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Abstract Background Hypertensive disorders, i.e. pregnancy induced hypertension and preeclampsia, complicate 10 to15% of all pregnancies at term and are a major cause of maternal and perinatal morbidity and mortality. The only causal treatment is delivery. In case of preterm pregnancies conservative management is advocated if the risks for mother and child remain acceptable. In contrast, there is no consensus on how to manage mild hypertensive disease in pregnancies at term. Induction of labour might prevent maternal and neonatal complications at the expense of increased instrumental vaginal delivery rates and caesarean section rates. Methods/Design Women with a pregnancy complicated by pregnancy induced hypertension or mild preeclampsia at a gestational age between 36+0 and 41+0 weeks will be asked to participate in a multi-centre randomised controlled trial. Women will be randomised to either induction of labour or expectant management for spontaneous delivery. The primary outcome of this study is severe maternal morbidity, which can be complicated by maternal mortality in rare cases. Secondary outcome measures are neonatal mortality and morbidity, caesarean and vaginal instrumental delivery rates, maternal quality of life and costs. Analysis will be by intention to treat. In total, 720 pregnant women have to be randomised to show a reduction in severe maternal complications of hypertensive disease from 12 to 6%. Discussion This trial will provide evidence as to whether or not induction of labour in women with pregnancy induced hypertension or mild preeclampsia (nearly) at term is an effective treatment to prevent severe maternal complications. Trial Registration The protocol is registered in the clinical trial register number ISRCTN08132825.

Objective To assess whether postpartum hemorrhage can be predicted in women with gestational hypertension or mild preeclampsia at term. Design A cohort study in which we used data from our multicentre randomized controlled trial ( HYPITAT trial). Setting The study was conducted in 38 hospitals in the Netherlands between 2005 and 2008. Population Women with gestational hypertension or mild preeclampsia at term ( n = 1132). Methods An antepartum model (model A) and an antepartum/intrapartum model (model B) were created using logistic regression. The predictive capacity of the models was assessed with receiver operating characteristic analysis and calibration. Main outcome measure Postpartum hemorrhage, defined as blood loss >1000 mL within 24 h after delivery. Results Postpartum hemorrhage occurred in 118 (10.4%) women. Maternal age (odds ratio 1.03), prepregnancy body mass index (odds ratio 0.96), and women with preeclampsia (odds ratio 1.5) were independent antepartum prognostic variables of postpartum hemorrhage. Intrapartum variables incorporated in the model were gestational age at delivery (odds ratio 1.2), duration of dilatation stage (odds ratio 1.1), and episiotomy (odds ratio 1.5). Model A and model B showed moderate discrimination, with areas under the receiver operating characteristic curve of 0.59 (95% confidence interval 0.53-0.64) and 0.64 (95% confidence interval 0.59-0.70), respectively. Calibration was moderate for model A (Hosmer-Lemeshow p = 0.26) but better for model B (Hosmer-Lemeshow p = 0.36). The rates of postpartum hemorrhage ranged from 4% (lowest 10%) to 22% (highest 10%). Conclusion In the assessment of performance of a prediction model, calibration is more important than discriminative capacity. Our prediction model shows that for women with gestational hypertension or mild preeclampsia at term, distinction between low and high risk of developing postpartum hemorrhage is possible when antepartum and intrapartum variables are combined. [ABSTRACT FROM AUTHOR]

Objective. To evaluate whether eclampsia can be predicted in gestational hypertension or mild preeclampsia at term. Methods. For this case-control study we selected 76 cases with eclampsia from the LEMMoN study and 1149 controls with mild hypertensive disease of pregnancy, who did not develop eclampsia, from the HYPITAT study. Risk indicators for eclampsia, identified in multivariable logistic regression, were used to assess the predictive capacity of our model with receiver-operating characteristic (ROC) curve analysis. Model optimism was assessed with bootstrapping. Results. Maternal age, non-Caucasian ethnicity, systolic blood pressure >155 mmHg, ≥2++ protein on dipstick, elevated uric acid, creatinin >74 μmol//L, aspartate aminotransferase >30 U//L, and lactate dehydrogenase >400 U//L were significantly associated with eclampsia. Other factors included in the model were previous fetal loss, previous miscarriage, gestational age, and low platelet count. The area under the ROC curve was 0.92. Bootstrapping showed minimal overfitting of the model. Conclusion. In women with gestational hypertension or mild preeclampsia at term eclampsia can be predicted. [ABSTRACT FROM AUTHOR]

A letter to the editor and the authors' response are presented about the article "Induction of Labour Versus Expectant Monitoring for Gestational Hypertension or Mild Pre-Eclampsia After 36 Weeks' Gestation (HYPITAT): A Multicenter, Open-Label Randomised Controlled Trial," by C. M. Koopmans and colleagues, published in the September 19, 2009 issue.

Biomarkers that predict treatment effects may be used to guide treatment decisions, thus improving patient outcomes. A meta-analysis of individual participant data (IPD) is potentially more powerful than a single-study data analysis in evaluating markers for treatment selection. Our study was motivated by the IPD that were collected from 2 randomized controlled trials of hypertension and preeclampsia among pregnant women to evaluate the effect of labor induction over expectant management of the pregnancy in preventing progression to severe maternal disease. The existing literature on statistical methods for biomarker evaluation in IPD meta-analysis have evaluated a marker's performance in terms of its ability to predict risk of disease outcome, which do not directly apply to the treatment selection problem. In this study, we propose a statistical framework for evaluating a marker for treatment selection given IPD from a small number of individual clinical trials. We derive marker-based treatment rules by minimizing the average expected outcome across studies. The application of the proposed methods to the IPD from 2 studies in women with hypertension in pregnancy is presented., (Copyright © 2018 John Wiley & Sons, Ltd.)