on both a cellular and organismal level. Lipid metabolic abnormalities have emerged as potential risk factors for the development and progression of preeclampsia. This review comprehensively examines decades of discovery to illuminate the roles of lipids and dysregulation in the levels of various lipid classes in preeclampsia. In addition, the roles of lipids are summarized to further understand the pathogenic mechanisms of preeclampsia. Overall, the review highlights the promising potential of pathophysiology and lipid-targeting therapeutic strategies in preeclampsia.

Proteinuria during pregnancy: definition, pathophysiology, methodology, and clinical significance

Qualitative and quantitative measurement of urine protein excretion is one of the most common tests performed during pregnancy. For more than 100 years, proteinuria was necessary for the diagnosis of preeclampsia, but recent guidelines recommend that proteinuria is sufficient but not necessary for the diagnosis. Still, in clinical practice, most patients with gestational hypertension will be diagnosed as having preeclampsia based on the presence of proteinuria. Although the reference standard for measuring urinary protein excretion is a 24-hour urine collection, spot urine protein-to-creatinine ratio is a reasonable "rule-out" test for proteinuria. Urine dipstick screening for proteinuria does not provide any clinical benefit and should not be used to diagnose proteinuria. The classic cutoff cited to define proteinuria during pregnancy is a value of >300 mg/24 hours or a urine protein-to-creatinine ratio of at least 0.3. Using this cutoff, the rate of isolated proteinuria in pregnancy may reach 8%, whereas preeclampsia occurs among 3% to 8% of pregnancies. Although this threshold is widely accepted, its origin is not based on evidence on adverse pregnancy outcomes but rather on expert opinion and results of small studies. After reviewing the available data, the most important factor that influences maternal and neonatal outcome is the severity of blood pressures and presence of end organ damage, rather than the excess protein excretion. Because the management of gestational hypertension and preeclampsia without severe features is almost identical in frequency of surveillance and timing of delivery, the separation into 2 disorders is unnecessary. If the management of women with gestational hypertension with a positive assessment of proteinuria will not change, we believe that urine assessment for proteinuria is unnecessary in women who develop new-onset blood pressure at or after 20 weeks' gestation. Furthermore, we do not recommend repeated measurement of proteinuria for women with preeclampsia, the amount of proteinuria does not seem to be related to poor maternal and neonatal outcomes, and monitoring proteinuria may lead to unindicated preterm deliveries and related neonatal complications. Our current diagnosis of preeclampsia in women with chronic kidney disease may be based on a change in protein excretion, a baseline protein excretion evaluation is critical in certain conditions such as chronic hypertension, diabetes, and autoimmune or other renal disorders. The current definition of superimposed preeclampsia possesses a diagnostic dilemma, and it is unclear whether a change in the baseline proteinuria reflects another systemic disease such as preeclampsia or whether women with chronic disease such as chronic hypertension or diabetes will experience a different "normal" pattern of protein excretion during pregnancy. Finally, limited data are available regarding angiogenic and other biomarkers in women with chronic kidney disease as a potential aid in distinguishing the worsening of baseline chronic kidney disease and chronic hypertension from superimposed preeclampsia.

External validation of prognostic models to predict stillbirth using International Prediction of Pregnancy Complications (IPPIC) Network database: individual participant data meta-analysis

OBJECTIVE

Stillbirth is a potentially preventable complication of pregnancy. Identifying women at high risk of stillbirth can guide decisions on the need for closer surveillance and timing of delivery in order to prevent fetal death. Prognostic models have been developed to predict the risk of stillbirth, but none has yet been validated externally. In this study, we externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance.

METHODS

MEDLINE, EMBASE, DH-DATA and AMED databases were searched from inception to December 2020 to identify studies reporting stillbirth prediction models. Studies that developed or updated prediction models for stillbirth for use at any time during pregnancy were included. IPD from cohorts within the International Prediction of Pregnancy Complications (IPPIC) Network were used to validate externally the identified prediction models whose individual variables were available in the IPD. The risk of bias of the models and cohorts was assessed using the Prediction study Risk Of Bias ASsessment Tool (PROBAST). The discriminative performance of the models was evaluated using the C-statistic, and calibration was assessed using calibration plots, calibration slope and calibration-in-the-large. Performance measures were estimated separately in each cohort, as well as summarized across cohorts using random-effects meta-analysis. Clinical utility was assessed using net benefit.

RESULTS

Seventeen studies reporting the development of 40 prognostic models for stillbirth were identified. None of the models had been previously validated externally, and the full model equation was reported for only one-fifth (20%, 8/40) of the models. External validation was possible for three of these models, using IPD from 19 cohorts (491 201 pregnant women) within the IPPIC Network database. Based on evaluation of the model development studies, all three models had an overall high risk of bias, according to PROBAST. In the IPD meta-analysis, the models had summary C-statistics ranging from 0.53 to 0.65 and summary calibration slopes ranging from 0.40 to 0.88, with risk predictions that were generally too extreme compared with the observed risks. The models had little to no clinical utility, as assessed by net benefit. However, there remained uncertainty in the performance of some models due to small available sample sizes.

CONCLUSIONS

The three validated stillbirth prediction models showed generally poor and uncertain predictive performance in new data, with limited evidence to support their clinical application. The findings suggest methodological shortcomings in their development, including overfitting. Further research is needed to further validate these and other models, identify stronger prognostic factors and develop more robust prediction models. © 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

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.

Serum biomarkers for the prediction and diagnosis of preeclampsia: A meta-analysis

Objective

Preeclampsia is a major risk factor for maternal and foetal mortality and morbidity. There have been tremendous efforts to identify serum biomarkers which can reliably predict the occurrence of preeclampsia. The study aims to assess the biomarkers that have the greatest utility in the diagnosis of preeclampsia.

Methods

A systematic search was performed on the PubMed literature database, and chain references were retrieved. Original research articles composed of case controls, cohorts, randomised control trials, and cross-sectional studies were included. The recorded variables included each study's design, type, year, and location; the value (mean ± standard deviation) of the markers in the patients and the pregnant controls; and the p-value, unit of measurement, and the sample size of each study. The results were interpreted based on the standardised mean difference (SMD) values.

Results

A total of 398 studies were retrieved from the PubMed database. After further analysis, 89 studies were selected for this review. An additional 47 studies were included based on chain referencing. Later, 136 full-text articles were reviewed in detail and their data were entered. Finally, 25 studies, in which 13 serum biomarkers were assessed, were selected for this meta-analysis. The levels of the angiogenic markers fms-like tyrosine kinase (sFlt), sFlt/placental growth factor (PlGF), and endoglin were significantly higher in patients with preeclampsia than in the pregnant controls. The levels of PlGF and the lipid biomarkers high density lipoprotein (HDL) and adiponectin were significantly lower, while the levels of triglycerides, apolipoprotein B (APO-B), and leptin were elevated in the preeclamptic patients compared to the pregnant controls (p < 0.05).

Conclusion

In our study, the values of the serum biomarkers sFlt, PlGF, sFlt/PlGF, HDL, adiponectin, leptin, triglycerides, and APO-B differed significantly between preeclampsia patients and the pregnant controls. These findings demand advanced evaluation of biomarkers to enhance diagnostic screening for preeclampsia.

Pre-eclampsia

Pre-eclampsia is a multisystem pregnancy disorder characterised by variable degrees of placental malperfusion, with release of soluble factors into the circulation. These factors cause maternal vascular endothelial injury, which leads to hypertension and multi-organ injury. The placental disease can cause fetal growth restriction and stillbirth. Pre-eclampsia is a major cause of maternal and perinatal mortality and morbidity, especially in low-income and middle-income countries. Prophylactic low-dose aspirin can reduce the risk of preterm pre-eclampsia, but once pre-eclampsia has been diagnosed there are no curative treatments except for delivery, and no drugs have been shown to influence disease progression. Timing of delivery is planned to optimise fetal and maternal outcomes. Clinical trials have reported diagnostic and prognostic strategies that could improve fetal and maternal outcomes and have evaluated the optimal timing of birth in women with late preterm pre-eclampsia. Ongoing studies are evaluating the efficacy, dose, and timing of aspirin and calcium to prevent pre-eclampsia and are evaluating other drugs to control hypertension or ameliorate disease progression.

Maternal microbiome in preeclampsia pathophysiology and implications on offspring health

Preeclampsia is a devastating hypertensive pregnancy disorder that currently affects 2%–8% of pregnancies worldwide. It is associated with maternal and fetal mortality and morbidity and adverse health outcomes both in mom and offspring beyond pregnancy. The pathophysiology is not completely understood, and there are no approved therapies to specifically treat for the disease, with only few therapies approved to manage symptoms. Recent advances suggest that aberrations in the composition of the microbiome may play a role in the pathogenesis of various diseases including preeclampsia. The maternal and uteroplacental environments greatly influence the long‐term health outcomes of the offspring through developmental programming mechanisms. The current review summarizes recent developments on the role of the microbiome in adverse pregnancy outcomes with a focus on preeclampsia. It also discusses the potential role of the maternal microbiome in fetal programming; explores gut‐targeted therapeutics advancement and their implications in the treatment of preeclampsia.

The ROBINS-I and the NOS had similar reliability but differed in applicability: A random sampling observational studies of systematic reviews/meta-analysis

OBJECTIVE

There is a lack of evidence on the usage of the quality assessment tool-the Risk Of Bias In Nonrandomized Studies-of Interventions (ROBINS-I). This article aimed to measure the reliability, criterion validity, and feasibility of the ROBINS-I and the Newcastle-Ottawa Scale (NOS).

METHODS

A sample of systematic reviews or meta-analyses of observational studies were selected from Medline (2013-2017) and assessed by two reviewers using ROBINS-I and the NOS. We reported on reliability in terms of the first-order agreement coefficient (AC1) statistic. Correlation coefficient statistic was used to explore the criterion validity of the ROBINS-I. We compared the feasibility of the ROBINS-I and NOS by recording the time to complete an assessment and the instances where assessing was difficult.

RESULTS

Five systematic reviews containing 41 cohort studies were finally included. Interobserver agreement on the individual domain of the ROBINS-I as well as the NOS was substantial with a mean AC1 statistic of 0.67 (95% CI: 0.50-0.83) and 0.73 (95% CI: 0.65-0.81), respectively. The criterion validity of the ROBNS-I was moderate (K = 0.52) against NOS. The time in assessing a single study by ROBINS-I varied from 7 hours initially to 3 hours compared with 30 minutes for the NOS. Both reviewers rated "bias due to departure from the intended interventions" the most time-consuming domain in the ROBINS-I, items in the NOS were equal.

CONCLUSIONS

The ROBINS-I and the NOS seem to provide the same reliability but vary in applicability. The over-complicated feature of ROBINS-I may limit its usage and a simplified version is needed.

Proteomic signatures predict preeclampsia in individual cohorts but not across cohorts - implications for clinical biomarker studies

Background:

Early identification of pregnant women at risk for preeclampsia (PE) is important, as it will enable targeted interventions ahead of clinical manifestations. The quantitative analyses of plasma proteins feature prominently among molecular approaches used for risk prediction. However, derivation of protein signatures of sufficient predictive power has been challenging. The recent availability of platforms simultaneously assessing over 1000 plasma proteins offers broad examinations of the plasma proteome, which may enable the extraction of proteomic signatures with improved prognostic performance in prenatal care.

Objective:

The primary aim of this study was to examine the generalizability of proteomic signatures predictive of PE in two cohorts of pregnant women whose plasma proteome was interrogated with the same highly multiplexed platform. Establishing generalizability, or lack thereof, is critical to devise strategies facilitating the development of clinically useful predictive tests. A second aim was to examine the generalizability of protein signatures predictive of gestational age (GA) in uncomplicated pregnancies in the same cohorts to contrast physiological and pathological pregnancy outcomes.

Study design:

Serial blood samples were collected during the first, second, and third trimesters in 18 women who developed PE and 18 women with uncomplicated pregnancies (Stanford cohort). The second cohort (Detroit), used for comparative analysis, consisted of 76 women with PE and 90 women with uncomplicated pregnancies. Multivariate analyses were applied to infer predictive and cohort-specific proteomic models, which were then tested in the alternate cohort. Gene ontology (GO) analysis was performed to identify biological processes that were over-represented among top-ranked proteins associated with PE.

Results:

The model derived in the Stanford cohort was highly significant (p = 3.9E–15) and predictive (AUC = 0.96), but failed validation in the Detroit cohort (p = 9.7E–01, AUC = 0.50). Similarly, the model derived in the Detroit cohort was highly significant (p = 1.0E–21, AUC = 0.73), but failed validation in the Stanford cohort (p = 7.3E–02, AUC = 0.60). By contrast, proteomic models predicting GA were readily validated across the Stanford (p = 1.1E–454, R = 0.92) and Detroit cohorts (p = 1.1.E–92, R = 0.92) indicating that the proteomic assay performed well enough to infer a generalizable model across studied cohorts, which makes it less likely that technical aspects of the assay, including batch effects, accounted for observed differences.

Conclusions:

Results point to a broader issue relevant for proteomic and other omic discovery studies in patient cohorts suffering from a clinical syndrome, such as PE, driven by heterogeneous pathophysiologies. While novel technologies including highly multiplex proteomic arrays and adapted computational algorithms allow for novel discoveries for a particular study cohort, they may not readily generalize across cohorts. A likely reason is that the prevalence of pathophysiologic processes leading up to the “same” clinical syndrome can be distributed differently in different and smaller-sized cohorts. Signatures derived in individual cohorts may simply capture different facets of the spectrum of pathophysiologic processes driving a syndrome. Our findings have important implications for the design of omic studies of a syndrome like PE. They highlight the need for performing such studies in diverse and well-phenotyped patient populations that are large enough to characterize subsets of patients with shared pathophysiologies to then derive subset-specific signatures of sufficient predictive power.

Comparative risks and predictors of preeclamptic pregnancy in the Eastern, Western and developing world

Preeclampsia (PE) is a complication of pregnancy characterized by hypertension (HTN-Preg), and often proteinuria. If not managed promptly, PE could lead to eclampsia and seizures. PE could also lead to intrauterine growth restriction (IUGR) and prematurity at birth. Although PE is a major cause of maternal and fetal morbidity and mortality, the underlying mechanisms are unclear. Also, there is a wide variability in the incidence of PE, ranging between 2 and 8% of pregnancies in the Eastern, Western and Developing world, suggesting regional differences in the risk factors and predictors of the pregnancy-related disorder. Several demographic, genetic, dietary and environmental factors, as well as maternal circulating biomarkers have been associated with PE. Demographic factors such as maternal race and ethnicity could play a role in PE. Specific genetic polymorphisms have been identified in PE. Maternal age, parity, education and socioeconomic status could be involved in PE. Dietary fat, protein, calcium and vitamins, body weight, and environmental factors including climate changes and air pollutants could also play a role in PE. Several circulating cytoactive factors including anti-angiogenic factors and cytokines have also been associated with PE. Traditional midwifery care is a common practice in local maternity care units, while advanced perinatal care and new diagnostic tools such as uterine artery Doppler velocimetry have been useful in predicting early PE in major medical centers. These PE risk factors, early predictors and diagnostic tools vary vastly in different regions of the Eastern, Western and Developing world. Further understanding of the differences in the demographic, genetic, dietary and environmental factors among pregnant women in different world regions should help in designing a region-specific cluster of risk factors and predictors of PE, and in turn provide better guidance for region-specific tools for early detection and management of PE.

Potential Protein Biomarkers for Preeclampsia

To date, the etiology of preeclampsia (PE) has not been clarified and the specific treatment is lacking; hence, early prediction and prevention are very important. Thus, a large number of biomarkers that may be associated with PE have been identified based on proteomics to provide a reference for the prediction of PE and for the understanding of the pathological mechanisms of this disease. This article briefly summarizes the application of proteomics in PE and the potential protein biomarkers to provide a reference for other researchers.

Soluble fms-like tyrosine kinase 1 and placental growth factor ratio for predicting preeclampsia in elderly gravida

Objective: To determine the predictive value of plasma soluble fms-like tyrosine kinase 1 (sFlt-1) and placental growth factor (PlGF) ratio for detection of preeclampsia in elderly gravida at 16-18 weeks of gestation and to identify whether abnormalities of this ratio are associated with any other pregnancy complications or not.Methods: Blood samples of 300 cases were collected. Plasma sFlt-1 and PlGF levels were measured using an automated immunoassay.Results: Sensitivity and specificity for plasma sFlt-1/PlGF ratio above 9.8 for preeclampsia prediction were 85.7% and 61.2%, respectively. The sensitivity and specificity to predict early onset preeclampsia were 100% and 61.1%, respectively. Women with abnormal plasma sFlt-1/PlGF ratio were not associated with any other pregnancy complications.Conclusion:  sFlt-1/PlGF ratio at 16-18 weeks of gestation in elderly gravida has a high sensitivity for predicting preeclampsia, especially early onset preeclampsia.

Altered level of salivary placental growth factor is associated with preeclampsia

A pilot, case-control study was conducted to compare the concentrations of placental growth factor (PlGF) and placental alkaline phosphatase (PLAP) in saliva of preeclampsia (PE) patients with normotensive controls in the second and third trimesters. Measured by ELISA assays, levels of salivary PlGF were significantly lower in PE patients (n = 13) compared to controls (n = 15) (two-way ANOVA, p = 0.0208) independent of gestational age at time of collection (p = 0.49). Salivary PLAP differences between PE and controls were not statistically significant. Placenta-specific proteins are detectable in maternal saliva and may serve as noninvasive biomarkers to monitor placenta health and disease during pregnancy.

Biosensors for Detection of Human Placental Pathologies: A Review of Emerging Technologies and Current Trends

Substantial growth in the biosensor research has enabled novel, sensitive and point-of-care diagnosis of human diseases in the last decade. This paper presents an overview of the research in the field of biosensors that can potentially predict and diagnosis of common placental pathologies. A survey of biomarkers in maternal circulation and their characterization methods is presented, including markers of oxidative stress, angiogenic factors, placental debris, and inflammatory biomarkers that are associated with various pathophysiological processes in the context of pregnancy complications. Novel biosensors enabled by microfluidics technology and nanomaterials is then reviewed. Representative designs of plasmonic and electrochemical biosensors for highly sensitive and multiplexed detection of biomarkers, as well as on-chip sample preparation and sensing for automatic biomarker detection are illustrated. New trends in organ-on-a-chip based placental disease models are highlighted to illustrate the capability of these in vitro disease models in better understanding the complex pathophysiological processes, including mass transfer across the placental barrier, oxidative stress, inflammation, and malaria infection. Biosensor technologies that can be potentially embedded in the placental models for real time, label-free monitoring of these processes and events are suggested. Merger of cell culture in microfluidics and biosensing can provide significant potential for new developments in advanced placental models, and tools for diagnosis, drug screening and efficacy testing.

Maternal vascular malformation in the placenta is an indicator for fetal growth restriction irrespective of neonatal birthweight

INTRODUCTION

To study the association between placental pathology and neonatal birthweight and outcomes, and whether a combination of first trimester biomarkers and fetal growth velocity can predict placental lesions.

METHODS

The presence of maternal vascular malperfusion (MVM) lesions (Amsterdam criteria) was recorded in a retrospective cohort of singleton pregnancies in the Maastricht University Medical Centre, 2011-2018. First trimester maternal characteristics and PAPP-A, PlGF and sFlt-1 levels were collected. Fetal growth velocities were calculated (mm/week) from 20 to 32 weeks for abdominal circumference, biparietal diameter, head circumference and femur length. Data were compared between neonates with 'small for gestational age' (SGA < p10) and different categories of 'appropriate for gestational age (AGA)': AGAp10-30, AGAp30-50 and AGA > p50 (reference), using one-way ANOVA and post hoc test.

RESULTS

There were significantly more MVM lesions in the SGA group (94.6% p < .0001), but also in the AGAp10-30 (67.3% p < .0001) and AGAp30-50 (41.6% p = 0.002), compared to the reference AGA group (19.3%). The prediction of MVM for a 20% false-positive rate, with maternal characteristics was25.2%. The addition of birthweight percentile gave a prediction of 51.7% for MVM. However adding placental biomarkers and fetal growth velocities (instead of birthweight percentile) to the maternal characteristics, gave a prediction of 81.8% (PPV 49.5%, NPV 53.7%).

DISCUSSION

Placental MVM lesions correlated inversely with birthweight even in AGA neonates, and was associated with slower fetal growth and more adverse outcome in SGA neonates. A combination of first trimester biomarkers and fetal growth velocity had good prediction of placental MVM lesions, as an indicator of fetal growth restriction irrespective of neonatal weight.

Profiles of circular RNAs in human placenta and their potential roles related to preeclampsia

To identify the profiles of circular RNAs (circRNAs) in human placental tissues and to explore the potential roles of dysregulated circRNAs in the pathological genesis of preeclampsia, expression profiles of circRNAs in human placentas were performed in this study. Utilizing high-throughput technology, based on fold changes and P values, 300 circRNAs that are differentially expressed between preeclampsia and normal placental tissues were identified. Among them, hg38_circ_0014736 and hsa_circ_0015382 were validated as significantly upregulated by real-time quantitative PCR with divergent primers. At the same time, hsa_circ_0007121 was significantly downregulated. GO analysis revealed that the three altered circRNAs had a relationship with transcription regulation, proliferation, protein binding, and response to hypoxia. KEGG analysis yielded that apoptosis, Wnt signaling, and HIF-1 pathways were significantly enriched. Interestingly, hsa_circ_0007121 was found to be expressed differently in plasma between preeclampsia and normal pregnancy and this difference could be detected before 20 gestational weeks. Besides, addition receiver operating characteristic (ROC) curve analysis showed that the area under the ROC curve of hsa_circ_0007121 reached 0.72 ([0.59-0.85], P = 0.004) with a sensitivity of 0.77 and specificity of 0.70. Collectively, this study demonstrates the existence of dysregulated circRNAs in the placenta of preeclampsia patients and annotates their potential roles in the pathogenesis of the disease. Encouragingly, hsa_circ_0007121 was found to be a potential noninvasive biomarker for the prediction of preeclampsia.

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.

Clinical Pharmacology and Pharmacometrics to Better Understand Physiological Changes During Pregnancy and Neonatal Life

Pregnant women, fetuses, and newborns are particularly vulnerable patient populations. During pregnancy, the body is subject to physiological changes that influence the pharmacokinetics and pharmacodynamics of drugs. Inappropriate dosing in pregnant women can result in sub-therapeutic or toxic effects, putting not only the pregnant woman but also her fetus at risk. During neonatal life, maturation processes also affect pharmacokinetics and pharmacodynamics of drugs. Inappropriate dosing in newborns leads not only to short-term complications but can also have a negative impact on the long-term development of infants and children. For these reasons, it is crucial to characterize physiological changes in pregnant women, describe placental transfer kinetics of drugs, and describe physiological changes related to the transition from intrauterine to extrauterine life and maturation processes in preterm and term neonates. Quantitative pharmacological approaches such as pharmacometric and physiologically-based modeling and model-based simulations can be useful to better understand and predict such physiological changes and their effects on drug exposure and response. This review article (1) gives an overview of physiological changes in pregnant women, their fetuses, and (pre)term neonates, (2) presents case studies to illustrate applications of new modeling and simulation approaches, and (3) discusses challenges and opportunities in optimizing and personalizing treatments during pregnancy and neonatal life.

Statistical and artificial neural network-based analysis to understand complexity and heterogeneity in preeclampsia

Preeclampsia is a pregnancy associated disease. It is characterized by high blood pressure and symptoms that are indicative of damage to other organ systems, most often involving the liver and kidneys. If left untreated, the condition could be fatal to mother and baby. This makes it important to delineate the complexities associated with the disease at a molecular level that would help develop methods for early diagnosis. In microarray-based studies, Textoris et al. and Mirzakhani et al. have analyzed the transcriptome with a view to identify biomarkers for preeclampsia. The current study has extensively analyzed these microarray data sets to understand the complexity and heterogeneity associated with preeclampsia. A statistical multiple comparisons-based approach has been used to identify features capable of distinguishing preeclampsia from normotensive cases. These features were then used to build an artificial neural network-based machine learning model that successfully classified the samples. Further, the machine learning model was used to delineate features critical for its internal representation by extending the calliper randomization approach to the analysis of microarray data. Functional analysis of the features identified by the calliper randomization approach revealed pathways that could be crucially involved in the mechanism of the underlying disease. Biological processes associated with the features identified have revealed among others, genes involved in reproductive processes to be differentially expressed.

Prospective biomarkers in preterm preeclampsia: A review

Preterm pre-eclampsia (prior to 37 weeks' gestation) remains a major cause of maternal and fetal morbidity and mortality particularly in low to middle income countries. Much research has focused on first and second trimester predictors of pre-eclampsia with the aim of allowing stratification of antenatal care and trialling of potential preventative and therapeutic agents. However, none have been shown to be of benefit in randomised controlled trials. In this literature review we critically evaluate predictive and diagnostic tests for preterm pre-eclampsia and discuss their clinical use and potential value in the management of preterm pre-eclampsia. We defined preterm pre-eclampsia as pre-eclampsia occurring prior to 37 weeks' gestation. Substantial progress has been made in the development of predictive screening tests for preterm pre-eclampsia, but further research is needed prior to their introduction and integration into routine clinical practice. The performance of diagnostic tests mainly utilising angiogenic and anti-angiogenic factors for determining time to delivery in later pregnancy currently hold more promise than first trimester predictive tests, possible reflecting the heterogeneity of pre-eclampsia.

Oxidative stress in placental pathology

The most important function of the placenta is the exchange of nutrients and oxygen between a mother and her fetus. To establish a healthy functioning placenta, placentation needs to occur with adequate remodelling of spiral arteries by extravillous trophoblasts. When this process is impaired, the resulting suboptimal and inadequate placenta function results in the manifestation of pregnancy complications. Impaired placenta function can cause preeclampsia and leads to fetal growth restriction due to hypoxia. Presence of hypoxia leads to oxidative stress due to an imbalance between reactive oxygen species and antioxidants, thereby causing damage to proteins, lipids and DNA. In the placenta, signs of morphological adaptation in response to hypoxia can be found. Different placental lesions like maternal or fetal vascular malperfusion or chronic villitis lead to a decreased exchange of oxygen between the mother and the fetus. Clinically, several biomarkers indicative for oxidative stress, e.g. malondialdehyde and reduced levels of free thiols are found. This review aims to give an overview of the causes and (potential) role of placental oxidative stress in the development of placental parenchymal pathology and its clinical consequences. Also, therapeutic options aiming at prevention or treatment of hypoxia of the placenta and fetus are described.

Angiogenic factors: potential to change clinical practice in pre-eclampsia?

Pre‐eclampsia is a complex disease with significant maternal and fetal morbidity and mortality. Its syndromic nature makes diagnosis and management difficult. The field is rapidly evolving with the definition of pre‐eclampsia being challenged by some organisations, with proteinuria no longer being essential in the presence of other features. In the last decade, angiogenic factors, in particular soluble fms‐like tyrosine kinase 1 (sFlt‐1), have emerged as important molecules in the pathogenesis of pre‐eclampsia. Here we review the most recent evidence regarding the potential of these factors as biomarkers and therapeutic targets for pre‐eclampsia.

Tweetable abstract

A review of angiogenic factors, sFlt‐1 and PlGF, in the diagnosis, prediction and management of pre‐eclampsia.

A review of angiogenic factors, sFlt‐1 and PlGF, in the diagnosis, prediction and management of pre‐eclampsia.

Antithrombin improves the maternal and neonatal outcomes but not the angiogenic factors in extremely growth-restricted fetuses at <28 weeks of gestation

AIMS

Severe preterm fetal growth restriction (FGR) remote from term is problematic. We aimed to investigate the effect of maternally-administered antithrombin on maternal and neonatal outcomes. A prospective, one-arm, pilot study was performed in 14 women with severe FGR (≤5th centile) at <28 weeks of gestation, without hypertensive disorders. Maternal plasma concentrations of soluble Feline McDonough Sarcoma (FMS)-like trypsin kinase-1 (sFlt-1) and placental growth factor (PlGF) were measured and categorized into three groups: group 1; low sFlt-1 and high PlGF, group 2; moderate sFlt-1 and low PlGF, and group 3; high sFlt-1 and low PlGF. Antithrombin was administered for 3 days. The incidence of perinatal mortality, infant morbidity, and the period of pregnancy prolongation were compared.

RESULTS

In group 1 (n=4), their pregnancies were extended for longer periods and the maternal and infant outcomes were good. The prolongation periods were shorter in groups 2 (n=3) and 3 (n=7), which resulted in poor maternal [severe preeclampsia or hemolysis, elevated liver enzymes, and low platelet count (HELLP) syndrome] and infant outcomes.

CONCLUSIONS

The evaluation of the maternal sFlt-1 and PlGF at 21-27 weeks of gestation is useful in the managements of severe FGR. Antithrombin treatment could prolong the pregnancies with low sFlt-1 and high PlGF without negatively affecting maternal or fetal health.

Vascular Dysfunction in Mother and Offspring During Preeclampsia: Contributions from Latin-American Countries

Pregnancy is a physiologically stressful condition that generates a series of functional adaptations by the cardiovascular system. The impact of pregnancy on this system persists from conception beyond birth. Recent evidence suggests that vascular changes associated with pregnancy complications, such as preeclampsia, affect the function of the maternal and offspring vascular systems, after delivery and into adult life. Since the vascular system contributes to systemic homeostasis, defective development or function of blood vessels predisposes both mother and infant to future risk for chronic disease. These alterations in later life range from fertility problems to alterations in the central nervous system or immune system, among others. It is important to note that rates of morbi-mortality due to pregnancy complications including preeclampsia, as well as cardiovascular diseases, have a higher incidence in Latin-American countries than in more developed countries. Nonetheless, there is a lack both in the amount and impact of research conducted in Latin America. An impact, although smaller, can be seen when research in vascular disorders related to problems during pregnancy is analyzed. Therefore, in this review, information about preeclampsia and endothelial dysfunction generated from research groups based in Latin-American countries will be highlighted. We relate the need, as present in many other countries in the world, for increased effective regional and international collaboration to generate new data specific to our region on this topic.

Metformin, the aspirin of the 21st century: its role in gestational diabetes mellitus, prevention of preeclampsia and cancer, and the promotion of longevity

Metformin is everywhere. Originally introduced in clinical practice as an antidiabetic agent, its role as a therapeutic agent is expanding to include treatment of prediabetes mellitus, gestational diabetes mellitus, and polycystic ovarian disease; more recently, experimental studies and observations in randomized clinical trials suggest that metformin could have a place in the treatment or prevention of preeclampsia. This article provides a brief overview of the history of metformin in the treatment of diabetes mellitus and reviews the results of metaanalyses of metformin in gestational diabetes mellitus as well as the treatment of obese, non-diabetic, pregnant women to prevent macrosomia. We highlight the results of a randomized clinical trial in which metformin administration in early pregnancy did not reduce the frequency of large-for-gestational-age infants (the primary endpoint) but did decrease the frequency of preeclampsia (a secondary endpoint). The mechanisms by which metformin may prevent preeclampsia include a reduction in the production of antiangiogenic factors (soluble vascular endothelial growth factor receptor-1 and soluble endoglin) and the improvement of endothelial dysfunction, probably through an effect on the mitochondria. Another potential mechanism whereby metformin may play a role in the prevention of preeclampsia is its ability to modify cellular homeostasis and energy disposition, mediated by rapamycin, a mechanistic target. Metformin has a molecular weight of 129 Daltons and therefore readily crosses the placenta. There is considerable evidence to suggest that this agent is safe during pregnancy. New literature on the role of metformin as a chemotherapeutic adjuvant in the prevention of cancer and in prolonging life and protecting against aging is reviewed briefly. Herein, we discuss the mechanisms of action and potential benefits of metformin.

Blood laboratory testing for early prediction of preeclampsia: chasing the finish line or at the starting blocks?

Preeclampsia (PE) affects 2-8% of pregnancies worldwide, thus representing an important cause of maternal and neonatal morbidity, up to death. Many studies have been designed to identify putative biomarkers for accurate and timely diagnosing PE, but only some of them were focused on specific and sensitive biomarkers for early prediction of this life-threatening condition. In particular, some prospective studies aimed to investigate the predictive role of circulating biomarkers before 20 weeks of gestation in the general pregnant population yielded conflicting results. This article is hence centered on results obtained in studies investigating the predictive performances of angiogenic, anti-angiogenic, inflammatory, endocrine, and epigenetic biomarkers. The available evidence suggests that angiogenic and anti-angiogenic molecules, in particular the sFlt1:PlGF ratio, may be considered the biomarkers with the best diagnostic performance in the second trimester. However, doubts remain about their use in clinical settings before the 20th gestational week. Even lower evidence is available for other biomarkers, due to the fact that some positive results have not been confirmed in ensuing investigations, whereas unresolved analytical issues still contribute to make their clinical reliability rather questionable. Differential expression of microRNAs seems also a promising evidence for early prediction of PE, but additional research and well-designed prospective studies are needed to identify and validate routine predictive tests. KEY MESSAGES Preeclampsia affects 2-8% of pregnant women worldwide, thus remaining one of the leading causes of maternal and neonatal morbidity and mortality. Several studies have investigated the predictive role of circulating biomarkers before 20th week of gestation with conflicting results. Additional research and well-designed prospective studies are needed to identify and validate predictive tests in clinical practice.

Prediction of complications in early-onset pre-eclampsia (PREP): development and external multinational validation of prognostic models

BACKGROUND

Unexpected clinical deterioration before 34 weeks gestation is an undesired course in early-onset pre-eclampsia. To safely prolong preterm gestation, accurate and timely prediction of complications is required.

METHOD

Women with confirmed early onset pre-eclampsia were recruited from 53 maternity units in the UK to a large prospective cohort study (PREP-946) for development of prognostic models for the overall risk of experiencing a complication using logistic regression (PREP-L), and for predicting the time to adverse maternal outcome using a survival model (PREP-S). External validation of the models were carried out in a multinational cohort (PIERS-634) and another cohort from the Netherlands (PETRA-216). Main outcome measures were C-statistics to summarise discrimination of the models and calibration plots and calibration slopes.

RESULTS

A total of 169 mothers (18%) in the PREP dataset had adverse outcomes by 48 hours, and 633 (67%) by discharge. The C-statistics of the models for predicting complications by 48 hours and by discharge were 0.84 (95% CI, 0.81-0.87; PREP-S) and 0.82 (0.80-0.84; PREP-L), respectively. The PREP-S model included maternal age, gestation, medical history, systolic blood pressure, deep tendon reflexes, urine protein creatinine ratio, platelets, serum alanine amino transaminase, urea, creatinine, oxygen saturation and treatment with antihypertensives or magnesium sulfate. The PREP-L model included the above except deep tendon reflexes, serum alanine amino transaminase and creatinine. On validation in the external PIERS dataset, the reduced PREP-S model showed reasonable calibration (slope 0.80) and discrimination (C-statistic 0.75) for predicting adverse outcome by 48 hours. Reduced PREP-L model showed excellent calibration (slope: 0.93 PIERS, 0.90 PETRA) and discrimination (0.81 PIERS, 0.75 PETRA) for predicting risk by discharge in the two external datasets.

CONCLUSIONS

PREP models can be used to obtain predictions of adverse maternal outcome risk, including early preterm delivery, by 48 hours (PREP-S) and by discharge (PREP-L), in women with early onset pre-eclampsia in the context of current care. They have a potential role in triaging high-risk mothers who may need transfer to tertiary units for intensive maternal and neonatal care.

TRIAL REGISTRATION

ISRCTN40384046 , retrospectively registered.

Prediction of Preeclampsia Using the Soluble fms-Like Tyrosine Kinase 1 to Placental Growth Factor Ratio: A Prospective Cohort Study of Unselected Nulliparous Women

We sought to assess the ratio of sFlt-1 (soluble fms-like tyrosine kinase 1) to PlGF (placental growth factor) in maternal serum as a screening test for preeclampsia in unselected nulliparous women with a singleton pregnancy. We studied 4099 women recruited to the POP study (Pregnancy Outcome Prediction) (Cambridge, United Kingdom). The sFlt-1:PlGF ratio was measured using the Roche Cobas e411 platform at ≈20, ≈28, and ≈36 weeks of gestational age (wkGA). Screen positive was defined as an sFlt-1:PlGF ratio >38, but higher thresholds were also studied. At 28 wkGA, an sFlt-1:PlGF ratio >38 had a positive predictive value (PPV) of 32% for preeclampsia and preterm birth, and the PPV was similar comparing women with low and high prior risk of disease. At 36 wkGA, an sFlt-1:PlGF ratio >38 had a PPV for severe preeclampsia of 20% in high-risk women and 6.4% in low-risk women. At 36 wkGA, an sFlt-1:PlGF ratio >110 had a PPV of 30% for severe preeclampsia, and the PPV was similar comparing low- and high-risk women. Overall, at 36 wkGA, 195 (5.2%) women either had an sFlt-1:PlGF ratio of >110 or an sFlt-1:PlGF ratio >38 plus maternal risk factors: 43% of these women developed preeclampsia, about half with severe features. Among low-risk women at 36 wkGA, an sFlt-1:PlGF ratio ≤38 had a negative predictive value for severe preeclampsia of 99.2%. The sFlt-1:PlGF ratio provided clinically useful prediction of the risk of the most important manifestations of preeclampsia in a cohort of unselected nulliparous women.

A longitudinal analysis of angiotensin II type 1 receptor antibody and angiogenic markers in pregnancy

BACKGROUND

Preeclampsia can be caused by shallow trophoblast invasion and results in endothelial dysfunction. Angiotensin II type 1 receptor antibodies may have a role in both processes. Other angiogenic markers (placental growth factor, soluble fms-like tyrosine kinase-1, and soluble endoglin) have been shown to alter before clinically evident preeclampsia.

OBJECTIVE

The aim of this study is to assess the longitudinal changes and utility of biomarker angiotensin II type 1 receptor antibodies and angiogenic markers in hypertensive disorders of pregnancy, gestational hypertension, and preeclampsia.

STUDY DESIGN

A longitudinal prospective cohort observational study of angiogenic markers and a secondary retrospective case-control study of angiotensin II type 1 receptor antibody changes were conducted. The studies were conducted in a large tertiary metropolitan teaching hospital (Sydney, Australia). Sequential recruitment of women with a singleton pregnancy (N = 351) was undertaken. Plasma concentrations of angiotensin II type 1 receptor antibodies, placental growth factor, soluble fms-like tyrosine kinase-1, and soluble endoglin were measured using validated enzyme-linked immunosorbent assays at 12, 18, 28, 36, and 40 weeks' gestation and 6 weeks' postpartum. Clinical, demographic, and pregnancy data were prospectively collected. Pregnancy outcomes were classified as normotensive, gestational hypertension, or preeclampsia. Analyses were carried out using software and significance set at P < .05.

RESULTS

In all, 351 women were recruited, 17 developed gestational hypertension, and 18 developed preeclampsia. Women with preeclampsia at baseline were heavier (P = .015), were taller (P = .046), and had higher systolic (P = .029) and diastolic (P = .006) blood pressure. The preeclampsia group had higher soluble fms-like tyrosine kinase-1 from ≥28 weeks (P = .003) and lower placental growth factor from 18 weeks (P = .004). Soluble endoglin and angiotensin II type 1 receptor antibodies did not vary over time or between groups. Angiotensin II type 1 receptor antibody (12 weeks) was positively correlated with serum pregnancy associated plasma protein A (P = .008) and human chorionic gonadotrophin (P = .04).

CONCLUSION

Angiogenic markers vary longitudinally during pregnancy and placental growth factor and soluble fms-like tyrosine kinase-1 have a role for predicting and diagnosing preeclampsia later in disease. Our data show that angiotensin II type 1 receptor antibodies are not sensitive for disease and hence not useful as a biomarker. Larger studies are required to describe the role and functionality of angiotensin II type 1 receptor antibodies in preeclampsia.

Review: Placental derived biomarkers of pregnancy disorders

Pregnancy is one of the greatest physiological challenges that a women can experience. The physiological adaptations that accompany pregnancy may increase the risk of developing a number of disorders that can lead to both acute and chronic physiological outcomes. In addition, fetal development may be impaired and, if the fetus survives, the child may be at an increased risk of disease throughout life. Pregnancy disorders are poorly predicted by traditional risk factors and maternal history alone. The identification of biomarkers that can predict incidence and severity of disease would allow for improved and targeted prophylactic therapies to prevent adverse maternal and fetal outcomes. Many of these pregnancy disorders, including preeclampsia, intrauterine growth restriction, gestational diabetes mellitus and preterm birth are known to be regulated at least in part by poor trophoblast invasion and/or dysregulated placental function. Cellular stress within the placenta increases the release of a number of factors into the maternal circulation. While many of these factors minimally impact maternal biology, others affect key physiological systems and contribute to disease. Importantly, these factors may be detected in physiological fluids and have predictive capacity making them ideal candidates as biomarkers of pregnancy disorders. This review will discuss what is known about these placental derived biomarkers of pregnancy disorders and highlight potential clinical opportunities for disease prediction and diagnosis.

Andrée Gruslin award lecture: Metabolomics as an important modality to better understand preeclampsia

Preeclampsia (PE) is a complex disorder that affects 3-5% of all pregnancies and is a leading cause of maternal and fetal morbidity and mortality. To date, the heterogeneity of clinical presentation, disease severity and outcomes have limited significant advances in early prediction, diagnosis, and therapeutic intervention of PE. The rapidly expanding field of metabolomics, which has the capacity to quantitatively detect low molecular weight compounds (metabolites) in tissue and biological fluids, shows tremendous promise in gaining a better understanding of PE. This review will discuss this emerging field and its contribution to recent advances in the understanding of PE pathophysiology, and identification of early predictive metabolic biomarkers for this complex disorder.

Preventing deaths due to the hypertensive disorders of pregnancy

In this chapter, taking a life cycle and both civil society and medically oriented approach, we will discuss the contribution of the hypertensive disorders of pregnancy (HDPs) to maternal, perinatal and newborn mortality and morbidity. Here we review various interventions and approaches to preventing deaths due to HDPs and discuss effectiveness, resource needs and long-term sustainability of the different approaches. Societal approaches, addressing sustainable development goals (SDGs) 2.2 (malnutrition), 3.7 (access to sexual and reproductive care), 3.8 (universal health coverage) and 3c (health workforce strengthening), are required to achieve SDGs 3.1 (maternal survival), 3.2 (perinatal survival) and 3.4 (reduced impact of non-communicable diseases (NCDs)). Medical solutions require greater clarity around the classification of the HDPs, increased frequency of effective antenatal visits, mandatory responses to the HDPs when encountered, prompt provision of life-saving interventions and sustained surveillance for NCD risk for women with a history of the HDPs.