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

Use of the USCOM® noninvasive cardiac output measurement system to predict the development of pre-eclampsia in hypertensive pregnancies

OBJECTIVES

To assess the ability of the USCOM® (USCOM), using measurements of cardiac output (CO) and systemic vascular resistance (SVR), to predict the development of pre-eclampsia (PE) and severe PE in hypertensive pregnancies.

STUDY DESIGN

Prospective cohort study of women in the second or third trimester recruited at a tertiary center in Sydney, Australia. Demographic data and hemodynamic measurements using the USCOM were taken for all study participants at recruitment. Pregnancy outcome, including development of PE and severe PE, was tracked. Data were analyzed using ANOVA testing, pair-wise comparison testing, and Student's t-testing.

RESULTS

Recruitment included 65 normotensive controls, 34 women with chronic hypertension (CH), 51 with gestational hypertension (GH), and 21 with PE. Significantly higher weight, body surface area, and blood pressure measurements were found in the hypertensive, compared with the normotensive control and pregnancies. There were no observed differences in USCOM-measured CO, cardiac index, SVR, or systemic vascular resistance index between hypertensive women who did versus did not develop PE or severe PE in later pregnancy. Analysis of the CH and GH subgroups, as well as only unmedicated hypertensive women (n = 24), also showed no significant difference in hemodynamic parameters between those who did or did not develop PE or severe PE.

CONCLUSIONS

Our group was unable to successfully predict the onset of PE or severe PE based on hemodynamic parameters measured with the USCOM. It is possible this relates to the high proportion of women on antihypertensive medication at recruitment.

Large-Scale Proteomics in Early Pregnancy and Hypertensive Disorders of Pregnancy

Importance

There is no consensus regarding the best method for prediction of hypertensive disorders of pregnancy (HDP), including gestational hypertension and preeclampsia.

Objective

To determine predictive ability in early pregnancy of large-scale proteomics for prediction of HDP.

Design, Setting, and Participants

This was a nested case-control study, conducted in 2022 to 2023, using clinical data and plasma samples collected between 2010 and 2013 during the first trimester, with follow-up until pregnancy outcome. This multicenter observational study took place at 8 academic medical centers in the US. Nulliparous individuals during first-trimester clinical visits were included. Participants with HDP were selected as cases; controls were selected from those who delivered at or after 37 weeks without any HDP, preterm birth, or small-for-gestational-age infant. Age, self-reported race and ethnicity, body mass index, diabetes, health insurance, and fetal sex were available covariates.

Exposures

Proteomics using an aptamer-based assay that included 6481 unique human proteins was performed on stored plasma. Covariates were used in predictive models.

Main Outcomes and Measures

Prediction models were developed using the elastic net, and analyses were performed on a randomly partitioned training dataset comprising 80% of study participants, with the remaining 20% used as an independent testing dataset. Primary measure of predictive performance was area under the receiver operating characteristic curve (AUC).

Results

This study included 753 HDP cases and 1097 controls with a mean (SD) age of 26.9 (5.5) years. Maternal race and ethnicity were 51 Asian (2.8%), 275 non-Hispanic Black (14.9%), 275 Hispanic (14.9%), 1161 non-Hispanic White (62.8% ), and 88 recorded as other (4.8%), which included those who did not identify according to these designations. The elastic net model, allowing for forced inclusion of prespecified covariates, was used to adjust protein-based models for clinical and demographic variables. Under this approach, no proteins were selected to augment the clinical and demographic covariates. The predictive performance of the resulting model was modest, with a training set AUC of 0.64 (95% CI, 0.61-0.67) and a test set AUC of 0.62 (95% CI, 0.56-0.68). Further adjustment for study site yielded only minimal changes in AUCs.

Conclusions and Relevance

In this case-control study with detailed clinical data and stored plasma samples available in the first trimester, an aptamer-based proteomics panel did not meaningfully add to predictive utility over and above clinical and demographic factors that are routinely available.

Development and validation of a prognostic model to predict birth weight: individual participant data meta-analysis

Objective

To predict birth weight at various potential gestational ages of delivery based on data routinely available at the first antenatal visit.

Design

Individual participant data meta-analysis.

Data sources

Individual participant data of four cohorts (237 228 pregnancies) from the International Prediction of Pregnancy Complications (IPPIC) network dataset.

Eligibility criteria for selecting studies

Studies in the IPPIC network were identified by searching major databases for studies reporting risk factors for adverse pregnancy outcomes, such as pre-eclampsia, fetal growth restriction, and stillbirth, from database inception to August 2019. Data of four IPPIC cohorts (237 228 pregnancies) from the US (National Institute of Child Health and Human Development, 2018; 233 483 pregnancies), UK (Allen et al, 2017; 1045 pregnancies), Norway (STORK Groruddalen research programme, 2010; 823 pregnancies), and Australia (Rumbold et al, 2006; 1877 pregnancies) were included in the development of the model.

Results

The IPPIC birth weight model was developed with random intercept regression models with backward elimination for variable selection. Internal-external cross validation was performed to assess the study specific and pooled performance of the model, reported as calibration slope, calibration-in-the-large, and observed versus expected average birth weight ratio. Meta-analysis showed that the apparent performance of the model had good calibration (calibration slope 0.99, 95% confidence interval (CI) 0.88 to 1.10; calibration-in-the-large 44.5 g, -18.4 to 107.3) with an observed versus expected average birth weight ratio of 1.02 (95% CI 0.97 to 1.07). The proportion of variation in birth weight explained by the model (R2) was 46.9% (range 32.7-56.1% in each cohort). On internal-external cross validation, the model showed good calibration and predictive performance when validated in three cohorts with a calibration slope of 0.90 (Allen cohort), 1.04 (STORK Groruddalen cohort), and 1.07 (Rumbold cohort), calibration-in-the-large of -22.3 g (Allen cohort), -33.42 (Rumbold cohort), and 86.4 g (STORK Groruddalen cohort), and observed versus expected ratio of 0.99 (Rumbold cohort), 1.00 (Allen cohort), and 1.03 (STORK Groruddalen cohort); respective pooled estimates were 1.00 (95% CI 0.78 to 1.23; calibration slope), 9.7 g (-154.3 to 173.8; calibration-in-the-large), and 1.00 (0.94 to 1.07; observed v expected ratio). The model predictions were more accurate (smaller mean square error) in the lower end of predicted birth weight, which is important in informing clinical decision making.

Conclusions

The IPPIC birth weight model allowed birth weight predictions for a range of possible gestational ages. The model explained about 50% of individual variation in birth weights, was well calibrated (especially in babies at high risk of fetal growth restriction and its complications), and showed promising performance in four different populations included in the individual participant data meta-analysis. Further research to examine the generalisability of performance in other countries, settings, and subgroups is required.

Trial registration

PROSPERO CRD42019135045.

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.

Identifying Predictor Variables for a Composite Risk Prediction Tool for Gestational Diabetes and Hypertensive Disorders of Pregnancy: A Modified Delphi Study

A composite cardiometabolic risk prediction tool will support the systematic identification of women at increased cardiometabolic risk during pregnancy to enable early screening and intervention. This study aims to identify and select predictor variables for a composite risk prediction tool for cardiometabolic risk (gestational diabetes mellitus and/or hypertensive disorders of pregnancy) for use in the first trimester. A two-round modified online Delphi study was undertaken. A prior systematic literature review generated fifteen potential predictor variables for inclusion in the tool. Multidisciplinary experts (n = 31) rated the clinical importance of variables in an online survey and nominated additional variables for consideration (Round One). An online meeting (n = 14) was held to deliberate the importance, feasibility and acceptability of collecting variables in early pregnancy. Consensus was reached in a second online survey (Round Two). Overall, 24 variables were considered; 9 were eliminated, and 15 were selected for inclusion in the tool. The final 15 predictor variables related to maternal demographics (age, ethnicity/race), pre-pregnancy history (body mass index, height, history of chronic kidney disease/polycystic ovarian syndrome, family history of diabetes, pre-existing diabetes/hypertension), obstetric history (parity, history of macrosomia/pre-eclampsia/gestational diabetes mellitus), biochemical measures (blood glucose levels), hemodynamic measures (systolic blood pressure). Variables will inform the development of a cardiometabolic risk prediction tool in subsequent research. Evidence-based, clinically relevant and routinely collected variables were selected for a composite cardiometabolic risk prediction tool for early pregnancy.

Hypertensive Disorders of Pregnancy and the Cardiovascular System: Causes, Consequences, Therapy, and Prevention

Hypertensive disorders of pregnancy continue to be significant contributors to adverse perinatal outcome and maternal mortality, as well as inducing life-long cardiovascular health impacts that are proportional to the severity and frequency of pregnancy complications. The placenta is the interface between the mother and fetus and its failure to undergo vascular maturation in tandem with maternal cardiovascular adaptation by the end of the first trimester predisposes to hypertensive disorders and fetal growth restriction. While primary failure of trophoblastic invasion with incomplete maternal spiral artery remodeling has been considered central to the pathogenesis of preeclampsia, cardiovascular risk factors associated with abnormal first trimester maternal blood pressure and cardiovascular adaptation produce identical placental pathology leading to hypertensive pregnancy disorders. Outside pregnancy blood pressure treatment thresholds are identified with the goal to prevent immediate risks from severe hypertension >160/100 mm Hg and long-term health impacts that arise from elevated blood pressures as low as 120/80 mm Hg. Until recently, the trend for less aggressive blood pressure management during pregnancy was driven by fear of inducing placental malperfusion without a clear clinical benefit. However, placental perfusion is not dependent on maternal perfusion pressure during the first trimester and risk-appropriate blood pressure normalization may provide the opportunity to protect from the placental maldevelopment that predisposes to hypertensive disorders of pregnancy. Recent randomized trials set the stage for more aggressive risk-appropriate blood pressure management that may offer a greater potential for prevention for hypertensive disorders of pregnancy. KEY POINTS: · Optimal management of maternal blood pressure to prevent preeclampsia and its risks is undefined.. · Early gestational rheological damage to the intervillous space predisposes to preeclampsia and FGR.. · First trimester blood pressure management may need to aim for normotension to prevent preeclampsia..

Fibrinaloid Microclots and Atrial Fibrillation

Atrial fibrillation (AF) is a comorbidity of a variety of other chronic, inflammatory diseases for which fibrinaloid microclots are a known accompaniment (and in some cases, a cause, with a mechanistic basis). Clots are, of course, a well-known consequence of atrial fibrillation. We here ask the question whether the fibrinaloid microclots seen in plasma or serum may in fact also be a cause of (or contributor to) the development of AF. We consider known 'risk factors' for AF, and in particular, exogenous stimuli such as infection and air pollution by particulates, both of which are known to cause AF. The external accompaniments of both bacterial (lipopolysaccharide and lipoteichoic acids) and viral (SARS-CoV-2 spike protein) infections are known to stimulate fibrinaloid microclots when added in vitro, and fibrinaloid microclots, as with other amyloid proteins, can be cytotoxic, both by inducing hypoxia/reperfusion and by other means. Strokes and thromboembolisms are also common consequences of AF. Consequently, taking a systems approach, we review the considerable evidence in detail, which leads us to suggest that it is likely that microclots may well have an aetiological role in the development of AF. This has significant mechanistic and therapeutic implications.

Maternal First-Trimester Alpha-Fetoprotein and Placenta-Mediated Pregnancy Complications

BACKGROUND

Maternal serum markers used for trisomy 21 screening are associated with placenta-mediated complications. Recently, there has been a transition from the traditional first-trimester screening (FTS) that included PAPP-A (pregnancy-associated plasma protein-A) and beta-hCG (human chorionic gonadotropin), to the enhanced FTS test, which added first-trimester AFP (alpha-fetoprotein) and PlGF (placental growth factor). However, whether elevated first-trimester AFP has a similar association with placenta-mediated complications to that observed for elevated second-trimester AFP remains unclear. Our objective was to estimate the association of first-trimester AFP with placenta-mediated complications and compare it with the corresponding associations of second-trimester AFP and other first-trimester serum markers.

METHODS

Retrospective population-based cohort study of women who underwent trisomy 21 screening in Ontario, Canada (2013-2019). The association of first-trimester AFP with placenta-mediated complications was estimated and compared with that of the traditional serum markers. The primary outcome was a composite of stillbirth or preterm placental complications (preeclampsia, birthweight less than third centile, or placental abruption).

RESULTS

A total of 244 990 and 96 167 women underwent FTS and enhanced FTS test screening, respectively. All markers were associated with the primary outcome, but the association for elevated first-trimester AFP (adjusted relative risk [aRR], 1.57 [95% CI, 1.37-1.81]) was weaker than that observed for low PAPP-A (aRR, 2.48 [95% CI, 2.2-2.8]), low PlGF (aRR, 2.28 [95% CI, 1.97-2.64]), and elevated second-trimester AFP (aRR, 1.97 [95% CI, 1.81-2.15]). When the models were adjusted for all 4 enhanced FTS test markers, elevated first-trimester AFP was no longer associated with the primary outcome (aRR, 0.77 [95% CI, 0.58-1.02]).

CONCLUSIONS

Unlike second-trimester AFP, elevated first-trimester AFP is not an independent risk factor for placenta-mediated complications.

First-trimester serum antiphosphatidylserine antibodies serve as candidate biomarkers for predicting pregnancy-induced hypertension

OBJECTIVE

The aim of this study was to explore whether antiphosphatidylserine (aPS) antibodies play roles in the early prediction of pregnancy-induced hypertension (PIH).

METHODS

The serum levels of different isotypes of aPS antibodies were compared in women diagnosed with PIH (PIH group, n  = 30) and 1 : 1 matched normotensive controls (control group, n  = 30). All patients underwent frozen embryo transfer (FET) cycles, and all serum samples were collected during 11-13 weeks of gestation. Receiver operating characteristic (ROC) curves were drawn to analyze the predictive values of aPS antibodies for PIH.

RESULTS

The women who developed PIH after FET had higher serum optical density values (450 nm) of aPS immunoglobulin (Ig) A (1.31 ± 0.43 vs. 1.02 ± 0.51, P  = 0.022), aPS IgM (1.00 ± 0.34 vs. 0.87 ± 0.18, P  = 0.046), and aPS IgG (0.50 ± 0.12 vs. 0.34 ± 0.07, P  < 0.001) compared with the normotensive controls. The serum concentration of total IgG [48.29 ± 10.71 (g/dl) vs. 34.39 ± 11.62 (g/dl), P  < 0.001] was also higher in the PIH group compared with that in the control group. The aPS IgG alone [area under the curve (AUC): 0.913, 95% confidence interval (CI): 0.842-0.985, P  < 0.001] and the combined analysis of aPS IgA, aPS IgM, aPS IgG, and total IgG (AUC: 0.944, 95% CI: 0.888-1.000, P  < 0.001) had high predictive values for PIH.

CONCLUSION

Serum aPS autoantibody levels during the first trimester of pregnancy are positively associated with the development of PIH. Further validation is needed to clearly identify the distinct contributions and underlying mechanisms for diagnostic applications of aPS autoantibodies in PIH prediction.

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.

Impact of replacing or adding pregnancy-associated plasma protein-A at 11-13 weeks on screening for preterm pre-eclampsia

OBJECTIVE

To assess whether pregnancy-associated plasma protein-A (PAPP-A) alters or provides equivalent screening performance as placental growth factor (PlGF) when screening for preterm pre-eclampsia (PE) at 11-13 weeks of gestation.

METHODS

This was a secondary analysis of a non-intervention screening study of 6546 singleton pregnancies that were screened prospectively for preterm PE in the first trimester between December 2016 and June 2018. Patient-specific risks for preterm PE were estimated by maternal history, mean arterial pressure (MAP), uterine artery pulsatility index (UtA-PI), PlGF and PAPP-A. A competing-risks model with biomarkers expressed as multiples of the median was used. All women and clinicians were blinded to the risk for preterm PE. The performance of screening for preterm PE using PlGF vs PAPP-A vs both PAPP-A and PlGF was assessed by comparing areas under the receiver-operating-characteristics (AUC) curves. McNemar's test was used to compare detection rate at a fixed false-positive rate (FPR) of 10%.

RESULTS

PlGF and PAPP-A were measured in 6546 women, of whom 37 developed preterm PE. The AUC and detection rate at 10% FPR using PlGF in combination with maternal history, MAP and UtA-PI were 0.854 and 59.46%, respectively. The respective values were 0.813 and 51.35% when replacing PlGF with PAPP-A and 0.855 and 59.46% when using both PAPP-A and PlGF. Statistically non-significant differences were noted in AUC when replacing PlGF with PAPP-A (ΔAUC, 0.04; P = 0.095) and when using both PAPP-A and PlGF (ΔAUC, 0.002; P = 0.423). However, on an individual case basis, screening using PlGF in conjunction with maternal history, MAP and UtA-PI identified three (8.1%) additional pregnancies that developed preterm PE and that were not identified when replacing PlGF with PAPP-A. Screening using PAPP-A in addition to maternal history and other biomarkers did not identify any additional pregnancies.

CONCLUSION

On an individual case basis, adoption of a screening strategy that uses PAPP-A instead of PlGF results in reduced detection of preterm PE, consistent with previous literature. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Polycyclic aromatic hydrocarbons (PAHs) may explain the paradoxical effects of cigarette use on preeclampsia (PE)

Tobacco smoking and use of snus (smokeless tobacco) are associated with adverse effects on pregnancy and neonatal outcomes. Nicotine is considered a key toxicant involved in effects caused by both smoking and snus, while pyrolysis products including polycyclic aromatic hydrocarbons (PAHs) in cigarette smoke represents the constituents most unequally divided between these two groups of tobacco products. The aim of this review was: i) to compare the impact, in terms of relative effect estimates, of cigarette smoking and use of Swedish snus on pregnancy outcomes using similar non-tobacco user controls, and ii) to examine whether exposure to PAHs from smoking could explain possible differences in impact on pregnancy outcomes. We systematically searched MEDLINE, Embase, PsycInfo, Web of Science and the Cochrane Database of Systematic Reviews up to October 2021 and identified studies reporting risks for adverse pregnancy and neonatal outcomes associated with snus use and with smoking relative to pregnant women with no use of tobacco. Both snus use and smoking were associated with increased risk of stillbirth, preterm birth, and oral cleft malformation, with comparable point estimates. These effects were likely due to comparable nicotine exposure. We also found striking differences. While both smoking and snus increased the risk of having small for gestational age (SGA) infants, risk from maternal smoking was markedly higher as was the reduction in birthweight. In contrast, the risk of preeclampsia (PE) was markedly lower in smokers than in controls, while snus use was associated with a slightly increased risk. We suggest that PAHs acting via AhR may explain the stronger effects of tobacco smoking on SGA and also to the apparent protective effect of cigarette smoking on PE. Possible mechanisms involved include: i) disrupted endocrine control of fetal development as well as placental development and function, and ii) stress adaption and immune suppression in placenta and mother.

Phenotype-Directed Management of Hypertension in Pregnancy

Hypertensive disorders of pregnancy are among the most serious conditions that pregnancy care providers face; however, little attention has been paid to the concept of tailoring clinical care to reduce associated adverse maternal and perinatal outcomes based on the underlying disease pathogenesis. This narrative review discusses the integration of phenotype-based clinical strategies in the management of high-risk pregnant patients that are currently not common clinical practice: real-time placental growth factor testing at Mount Sinai Hospital, Toronto and noninvasive hemodynamic monitoring to guide antihypertensive therapy at the University of Washington Medical Center, Seattle. Future work should focus on promoting more widespread integration of these novel strategies into obstetric care to improve outcomes of pregnancies at high risk of adverse maternal-fetal outcomes from these complications of pregnancy.

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.

Preeclampsia and gestational hypertension are associated to low maternal circulating kisspeptin levels: a systematic review and meta-analysis

BACKGROUND

There are contradictory data concerning kisspeptin in gravids with preeclampsia and gestational hypertension (GH).

OBJECTIVE

To conduct a meta-analysis of studies comparing maternal kisspeptin levels in gravids with and without preeclampsia or GH.

MATERIAL AND METHODS

We searched PubMed, LILACS, and CNKI list of articles up to 20 August 2021, without language limitations, comparing circulating maternal kisspeptin levels, and maternal and neonatal outcomes in gravids with and without preeclampsia or GH. Meta-analyzed results are reported as standardized mean differences (SMD), and their 95% confidence interval (CI).

RESULTS

Seven studies with a low-to-moderate risk of bias were eligible for meta-analysis. Gravids with preeclampsia or GH displayed significantly lower circulating kisspeptin levels (SMD, -0.68, 95% CI, -1.04 to -0.32), lower gestational ages at delivery (SMD, -2.22, 95% CI, -3.25 to -1.18), and birth weight (SMD, -2.16, 95% CI, -3.15 to -1.17), and significantly higher body mass indices (MD, 0.56, 95% CI, 0.24-0.88), systolic (SMD, 2.87, 95% CI, 2.22-3.53), and diastolic blood pressures (SMD, 2.57, 95% CI, 2.19-2.95).

CONCLUSION

Gravids with preeclampsia or GH had lower kisspeptin levels as compared to normotensive controls.

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.

Prediction of Adverse Pregnancy Outcome Related to Placental Dysfunction Using the sFlt-1/PlGF Ratio: A Narrative Review

The sFlt-1 (soluble fms-like tyrosine kinase-1)/PlGF (placental growth factor) ratio is a helpful tool for the prediction and diagnosis of preeclampsia (PE). Current data even show that the ratio has the potential to predict adverse pregnancy outcomes (APO) caused by placental pathologies. The aim of this article is to give a brief overview of recent findings on APO predictions based on the sFlt-1/PlGF ratio. The focus is on obstetric pathologies related to placental dysfunction (PD) such as PE and/or fetal growth restriction (FGR). New uses of the sFlt-1/PlGF ratio as a predictor of APO demonstrate its potential with regard to planning hospitalization and corticosteroid administration and the optimal timing of delivery. However, prospective interventional studies are warranted to define the exact role of the sFlt-1/PlGF ratio as a predictor of adverse pregnancy outcomes caused by placental pathologies.