Blood pressure cut-offs at 11-13 weeks' gestation and risk of preeclampsia.

BACKGROUND: A parallel has been drawn between first trimester placental vascular maturation and maternal cardiovascular adaptations, including blood pressure. Although 140/90 mmHg is well-accepted as the threshold for chronic hypertension in the general obstetric population in early pregnancy, a different threshold could apply to stratify risk of adverse outcomes, such as preeclampsia. This could have implications for interventions, such as the threshold for initiation of antihypertensive therapy and the target blood pressure level. OBJECTIVE: We evaluated the relationship between various blood pressure cut-offs at 11-13 weeks' gestation and development of preeclampsia, overall and according to key maternal characteristics. STUDY DESIGN: This secondary analysis was of data from a prospective non-intervention cohort study of singleton pregnancies delivering at ≥24 weeks, without major anomalies, at two UK maternity hospitals, 2006-2020. BP at 11-13 weeks' gestation was classified according to American College of Cardiology/American Heart Association categories (mmHg), as: 'Normal blood pressure' (systolic <120 and diastolic <80), 'Elevated blood pressure' (systolic ≥120 and diastolic <80), 'Stage 1 hypertension' (systolic ≥130 or diastolic 80-89), and 'Stage 2 hypertension (systolic ≥140 or diastolic ≥90). For blood pressure category thresholds and the outcome of preeclampsia, the following were calculated overall and across maternal age, body mass index, ethnicity, method of conception, and previous pregnancy history: detection rate, screen positive rate, and positive and negative likelihood ratios, with 95% confidence intervals (CIs). A p value <0.05 was considered significant. RESULTS: There were 137,458 pregnancies screened at 11-13 weeks' gestation. The population was ethnically diverse, with 15.9% of Black ethnicity, 6.7% of South or East Asian ethnicity, and 2.7% of mixed ethnicity, with the remainder of White ethnicity. Compared with 'Normal blood pressure', 'Stage 2 hypertension' was associated with both preterm preeclampsia (0.3 to 4.9%) and term PE (1.0 to 8.3%). A blood pressure threshold of 140/90 mmHg was good at identifying women at increased risk of preeclampsia, overall (positive likelihood ratio 5.61, 95% CI 5.14-6.11) and across maternal characteristics, compared with 'Elevated blood pressure' (positive likelihood ratio 1.70, 95% CI 1.63-1.77) and 'Stage 1 hypertension' (positive likelihood ratio 2.68, 95% CI 2.58-2.77). There were two exceptions: a blood pressure threshold of 130/80 mmHg was better for the 2.1% of women with body mass index <18.5kg/m2 (positive likelihood ratio 5.13, 95% CI 3.22-8.16), and a threshold of 135/85 mmHg better for the 50.4% of parous women without a history of preeclampsia (positive likelihood ratio 5.24, 95% CI 4.77-5.77). There was no blood pressure threshold below which reassurance could be provided against development of preeclampsia (all negative likelihood ratios ≥0.20). CONCLUSIONS: The traditional blood pressure threshold of 140/90 mmHg performs well to identify women at increased risk of preeclampsia. Women who are underweight or parous with no prior history of preeclampsia may be better identified by lower thresholds; however a randomised trial would be necessary to determine any benefits of such an approach if antihypertensive therapy were also administered at this threshold. No blood pressure threshold reassured against development of preeclampsia, regardless of maternal characteristics.

Machine learning-enabled maternal risk assessment for women with pre-eclampsia (the PIERS-ML model): a modelling study.

BACKGROUND: Affecting 2-4% of pregnancies, pre-eclampsia is a leading cause of maternal death and morbidity worldwide. Using routinely available data, we aimed to develop and validate a novel machine learning-based and clinical setting-responsive time-of-disease model to rule out and rule in adverse maternal outcomes in women presenting with pre-eclampsia. METHODS: We used health system, demographic, and clinical data from the day of first assessment with pre-eclampsia to predict a Delphi-derived composite outcome of maternal mortality or severe morbidity within 2 days. Machine learning methods, multiple imputation, and ten-fold cross-validation were used to fit models on a development dataset (75% of combined published data of 8843 patients from 11 low-income, middle-income, and high-income countries). Validation was undertaken on the unseen 25%, and an additional external validation was performed in 2901 inpatient women admitted with pre-eclampsia to two hospitals in south-east England. Predictive risk accuracy was determined by area-under-the-receiver-operator characteristic (AUROC), and risk categories were data-driven and defined by negative (-LR) and positive (+LR) likelihood ratios. FINDINGS: Of 8843 participants, 590 (6·7%) developed the composite adverse maternal outcome within 2 days, 813 (9·2%) within 7 days, and 1083 (12·2%) at any time. An 18-variable random forest-based prediction model, PIERS-ML, was accurate (AUROC 0·80 [95% CI 0·76-0·84] vs the currently used logistic regression model, fullPIERS: AUROC 0·68 [0·63-0·74]) and categorised women into very low risk (-LR <0·1; eight [0·7%] of 1103 women), low risk (-LR 0·1 to 0·2; 321 [29·1%] women), moderate risk (-LR >0·2 and +LR <5·0; 676 [61·3%] women), high risk (+LR 5·0 to 10·0, 87 [7·9%] women), and very high risk (+LR >10·0; 11 [1·0%] women). Adverse maternal event rates were 0% for very low risk, 2% for low risk, 5% for moderate risk, 26% for high risk, and 91% for very high risk within 48 h. The 2901 women in the external validation dataset were accurately classified as being at very low risk (0% with outcomes), low risk (1%), moderate risk (4%), high risk (33%), or very high risk (67%). INTERPRETATION: The PIERS-ML model improves identification of women with pre-eclampsia who are at lowest and greatest risk of severe adverse maternal outcomes within 2 days of assessment, and can support provision of accurate guidance to women, their families, and their maternity care providers. FUNDING: University of Strathclyde Diversity in Data Linkage Centre for Doctoral Training, the Fetal Medicine Foundation, The Canadian Institutes of Health Research, and the Bill & Melinda Gates Foundation.

First trimester risk of preeclampsia and rate of spontaneous birth in patients without preeclampsia.

BACKGROUND: First-trimester screening for preeclampsia using a combination of maternal risk factors and mean arterial pressure, uterine artery pulsatility index, and placental growth factor, as proposed by the Fetal Medicine Foundation, provides effective prediction of preterm preeclampsia. Placental dysfunction is a potential precursor of spontaneous birth. OBJECTIVE: The objective of this study was to examine if the estimated risk of preeclampsia is associated with the gestational age at onset of spontaneous delivery in the absence of preeclampsia. STUDY DESIGN: This was a secondary analysis of the data from the Screening programme for pre-eclampsia trial in which there was a comparison of the performance of first-trimester screening for preterm preeclampsia using the Fetal Medicine Foundation model vs a traditional history-based risk scoring system. A subgroup of women from the trial with spontaneous onset of delivery (labor with intact membranes or preterm prelabor rupture of membranes) was included in this study and was arbitrarily divided into 3 groups according to the risk for preterm preeclampsia as determined by the Fetal Medicine Foundation model at 11 to 13 weeks' gestation as follows: group 1 low risk (˂1/100); group 2 intermediate risk (1/50 to 1/100); and group 3 high risk (˃1/50). A survival analysis was carried out using a Kaplan-Meier estimator and a Cox regression analysis with stratification by the 3 preeclampsia risk groups. Occurrence of spontaneous birth in the study groups was compared using log-rank tests and hazard ratios. RESULTS: The study population comprised 10,820 cases with delivery after spontaneous onset of labor among the 16,451 cases who participated in the Screening programme for pre-eclampsia trial. There were 9795 cases in group 1, 583 in group 2, and 442 in group 3. The gestational age at delivery was <28, <32, <35, <37, and <40 weeks in 0.29%, 0.64%, 1.68%, 4.52%, and 44.97% of cases, respectively, in group 1; 0.69%, 1.71%, 3.26%, 7.72%, and 55.23% of cases, respectively, in group 2; and 0.45%, 1.81%, 5.66%, 13.80%, and 63.12% of cases, respectively, in group 3. The curve profile of gestational age at spontaneous birth in the 3 study groups was significantly different overall and in pairwise comparisons (P values <.001). The Cox regression analysis showed that risks increased for spontaneous birth by 18% when the intermediate-risk group was compared with the low-risk group (P˂.001) and by 41% when the high-risk group was compared with the low-risk group (P˂.001). CONCLUSION: In this study that investigated birth after spontaneous onset of labor in women without preeclampsia, there were 2 major findings. First, the duration of pregnancy decreased with increasing first-trimester risk for preeclampsia. Second, in the high-risk group, when compared with the low-risk group, the risk for spontaneous birth was 4 times higher at a gestational age of 24 to 26 weeks, 3 times higher at 28 to 32 weeks, and 2 times higher at 34 to 39 weeks. These differences present major clinical implications for antepartum counselling, monitoring, and interventions in these pregnancies.

Pregnancy-An Ideal Period to Identify Women at Risk for Chronic Hypertension.

BACKGROUND: Cardiovascular disease is the leading cause of mortality in women. Pregnancy is an ideal period to implement cardiovascular prevention strategies as women seek medical help. We aimed to develop a predictive model to identify women at increased risk for chronic hypertension (CH) based on information collected in the index pregnancy. METHODS: Cohort of 26 511 women seen in 2 consecutive pregnancies. Included were women without CH, with information on maternal characteristics and blood pressure at 11 to 13 weeks' gestation, and the development of preeclampsia or gestational hypertension (GH) in the index pregnancy. Logistic regression models were fitted for the prediction of the development of future CH by the 20th week of the subsequent pregnancy. The performance of screening and risk calibration of the model were assessed. RESULTS: In this study 1560 (5.9%) women developed preeclampsia or GH (index pregnancy), and 215 (0.8%) developed future CH, with a median of 3.0 years later. Predictors of development of future CH were maternal age, weight, and blood pressure; Black and South Asian ethnicity; family history of preeclampsia; parity; and development of preeclampsia or GH. Preeclampsia or GH detected 52.1% (45.2%-58.9%) of future CH. At a screen-positive rate of 10%, a model including maternal characteristics, early pregnancy blood pressure, and development of preeclampsia or GH detected 73.5% (67.1-79.3) of future CH. CONCLUSIONS: Early pregnancy maternal characteristics, blood pressure, and development of preeclampsia or GH identify three-fourths of women at risk for future CH. Our results offer an important preventative strategy for identifying women at increased risk of future CH, which is applicable worldwide.

First-trimester prediction of preterm pre-eclampsia and prophylaxis by aspirin: Effect on spontaneous and iatrogenic preterm birth.

OBJECTIVE: To report the predictive performance for preterm birth (PTB) of the Fetal Medicine Foundation (FMF) triple test and National Institute for health and Care Excellence (NICE) guidelines used to screen for pre-eclampsia and examine the impact of aspirin in the prevention of PTB. DESIGN: Secondary analysis of data from the SPREE study and the ASPRE trial. SETTING: Multicentre studies. POPULATION: In SPREE, women with singleton pregnancies had screening for preterm pre-eclampsia at 11-13 weeks of gestation by the FMF method and NICE guidelines. There were 16 451 pregnancies that resulted in delivery at ≥24 weeks of gestation and these data were used to derive the predictive performance for PTB of the two methods of screening. The results from the ASPRE trial were used to examine the effect of aspirin in the prevention of PTB in the population from SPREE. METHODS: Comparison of performance of FMF method and NICE guidelines for pre-eclampsia in the prediction of PTB and use of aspirin in prevention of PTB. MAIN OUTCOME MEASURE: Spontaneous PTB (sPTB), iatrogenic PTB for pre-eclampsia (iPTB-PE) and iatrogenic PTB for reasons other than pre-eclampsia (iPTB-noPE). RESULTS: Estimated incidence rates of sPTB, iPTB-PE and iPTB-noPE were 3.4%, 0.8% and 1.6%, respectively. The corresponding detection rates were 17%, 82% and 25% for the triple test and 12%, 39% and 19% for NICE guidelines, using the same overall screen positive rate of 10.2%. The estimated proportions prevented by aspirin were 14%, 65% and 0%, respectively. CONCLUSION: Prediction of sPTB and iPTB-noPE by the triple test was poor and poorer by the NICE guidelines. Neither sPTB nor iPTB-noPE was reduced substantially by aspirin.

Placental growth factor testing at 19-23 weeks of gestation as a guide to subsequent care in pregnancy: A prospective observational study.

OBJECTIVE: To determine whether serum placental growth factor (PlGF) at 19-23 weeks of gestation can improve the identification of risk for adverse outcomes. DESIGN: Prospective observational cohort study. SETTING: Two English maternity units. POPULATION: Unselected singleton pregnancies attending routine ultrasound at 19-23 weeks of gestation. METHODS: Outcomes ascertained by health record review. Diagnostic test properties evaluated clinical risk factors for pre-eclampsia (according to National Institute of Care Excellence) or fetal growth restriction (according to Royal College of Obstetricians and Gynaecologists), low PlGF at 19-23 weeks of gestation (<5th percentile) or both. MAIN OUTCOME MEASURES: Pre-eclampsia, gestational hypertension, stillbirth, birthweight below third percentile or neonatal intensive care unit (NICU) admission for ≥48 h. RESULTS: In 30 013 pregnancies, risk factors were present in 9941 (33.1%), low PlGF was present in 1501 (5.0%) and both ('two-stage' screening) were present in 547 (1.8%) pregnancies. Risk factors detected 41.7%-54.7% of adverse outcomes, and could not meaningfully revise the risk (all positive likelihood ratios, +LR, <5.0; all negative likelihood ratios, -LR, ≥0.2). Low PlGF detected 8.5%-17.4% of adverse outcomes, but meaningfully increased risks (other than NICU admission) associated with delivery <37 weeks of gestation (+LR = 5.03-15.55); all -LRs were ≥0.2. 'Two-stage' screening detected 4.2%-8.9% of adverse outcomes, with meaningful +LRs (6.28-18.61) at <37 weeks of gestation, except for NICU admission of ≥48 h, which had an +LR of 7.56 at <34 weeks of gestation; all -LRs were ≥0.2. No screening strategy meaningfully increased or decreased the detection of adverse outcome risk at term. CONCLUSIONS: Clinical risk factor screening has a high screen-positive rate and a poor detection of adverse outcomes. False positives cannot be reduced by PlGF testing at 19-23 weeks of gestation; therefore, this cannot be recommended as a useful strategy on its own.

Relation of antepartum stillbirth to birthweight and gestational age: Prospective cohort study.

OBJECTIVES: To investigate the incidence of antepartum stillbirth in relation to the distribution of neonatal/fetal weight for different gestational ages. DESIGN: Prospective observational cohort study. SETTING: Obstetric ultrasound departments in two UK maternity hospitals. POPULATION: 168 966 women with singleton pregnancies attending for routine antenatal care. METHODS: We examined the incidence of antepartum stillbirths, within different birthweight and fetal weight percentile subgroups, conditioning for gestational age. MAIN OUTCOME MEASURES: Incidence of antepartum stillbirth. RESULTS: The risk of stillbirth progressively increased for lower birthweight. Considering the 25-75th percentile as the reference category, the relative risks for stillbirth at <37 weeks' gestation were 7.6 (95% confidence interval [CI] 5.7-10.2) <1st percentile, 2.6 (95% CI 1.8-3.7) 1 to 10th percentile, 1.4 (95% CI 0.9-2.1) 10 to 25th percentile, 0.8 (95% CI 0.4-1.5) 75 to 90th percentile, 0.8 (95% CI 0.4-1.7) 90 to 99th percentile, 0.9 (95% CI 0.3-2.5) >99th percentile. The respective values for births at ≥37 weeks' gestation were 5.0 (95% CI 2.9-8.9), 2.1 (95% CI 1.4-3.3), 1.4 (95% CI 0.9-2.1), 1.2 (95% CI 0.7-1.8), 1.0 (95% CI 0.6-1.8) and 4.0 (95% CI 1.8-9.3). The incidence of stillbirth in ongoing low-risk singleton pregnancies gradually increases for smaller fetuses at any gestational point. The higher incidence (5.56%) was evident for fetal weight <1st percentile between 24 and 28 weeks' gestation. CONCLUSION: Fetal weight and the weight of the stillborn have a continuous association with the incidence of antepartum stillbirth which is affected by gestational age.

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

BACKGROUND: The exact mechanism by which aspirin prevents preeclampsia remains unclear. Its effects on serum placental biomarkers throughout pregnancy are also unknown. OBJECTIVE: To investigate the effects of aspirin on serum pregnancy-associated plasma protein A and placental growth factor trajectories using repeated measures from women at increased risk of preterm preeclampsia. STUDY DESIGN: This was a longitudinal secondary analysis of the Combined Multimarker Screening and Randomized Patient Treatment with Aspirin for Evidence-based Preeclampsia Prevention trial using repeated measures of pregnancy-associated plasma protein A and placental growth factor. In the trial, 1620 women at increased risk of preterm preeclampsia were identified using the Fetal Medicine Foundation algorithm at 11 to 13+6 weeks of gestation, of whom 798 were randomly assigned to receive aspirin 150 mg and 822 to receive placebo daily from before 14 weeks to 36 weeks of gestation. Serum biomarkers were measured at baseline and follow-up visits at 19 to 24, 32 to 34, and 36 weeks of gestation. Generalized additive mixed models with treatment by gestational age interaction terms were used to investigate the effect of aspirin on biomarker trajectories over time. RESULTS: Overall, there were 5507 pregnancy-associated plasma protein A and 5523 placental growth factor measurements. Raw pregnancy-associated plasma protein A values increased over time, and raw placental growth factor increased until 32 weeks of gestation followed by a decline. The multiple of the median mean values of the same biomarkers were consistently below 1.0 multiple of the median, reflecting the high-risk profile of the study population. Trajectories of mean pregnancy-associated plasma protein A and placental growth factor multiple of the median values did not differ significantly between the aspirin and placebo groups (aspirin treatment by gestational age interaction P values: .259 and .335, respectively). CONCLUSION: In women at increased risk of preterm preeclampsia, aspirin 150 mg daily had no significant effects on pregnancy-associated plasma protein A or placental growth factor trajectories when compared to placebo.

Preterm preeclampsia screening using biomarkers: combining phenotypic classifiers into robust prediction models.

BACKGROUND: Preeclampsia screening is a critical component of antenatal care worldwide. Currently, the most developed screening test for preeclampsia at 11 to 13 weeks' gestation integrates maternal demographic characteristics and medical history with 3 biomarkers-serum placental growth factor, mean arterial pressure, and uterine artery pulsatility index-to identify approximately 75% of women who develop preterm preeclampsia with delivery before 37 weeks of gestation. It is generally accepted that further improvements to preeclampsia screening require the use of additional biomarkers. We recently reported that the levels of specific metabolites and metabolite ratios are associated with preterm preeclampsia. Notably, for several of these markers, preterm preeclampsia prediction varied according to maternal body mass index class. These findings motivated us to study whether patient classification allowed for combining metabolites with the current biomarkers more effectively to improve prediction of preterm preeclampsia. OBJECTIVE: This study aimed to investigate whether metabolite biomarkers can improve biomarker-based preterm preeclampsia prediction in 3 screening resource scenarios according to the availability of: (1) placental growth factor, (2) placental growth factor+mean arterial pressure, and (3) placental growth factor+mean arterial pressure+uterine artery pulsatility index. STUDY DESIGN: This was an observational case-control study, drawn from a large prospective screening study at 11 to 13 weeks' gestation on the prediction of pregnancy complications, conducted at King's College Hospital, London, United Kingdom. Maternal blood samples were also collected for subsequent research studies. We used liquid chromatography-mass spectrometry to quantify levels of 50 metabolites previously associated with pregnancy complications in plasma samples from singleton pregnancies. Biomarker data, normalized using multiples of medians, on 1635 control and 106 preterm preeclampsia pregnancies were available for model development. Modeling was performed using a methodology that generated a prediction model for preterm preeclampsia in 4 consecutive steps: (1) z-normalization of predictors, (2) combinatorial modeling of so-called (weak) classifiers in the unstratified patient set and in discrete patient strata based on body mass index and/or race, (3) selection of classifiers, and (4) aggregation of the selected classifiers (ie, bagging) into the final prediction model. The prediction performance of models was evaluated using the area under the receiver operating characteristic curve, and detection rate at 10% false-positive rate. RESULTS: First, the predictor development methodology itself was evaluated. The patient set was split into a training set (2/3) and a test set (1/3) for predictor model development and internal validation. A prediction model was developed for each of the 3 different predictor panels, that is, placental growth factor+metabolites, placental growth factor+mean arterial pressure+metabolites, and placental growth factor+mean arterial pressure+uterine artery pulsatility index+metabolites. For all 3 models, the area under the receiver operating characteristic curve in the test set did not differ significantly from that of the training set. Next, a prediction model was developed using the complete data set for the 3 predictor panels. Among the 50 metabolites available for modeling, 26 were selected across the 3 prediction models; 21 contributed to at least 2 out of the 3 prediction models developed. Each time, area under the receiver operating characteristic curve and detection rate were significantly higher with the new prediction model than with the reference model. Markedly, the estimated detection rate with the placental growth factor+mean arterial pressure+metabolites prediction model in all patients was 0.58 (95% confidence interval, 0.49-0.70), a 15% increase (P<.001) over the detection rate of 0.43 (95% confidence interval, 0.33-0.55) estimated for the reference placental growth factor+mean arterial pressure. The same prediction model significantly improved detection in Black (14%) and White (19%) patients, and in the normal-weight group (18.5≤body mass index<25) and the obese group (body mass index≥30), with respectively 19% and 20% more cases detected, but not in the overweight group, when compared with the reference model. Similar improvement patterns in detection rates were found in the other 2 scenarios, but with smaller improvement amplitudes. CONCLUSION: Metabolite biomarkers can be combined with the established biomarkers of placental growth factor, mean arterial pressure, and uterine artery pulsatility index to improve the biomarker component of early-pregnancy preterm preeclampsia prediction tests. Classification of the pregnant women according to the maternal characteristics of body mass index and/or race proved instrumental in achieving improved prediction. This suggests that maternal phenotyping can have a role in improving the prediction of obstetrical syndromes such as preeclampsia.

Maternal Plasma RNA in First Trimester Nullipara for the Prediction of Spontaneous Preterm Birth ≤ 32 Weeks: Validation Study.

The first-trimester prediction of spontaneous preterm birth (sPTB) has been elusive, and current screening is heavily dependent on obstetric history. However, nullipara lack a relevant history and are at higher risk for spontaneous (s)PTB ≤ 32 weeks compared to multipara. No available objective first-trimester screening test has proven a fair predictor of sPTB ≤ 32 weeks. We questioned whether a panel of maternal plasma cell-free (PCF) RNAs (PSME2, NAMPT, APOA1, APOA4, and Hsa-Let-7g) previously validated at 16-20 weeks for the prediction of sPTB ≤ 32 weeks might be useful in first-trimester nullipara. Sixty (60) nulliparous women (40 with sPTB ≤ 32 weeks) who were free of comorbidities were randomly selected from the King's College Fetal Medicine Research Institute biobank. Total PCF RNA was extracted and the expression of panel RNAs was quantitated by qRT-PCR. The analysis employed, primarily, multiple regression with the main outcome being the prediction of subsequent sPTB ≤ 32 weeks. The test performance was judged by the area under the curve (AUC) using a single threshold cut point with observed detection rates (DRs) at three fixed false positive rates (FPR). The mean gestation was 12.9 ± 0.5 weeks (range 12.0-14.1 weeks). Two RNAs were differentially expressed in women destined for sPTB ≤ 32 weeks: APOA1 (p < 0.001) and PSME2 (p = 0.05). APOA1 testing at 11-14 weeks predicted sPTB ≤ 32 weeks with fair to good accuracy. The best predictive model generated an AUC of 0.79 (95% CI 0.66-0.91) with observed DRs of 41%, 61%, and 79% for FPRs of 10%, 20%, and 30%, including crown-rump length, maternal weight, race, tobacco use, and age.

Vaginal progesterone for preventing preterm birth and adverse perinatal outcomes in twin gestations: a systematic review and meta-analysis.

OBJECTIVE: To evaluate the efficacy of vaginal progesterone for the prevention of preterm birth and adverse perinatal outcomes in twin gestations. DATA SOURCES: MEDLINE, Embase, LILACS, and CINAHL (from their inception to January 31, 2023), Cochrane databases, Google Scholar, bibliographies, and conference proceedings. STUDY ELIGIBILITY CRITERIA: Randomized controlled trials that compared vaginal progesterone to placebo or no treatment in asymptomatic women with a twin gestation. METHODS: The systematic review was conducted according to the Cochrane Handbook for Systematic Reviews of Interventions. The primary outcome was preterm birth <34 weeks of gestation. Secondary outcomes included adverse perinatal outcomes. Pooled relative risks with 95% confidence intervals were calculated. We assessed the risk of bias in each included study, heterogeneity, publication bias, and quality of evidence, and performed subgroup and sensitivity analyses. RESULTS: Eleven studies (3401 women and 6802 fetuses/infants) fulfilled the inclusion criteria. Among all twin gestations, there were no significant differences between the vaginal progesterone and placebo or no treatment groups in the risk of preterm birth <34 weeks (relative risk, 0.99; 95% confidence interval, 0.84-1.17; high-quality evidence), <37 weeks (relative risk, 0.99; 95% confidence interval, 0.92-1.06; high-quality evidence), and <28 weeks (relative risk, 1.00; 95% confidence interval, 0.64-1.55; moderate-quality evidence), and spontaneous preterm birth <34 weeks of gestation (relative risk, 0.97; 95% confidence interval, 0.80-1.18; high-quality evidence). Vaginal progesterone had no significant effect on any of the perinatal outcomes evaluated. Subgroup analyses showed that there was no evidence of a different effect of vaginal progesterone on preterm birth <34 weeks of gestation related to chorionicity, type of conception, history of spontaneous preterm birth, daily dose of vaginal progesterone, and gestational age at initiation of treatment. The frequencies of preterm birth <37, <34, <32, <30, and <28 weeks of gestation and adverse perinatal outcomes did not significantly differ between the vaginal progesterone and placebo or no treatment groups in unselected twin gestations (8 studies; 3274 women and 6548 fetuses/infants). Among twin gestations with a transvaginal sonographic cervical length <30 mm (6 studies; 306 women and 612 fetuses/infants), vaginal progesterone was associated with a significant decrease in the risk of preterm birth occurring at <28 to <32 gestational weeks (relative risks, 0.48-0.65; moderate- to high-quality evidence), neonatal death (relative risk, 0.32; 95% confidence interval, 0.11-0.92; moderate-quality evidence), and birthweight <1500 g (relative risk, 0.60; 95% confidence interval, 0.39-0.88; high-quality evidence). Vaginal progesterone significantly reduced the risk of preterm birth occurring at <28 to <34 gestational weeks (relative risks, 0.41-0.68), composite neonatal morbidity and mortality (relative risk, 0.59; 95% confidence interval, 0.33-0.98), and birthweight <1500 g (relative risk, 0.55; 95% confidence interval, 0.33-0.94) in twin gestations with a transvaginal sonographic cervical length ≤25 mm (6 studies; 95 women and 190 fetuses/infants). The quality of evidence was moderate for all these outcomes. CONCLUSION: Vaginal progesterone does not prevent preterm birth, nor does it improve perinatal outcomes in unselected twin gestations, but it appears to reduce the risk of preterm birth occurring at early gestational ages and of neonatal morbidity and mortality in twin gestations with a sonographic short cervix. However, more evidence is needed before recommending this intervention to this subset of patients.

Preeclampsia Prevention by Timed Birth at Term.

BACKGROUND: Most preeclampsia occurs at term. There are no effective preventative strategies. We aimed to identify the optimal preeclampsia screening and timing of birth strategy for prevention of term preeclampsia. METHODS: This secondary analysis was of data from a prospective nonintervention cohort study of singleton pregnancies delivering at ≥24 weeks, without major anomalies, at 2 United Kingdom maternity hospitals. At routine visits at 11 to 13 weeks' (57 131 pregnancies screened, 1138 term preeclampsia developed) or 35 to 36 weeks' gestation (29 035 pregnancies screened, 619 term preeclampsia), with patient-specific preeclampsia risks determined by: United Kingdom National Institute for Health and Care Excellence guidance, and the Fetal Medicine Foundation competing-risks model. For each screening strategy, timing of birth for term preeclampsia prevention was evaluated at gestational time points that were fixed (37, 38, 39, 40 weeks) or dependent on preeclampsia risk by the competing-risks model at 35 to 36 weeks. Main outcomes were proportion of term preeclampsia prevented, and number-needed-to-deliver to prevent one term preeclampsia case. RESULTS: The proportion of term preeclampsia prevented was the highest, and number-needed-to-deliver lowest, for preeclampsia screening at 35 to 36 (rather than 11-13) weeks. For delivery at 37 weeks, fewer cases of preeclampsia were prevented for National Institute for Health and Care Excellence (28.8%) than the competing-risks model (59.8%), and the number-needed-to-deliver was higher (16.4 versus 6.9, respectively). The risk-stratified approach (at 35-36 weeks) had similar preeclampsia prevention (by 57.2%) and number-needed-to-deliver (8.4), but fewer women would be induced at 37 weeks (1.2% versus 8.8%). CONCLUSIONS: Risk-stratified timing of birth at term may more than halve the risk of term preeclampsia.

Personalized stratification of pregnancy care for small for gestational age neonates from biophysical markers at midgestation.

BACKGROUND: Antenatal identification of pregnancies at high risk of delivering small for gestational age neonates may improve the management of the condition and reduce the associated adverse perinatal outcomes. In a series of publications, we have developed a new competing-risks model for small for gestational age prediction, and we demonstrated that the new approach has a superior performance to that of the traditional methods. The next step in shaping the appropriate management of small for gestational age is the timely assessment of these high-risk pregnancies according to an antenatal stratification plan. OBJECTIVE: This study aimed to demonstrate the stratification of pregnancy care based on individual patient risk derived from the application of the competing-risks model for small for gestational age that combines maternal factors with sonographic estimated fetal weight and uterine artery pulsatility index at midgestation. STUDY DESIGN: This was a prospective observational study of 96,678 singleton pregnancies undergoing routine ultrasound examination at 19 to 24 weeks of gestation, which included recording of estimated fetal weight and measurement of uterine artery pulsatility index. The competing-risks model for small for gestational age was used to create a patient-specific stratification curve capable to define a specific timing for a repeated ultrasound examination after 24 weeks. We examined different stratification plans with the intention of detecting approximately 80%, 85%, 90%, and 95% of small for gestational age neonates with birthweight <3rd and <10th percentiles at any gestational age at delivery until 36 weeks; all pregnancies would be offered a routine ultrasound examination at 36 weeks. RESULTS: The stratification of pregnancy care for small for gestational age can be based on a patient-specific stratification curve. Factors from maternal history, low estimated fetal weight, and increased uterine artery pulsatility index shift the personalized risk curve toward higher risks. The degree of shifting defines the timing for assessment for each pregnancy. If the objective of our antenatal plan was to detect 80%, 85%, 90%, and 95% of small for gestational age neonates at any gestational age at delivery until 36 weeks, the median (range) proportions (percentages) of population examined per week would be 3.15 (1.9-3.7), 3.85 (2.7-4.5), 4.75 (4.0-5.4), and 6.45 (3.7-8.0) for small for gestational age <3rd percentile and 3.8 (2.5-4.6), 4.6 (3.6-5.4), 5.7 (3.8-6.4), and 7.35 (3.3-9.8) for small for gestational age <10th percentile, respectively. CONCLUSION: The competing-risks model provides an effective personalized continuous stratification of pregnancy care for small for gestational age which is based on individual characteristics and biophysical marker levels recorded at the midgestation scan.

First-trimester preterm preeclampsia prediction with metabolite biomarkers: differential prediction according to maternal body mass index.

BACKGROUND: Prediction of preeclampsia risk is key to informing effective maternal care. Current screening for preeclampsia at 11 to 13 weeks of gestation using maternal demographic characteristics and medical history with measurements of mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor can identify approximately 75% of women who develop preterm preeclampsia with delivery at <37 weeks of gestation. Further improvements to preeclampsia screening tests will likely require integrating additional biomarkers. Recent research suggests the existence of distinct maternal risk profiles. Therefore, biomarker evaluation should account for the possibility that a biomarker only predicts preeclampsia in a specific maternal phenotype. OBJECTIVE: This study aimed to verify metabolite biomarkers as preterm preeclampsia predictors early in pregnancy in all women and across body mass index groups. STUDY DESIGN: Observational case-control study drawn from a large prospective study on the early prediction of pregnancy complications in women attending their routine first hospital visit at King's College Hospital, London, United Kingdom, in 2010 to 2015. Pregnant women underwent a complete first-trimester assessment, including the collection of blood samples for biobanking. In 11- to 13-week plasma samples of 2501 singleton pregnancies, the levels of preselected metabolites implicated in the prediction of pregnancy complications were analyzed using a targeted liquid chromatography-mass spectrometry method, yielding high-quality quantification data on 50 metabolites. The ratios of amino acid levels involved in arginine biosynthesis and nitric oxide synthase pathways were added to the list of biomarkers. Placental growth factor and pregnancy-associated plasma protein A were also available for all study subjects, serving as comparator risk predictors. Data on 1635 control and 106 pregnancies complicated by preterm preeclampsia were considered for this analysis, normalized using multiples of medians. Prediction analyses were performed across the following patient strata: all subjects and the body mass index classes of <25, 25 to <30, and ≥30 kg/m2. Adjusted median levels were compared between cases and controls and between each body mass index class group. Odds ratios and 95% confidence intervals were calculated at the mean ±1 standard deviation to gauge clinical prediction merits. RESULTS: The levels of 13 metabolites were associated with preterm preeclampsia in the entire study population (P<.05) with particularly significant (P<.01) associations found for 6 of them, namely, 2-hydroxy-(2/3)-methylbutyric acid, 25-hydroxyvitamin D3, 2-hydroxybutyric acid, alanine, dodecanoylcarnitine, and 1-(1Z-octadecenyl)-2-oleoyl-sn-glycero-3-phosphocholine. Fold changes in 7 amino acid ratios, all involving glutamine or ornithine, were also significantly different between cases and controls (P<.01). The predictive performance of some metabolites and ratios differed according to body mass index classification; for example, ornithine (P<.001) and several ornithine-related ratios (P<.0001 to P<.01) were only strongly associated with preterm preeclampsia in the body mass index of <25 kg/m2 group, whereas dodecanoylcarnitine and 3 glutamine ratios were particularly predictive in the body mass index of ≥30 kg/m2 group (P<.01). CONCLUSION: Single metabolites and ratios of amino acids related to arginine bioavailability and nitric oxide synthase pathways were associated with preterm preeclampsia risk at 11 to 13 weeks of gestation. Differential prediction was observed according to body mass index classes, supporting the existence of distinct maternal risk profiles. Future studies in preeclampsia prediction should account for the possibility of different maternal risk profiles to improve etiologic and prognostic understanding and, ultimately, clinical utility of screening tests.

Preterm and term pre-eclampsia: Relative burdens of maternal and perinatal complications.

OBJECTIVE: To determine the relative burdens of maternal and perinatal complications for preterm and term pre-eclampsia. DESIGN: Prospective observational cohort study. SETTING: Two English maternity units. POPULATION: Unselected women with singleton pregnancies who developed pre-eclampsia (International Society for the Study of Hypertension in Pregnancy definition). METHODS: Outcomes were ascertained by health record review and compared between pregnancies with preterm (versus term) pre-eclampsia. MAIN OUTCOME MEASURES: Severe maternal hypertension, maternal mortality or major maternal morbidity, perinatal mortality or major neonatal morbidity, neonatal unit (NNU) admission ≥48 hours, and birthweight <3rd percentile. RESULTS: Among 40 241 singleton pregnancies, 298 (0.7%, 95% confidence interval [CI] 0.66-0.83) and 1194 (3.0%, 95% CI 2.8-3.1) developed preterm and term pre-eclampsia, respectively. Women with preterm (versus term) pre-eclampsia more commonly experienced adverse maternal or perinatal events: severe hypertension 18.5% (95% CI 14.5-23.3) versus 13.6% (95% CI 11.7-15.6); maternal mortality/major morbidity 7.4% (95% CI 4.9-10.9) versus 2.2% (95% CI 1.5-3.2); perinatal mortality/major neonatal morbidity 29.5% (95% CI 24.6-34.9) versus 2.2% (95% CI 1.5-3.2); and birthweight <3rd percentile 54.4% (95% CI 48.7-59.9) versus 14.2% (95% CI 12.4-16.3). However, in absolute terms, most maternal complications occurred in women with term pre-eclampsia, as did a large proportion of perinatal complications: severe hypertension 74.7% (95% CI 68.5-80.0); maternal mortality/major morbidity 54.2% (95% CI 40.3-67.4); perinatal mortality/major neonatal morbidity 22.8% (95% CI 16.1-31.3); NNU admission ≥48 hours 38.1% (95% CI 32.4-44.1); and birthweight <3rd percentile 51.2% (95% CI 45.8-56.5). CONCLUSIONS: Although adverse event risks are greater with preterm (versus term) pre-eclampsia, term disease is associated with at least equivalent total numbers of maternal, and a significant proportion of perinatal, adverse events. Increased efforts should be made to decrease the incidence of term pre-eclampsia.

Maternal plasma diacylglycerols and triacylglycerols in the prediction of gestational diabetes mellitus.

OBJECTIVE: To define the lipidomic profile in plasma across pregnancy, and identify lipid biomarkers for gestational diabetes mellitus (GDM) prediction in early pregnancy. DESIGN: Case-control study. SETTING: Tertiary referral maternity unit. POPULATION OR SAMPLE: Plasma samples from 100 GDM and 100 normal glucose tolerance (NGT) women, divided into a training set (GDM first trimester = 50, GDM second trimester = 40, NGT first trimester = 50, NGT second trimester = 50) and a validation set (GDM first trimester = 45, GDM second trimester = 34, NGT first trimester = 44, NGT second trimester = 40). METHODS: Plasma samples were collected in the first (11+0 to 13+6 weeks), second (19+0 to 24+6 weeks), and third trimesters (30+0 to 34+6 weeks), and tested by ultra-high-performance liquid chromatography coupled with electrospray ionisation-quadrupole-time of flight-mass spectrometry; The GDM prediction model was established by the machine-learning method of random forest. MAIN OUTCOME MEASURES: Gestational diabetes mellitus. RESULTS: In both the GDM and NGT group, lyso-glycerophospholipids were down-regulated, whereas ceramides, sphingomyelins, cholesteryl ester, diacylglycerols (DGs) and triacylglycerols (TGs) and glucosylceramide were up-regulated across the three trimesters of pregnancy. In the training dataset, seven TGs and five DGs demonstrated good performance in the prediction of GDM in the first and second trimesters (area under the curve [AUC] = 0.96 with 95% confidence interval [CI] of 0.93-1 and AUC = 0.97 with 95% CI of 0.95-1, respectively), independent of maternal body mass index (BMI) and ethnicity. In the validation dataset, the predictive model achieved an AUC of 0.88 and 0.94 at the first and second trimesters, respectively. CONCLUSIONS: Our results have proposed new lipid biomarkers for the first trimester prediction of GDM, independent of ethnicity and BMI.

The implications of the Fetal Medicine Foundation 35- to 36-week preeclampsia prediction competing-risk model on timing of birth.

BACKGROUND: Preeclampsia is associated with increased risks of life-threatening, -altering, and -ending complications. Assessment of risk for preeclampsia at 35 to 36 weeks' gestation by the Fetal Medicine Foundation 36-week competing-risk model identifies approximately 75% of women who will develop term preeclampsia, at a 10% screen-positive rate. OBJECTIVE: This study aimed to assess whether the Fetal Medicine Foundation 36-week model can provide personalized guidance to women about the probable timing of their delivery, whether or not they develop pregnancy hypertension. STUDY DESIGN: In this prospective nonintervention screening study at 2 maternity hospitals in England, women who did not have preeclampsia (American College of Obstetricians and Gynecologists definition) and were attending a routine hospital visit at 35 0/7 to 36 6/7 weeks' gestation underwent assessment of risk for preeclampsia, including maternal demographic characteristics, medical history, mean arterial pressure, and serum placental growth factor and soluble fms-like tyrosine kinase-1. Fetal Medicine Foundation 36-week model risk categories for subsequent preeclampsia were defined as: A, ≥0.500; B, 0.20 to 0.499; C, 0.05 to 0.199; D, 0.020 to 0.049; and E, <0.020. Obstetrical records were examined for all women to identify their gestational age at delivery, and whether they experienced a spontaneous onset of labor (irrespective of mode of delivery) or had a medically indicated birth (either induction of labor or unlabored cesarean delivery). The cumulative incidence of delivery and risk ratios, for all deliveries and for spontaneous deliveries, was assessed. RESULTS: Among 29,035 women with singleton pregnancies, 1.0%, 2.9%, 3.3%, 5.0%, 9.9%, and 77.9% were in A, B, C, D, and E risk strata, respectively. In the A (vs E) stratum, 71.95% (vs 33.52%) of births were medically indicated. Compared with women in stratum E, women in higher risk strata were more likely to deliver, and to deliver following spontaneous labor, before their due date. For example, of the women in stratum A (vs E), 14.2% (vs 1.1%; risk ratio, 12.5 [95% confidence interval, 9.45-15.35]), 48.5% (vs 5.1%; risk ratio, 8.47 [7.48-9.35]), 69.6% (vs 15.5%; risk ratio, 3.86 [3.59-4.08]), and 90.1% (vs 44.8%; risk ratio, 6.72 [4.53-9.95]) gave birth before 37 0/7, 38 0/7, 39 0/7, and 40 0/7 weeks, respectively. For women in stratum A (vs E), when censored for medically indicated births, spontaneous labor occurred more commonly before 37 0/7 (risk ratio, 4.31 [1.99-6.57]), 38 0/7 (risk ratio, 3.71 [2.48-4.88]), 39 0/7 (risk ratio, 2.87 [2.22-3.46]), and 40 0/7 (risk ratio, 1.42 [1.14-1.77]) weeks. CONCLUSION: Women in higher-risk strata gave birth earlier, and more frequently following medically indicated delivery, compared with those in lower-risk strata. Importantly, the proportion of women who gave birth following spontaneous onset of labor before their due date was also greater in higher-risk than in lower-risk women. The Fetal Medicine Foundation 36-week competing-risk model incorporates biomarkers of placental aging, including angiogenic imbalance; these results imply that a fetoplacental response to placental aging may be an important trigger for the onset of labor at term.

Effect of race on the measurement of angiogenic factors for prediction and diagnosis of pre-eclampsia.

OBJECTIVE: To examine the effect of self-declared race on serum placental growth factor (PlGF) and sFlt-1/PlGF ratio and the impact on pre-eclampsia (PE) prediction. DESIGN: Prospective observational study. SETTING: Two UK maternity hospitals. POPULATION: 29 035 women with singleton pregnancies attending a routine 35+0 to 36+6 weeks' gestation hospital visit, including 654 (2.3%) who subsequently developed PE. METHODS: The predictive performance of PlGF and sFlt-1/PlGF for PE in minority racial groups (versus white) was examined. MAIN OUTCOME MEASURE: Delivery with PE. RESULTS: Compared with white women, mean PlGF was higher and sFlt-1/PlGF ratio lower in black, South Asian, East Asian and mixed race women. In white women at a PlGF concentration cut-off corresponding to a screen-positive rate (SPR) of 10%, detection rates (DRs) were 49.1% for PE at any time and 72.3% for PE within 2 weeks after screening. In black women, at the same PlGF concentration cut-off for white women, the SPR was 5.5%, and DRs 33.6% and 55.0%, respectively; the number of PE cases was too small to evaluate screening performance in other racial groups. Using a fixed cut-off in sFlt-1/PlGF ratio to identify women at risk of developing PE, similarly diagnostically disadvantaged black women. Bias was overcome by adjusting metabolite concentrations for maternal characteristics and use of the competing risks model to estimate patient-specific risks. CONCLUSION: Screening for PE with fixed cut-offs in PlGF or sFlt-1/PlGF diagnostically disadvantages black women. It is essential that measured levels of PlGF be adjusted for race as well as other maternal characteristics.

GWAS meta-analysis of intrahepatic cholestasis of pregnancy implicates multiple hepatic genes and regulatory elements.

Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-specific liver disorder affecting 0.5-2% of pregnancies. The majority of cases present in the third trimester with pruritus, elevated serum bile acids and abnormal serum liver tests. ICP is associated with an increased risk of adverse outcomes, including spontaneous preterm birth and stillbirth. Whilst rare mutations affecting hepatobiliary transporters contribute to the aetiology of ICP, the role of common genetic variation in ICP has not been systematically characterised to date. Here, we perform genome-wide association studies (GWAS) and meta-analyses for ICP across three studies including 1138 cases and 153,642 controls. Eleven loci achieve genome-wide significance and have been further investigated and fine-mapped using functional genomics approaches. Our results pinpoint common sequence variation in liver-enriched genes and liver-specific cis-regulatory elements as contributing mechanisms to ICP susceptibility.