Objectives To develop a predictive model for pre-eclampsia based on clinical risk factors for nulliparous women and to identify a subgroup at increased risk, in whom specialist referral might be indicated. Design Prospective multicentre cohort. Setting Five centres in Auckland, New Zealand; Adelaide, Australia; Manchester and London, United Kingdom; and Cork, Republic of Ireland. Participants 3572 “healthy” nulliparous women with a singleton pregnancy from a large international study; data on pregnancy outcome were available for 3529 (99%). Main outcome measure Pre-eclampsia defined as ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg, or both, on at least two occasions four hours apart after 20 weeks’ gestation but before the onset of labour, or postpartum, with either proteinuria or any multisystem complication. Preterm pre-eclampsia was defined as women with pre-eclampsia delivered before 37⁺⁰ weeks’ gestation. In the stepwise logistic regression the comparison group was women without pre-eclampsia. Results Of the 3529 women, 186 (5.3%) developed pre-eclampsia, including 47 (1.3%) with preterm pre-eclampsia. Clinical risk factors at 14-16 weeks’ gestation were age, mean arterial blood pressure, body mass index (BMI), family history of pre-eclampsia, family history of coronary heart disease, maternal birth weight, and vaginal bleeding for at least five days. Factors associated with reduced risk were a previous single miscarriage with the same partner, taking at least 12 months to conceive, high intake of fruit, cigarette smoking, and alcohol use in the first trimester. The area under the receiver operating characteristics curve (AUC), under internal validation, was 0.71. Addition of uterine artery Doppler indices did not improve performance (internal validation AUC 0.71). A framework for specialist referral was developed based on a probability of pre-eclampsia generated by the model of at least 15% or an abnormal uterine artery Doppler waveform in a subset of women with single risk factors. Nine per cent of nulliparous women would be referred for a specialist opinion, of whom 21% would develop pre-eclampsia. The relative risk for developing pre-eclampsia and preterm pre-eclampsia in women referred to a specialist compared with standard care was 5.5 and 12.2, respectively. Conclusions The ability to predict pre-eclampsia in healthy nulliparous women using clinical phenotype is modest and requires external validation in other populations. If validated, it could provide a personalised clinical risk profile for nulliparous women to which biomarkers could be added. Trial registration ACTRN12607000551493.

More than half of all cases of preeclampsia occur in healthy first-time pregnant women. Our aim was to develop a method to predict those at risk by combining clinical factors and measurements of biomarkers in women recruited to the Screening for Pregnancy Endpoints (SCOPE) study of low-risk nulliparous women. Forty-seven biomarkers identified on the basis of (1) association with preeclampsia, (2) a biological role in placentation, or (3) a role in cellular mechanisms involved in the pathogenesis of preeclampsia were measured in plasma sampled at 14 to 16 weeks’ gestation from 5623 women. The cohort was randomly divided into training (n=3747) and validation (n=1876) cohorts. Preeclampsia developed in 278 (4.9%) women, of whom 28 (0.5%) developed early-onset preeclampsia. The final model for the prediction of preeclampsia included placental growth factor, mean arterial pressure, and body mass index at 14 to 16 weeks’ gestation, the consumption of ≥3 pieces of fruit per day, and mean uterine artery resistance index. The area under the receiver operator curve (95% confidence interval) for this model in training and validation cohorts was 0.73 (0.70–0.77) and 0.68 (0.63–0.74), respectively. A predictive model of early-onset preeclampsia included angiogenin/placental growth factor as a ratio, mean arterial pressure, any pregnancy loss <10 weeks, and mean uterine artery resistance index (area under the receiver operator curve [95% confidence interval] in training and validation cohorts, 0.89 [0.78–1.0] and 0.78 [0.58–0.99], respectively). Neither model included pregnancy-associated plasma protein A, previously reported to predict preeclampsia in populations of mixed parity and risk. In nulliparous women, combining multiple biomarkers and clinical data provided modest prediction of preeclampsia.

Serum inhibin A and activin A concentrations increase in pre-eclampsia. We investigated the time courses of the changes in relation to the onset of the maternal syndrome and if their measurement could be useful for clinical prediction particularly in relation to early onset disease, the most severe of the clinical presentations. Serial samples were taken from 1496 healthy nulliparae. Changes in activin A and inhibin A were analysed in women with: early onset pre-eclampsia (n = 11), pre-eclampsia delivering at 34–36 weeks (n = 14), term pre-eclampsia (n = 25) and gestational hypertension (n = 25); and in a subset with uncomplicated pregnancies (n = 25). Serum inhibin A and activin A were increased in all groups prior to pre-eclampsia, before 20 weeks in those with early onset pre-eclampsia. Screening efficacy was determined at 15–19 and 21–25 weeks in all women who developed pre-eclampsia (n = 70) and randomly selected controls (n = 240). Predictive sensitivities were low (16–59%) but much better for early onset pre-eclampsia: 67 and 44% at 15–19 weeks and 89 and 89% at 21–25 weeks for inhibin A and activin A respectively. Hence, serum inhibin A and activin A concentrations increase before the onset of pre-eclampsia at gestational ages that depend on when pre-eclampsia develops. On their own such measures are unlikely to prove efficient for screening.

Objective. Excessive gestational weight gain (GWG) is associated with adverse maternal and child outcomes and contributes to obesity in women. Our aim was to identify early pregnancy factors associated with excessive GWG, in a contemporary nulliparous cohort.Methods. Participants in the SCOPE study were classified into GWG categories (“not excessive” versus “excessive”) based on pregravid body mass index (BMI) using 2009 Institute of Medicine (IOM) guidelines. Maternal characteristics and pregnancy risk factors at 14–16 weeks were compared between categories and multivariable analysis controlled for confounding factors.Results. Of 1950 women, 17% gained weight within the recommended range, 74% had excessive and 9% inadequate GWG. Women with excessive GWG were more likely to be overweight (adjOR 2.9 (95% CI 2.2–3.8)) or obese (adjOR 2.5 (95% CI 1.8–3.5)) before pregnancy compared to women with a normal BMI. Other factors independently associated with excessive GWG included recruitment in Ireland, younger maternal age, increasing maternal birthweight, cessation of smoking by 14–16 weeks, increased nightly sleep duration, high seafood diet, recent immigrant, limiting behaviour, and decreasing exercise by 14–16 weeks. Fertility treatment was protective.Conclusions. Identification of potentially modifiable risk factors for excessive GWG provides opportunities for intervention studies to improve pregnancy outcome and prevent maternal obesity.