10 research outputs found

    External validation of prognostic models for preeclampsia in a Dutch multicenter prospective cohort

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    Objective: To perform an external validation of all published prognostic models for first-trimester prediction of the risk of developing preeclampsia (PE). Methods: Women <14 weeks of pregnancy were recruited in the Netherlands. All systematically identified prognostic models for PE that contained predictors commonly available were eligible for external validation. Results: 3,736 women were included; 87 (2.3%) developed PE. Calibration was poor due to overestimation. Discrimination of 9 models for LO-PE ranged from 0.58 to 0.71 and of 9 models for all PE from 0.55 to 0.75. Conclusion: Only a few easily applicable prognostic models for all PE showed discrimination above 0.70, which is considered an acceptable performance

    Progesterone for the prevention of preterm birth in women with multiple pregnancies: the AMPHIA trial

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    Contains fulltext : 53264.pdf (publisher's version ) (Open Access)BACKGROUND: 15% of multiple pregnancies ends in a preterm delivery, which can lead to mortality and severe long term neonatal morbidity. At present, no generally accepted strategy for the prevention of preterm birth in multiple pregnancies exists. Prophylactic administration of 17-alpha hydroxyprogesterone caproate (17OHPC) has proven to be effective in the prevention of preterm birth in women with singleton pregnancies with a previous preterm delivery. At present, there are no data on the effectiveness of progesterone in the prevention of preterm birth in multiple pregnancies. METHODS/DESIGN: We aim to investigate the hypothesis that 17OHPC will reduce the incidence of the composite neonatal morbidity of neonates by reducing the early preterm birth rate in multiple pregnancies. Women with a multiple pregnancy at a gestational age between 15 and 20 weeks of gestation will be entered in a placebo-controlled, double blinded randomised study comparing weekly 250 mg 17OHPC intramuscular injections from 16-20 weeks up to 36 weeks of gestation versus placebo. At study entry, cervical length will be measured. The primary outcome is composite bad neonatal condition (perinatal death or severe morbidity). Secondary outcome measures are time to delivery, preterm birth rate before 32 and 37 weeks, days of admission in neonatal intensive care unit, maternal morbidity, maternal admission days for preterm labour and costs. We need to include 660 women to indicate a reduction in bad neonatal outcome from 15% to 8%. Analysis will be by intention to treat. We will also analyse whether the treatment effect is dependent on cervical length. DISCUSSION: This trial will provide evidence as to whether or not 17OHPC-treatment is an effective means of preventing bad neonatal outcome due to preterm birth in multiple pregnancies. TRIAL REGISTRATION: Current Controlled Trials ISRCTN40512715

    Prediction of preterm birth in multiple pregnancies: development of a multivariable model including cervical length measurement at 16 to 21 weeks' gestation

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    To develop a multivariable prognostic model for the risk of preterm delivery in women with multiple pregnancy that includes cervical length measurement at 16 to 21 weeks' gestation and other variables. We used data from a previous randomized trial. We assessed the association between maternal and pregnancy characteristics including cervical length measurement at 16 to 21 weeks' gestation and time to delivery using multivariable Cox regression modelling. Performance of the final model was assessed for the outcomes of preterm and very preterm delivery using calibration and discrimination measures. We studied 507 women, of whom 270 (53%) delivered < 37 weeks (preterm) and 66 (13%) < 32 weeks (very preterm). Women with cervical length < 30 mm delivered more often preterm (hazard ratio 1.9; 95% CI 0.7 to 4.8). Other independently contributing predictors were previous preterm delivery, monochorionicity, smoking, educational level, and triplet pregnancy. Prediction models for preterm and very preterm delivery had a c-index of 0.68 (95% CI 0.63 to 0.72) and 0.68 (95% CI 0.62 to 0.75), respectively, and showed good calibration. In women with a multiple pregnancy, the risk of preterm delivery can be assessed with a multivariable model incorporating cervical length and other predictors. Abstract available from the publishe

    17 alpha-Hydroxyprogesterone Caproate for the Prevention of Adverse Neonatal Outcome in Multiple Pregnancies

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    OBJECTIVE: To estimate whether administration of 17 alpha-hydroxyprogesterone caproate can prevent neonatal morbidity in multiple pregnancies by reducing the preterm birth rate. METHODS: We conducted a multicenter, double-blind, placebo-controlled randomized trial in 55 obstetric clinics in the Netherlands. Women with a multiple pregnancy were randomized to weekly injections of either 250 mg 17 alpha-hydroxyprogesterone caproate or placebo, starting between 16 and 20 weeks of gestation and continuing until 36 weeks of gestation. The main outcome measure was adverse neonatal outcome. Secondary outcome measures were gestational age at delivery and delivery before 28, 32, and 37 weeks of gestation. RESULTS: We randomized 671 women. A composite measure of adverse neonatal outcome was present in 110 children (16%) born to mothers in the 17 alpha-hydroxyprogesterone caproate group, and in 80 children (12%) of mothers in the placebo group (relative risk [RR] 1.34; 95% confidence interval [CI] 0.95-1.89). The mean gestational age at delivery was 35.4 weeks for the 17 alpha-hydroxyprogesterone caproate group and 35.7 weeks for the placebo group (P =.32). Treatment with 17 alpha-hydroxyprogesterone caproate did not reduce the delivery rate before 28 weeks (6% in the 17 alpha-hydroxyprogesterone caproate group compared with 5% in the placebo group, RR 1.04; 95% CI 0.56-1.94), 32 weeks (14% compared with 10%, RR 1.37; 95% CI 0.91-2.05), or 37 weeks of gestation (55% compared with 50%, RR 1.11; 95% CI 0.97-1.28). CONCLUSION: 17 alpha-hydroxyprogesterone caproate does not prevent neonatal morbidity or preterm birth in multiple pregnancies

    External validation of prognostic models to predict risk of gestational diabetes mellitus in one Dutch cohort : prospective multicentre cohort study

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    OBJECTIVE: To perform an external validation and direct comparison of published prognostic models for early prediction of the risk of gestational diabetes mellitus, including predictors applicable in the first trimester of pregnancy. DESIGN: External validation of all published prognostic models in large scale, prospective, multicentre cohort study. SETTING: 31 independent midwifery practices and six hospitals in the Netherlands. PARTICIPANTS: Women recruited in their first trimester (<14 weeks) of pregnancy between December 2012 and January 2014, at their initial prenatal visit. Women with pre-existing diabetes mellitus of any type were excluded. MAIN OUTCOME MEASURES: Discrimination of the prognostic models was assessed by the C statistic, and calibration assessed by calibration plots. RESULTS: 3723 women were included for analysis, of whom 181 (4.9%) developed gestational diabetes mellitus in pregnancy. 12 prognostic models for the disorder could be validated in the cohort. C statistics ranged from 0.67 to 0.78. Calibration plots showed that eight of the 12 models were well calibrated. The four models with the highest C statistics included almost all of the following predictors: maternal age, maternal body mass index, history of gestational diabetes mellitus, ethnicity, and family history of diabetes. Prognostic models had a similar performance in a subgroup of nulliparous women only. Decision curve analysis showed that the use of these four models always had a positive net benefit. CONCLUSIONS: In this external validation study, most of the published prognostic models for gestational diabetes mellitus show acceptable discrimination and calibration. The four models with the highest discriminative abilities in this study cohort, which also perform well in a subgroup of nulliparous women, are easy models to apply in clinical practice and therefore deserve further evaluation regarding their clinical impact

    External validation of prognostic models for preeclampsia in a Dutch multicenter prospective cohort.

    No full text
    To perform an external validation of all published prognostic models for first-trimester prediction of the risk of developing preeclampsia (PE). Women <14 weeks of pregnancy were recruited in the Netherlands. All systematically identified prognostic models for PE that contained predictors commonly available were eligible for external validation. 3,736 women were included; 87 (2.3%) developed PE. Calibration was poor due to overestimation. Discrimination of 9 models for LO-PE ranged from 0.58 to 0.71 and of 9 models for all PE from 0.55 to 0.75. Only a few easily applicable prognostic models for all PE showed discrimination above 0.70, which is considered an acceptable performance

    External validation of prognostic models for preeclampsia in a Dutch multicenter prospective cohort

    No full text
    Objective: To perform an external validation of all published prognostic models for first-trimester prediction of the risk of developing preeclampsia (PE). Methods: Women <14 weeks of pregnancy were recruited in the Netherlands. All systematically identified prognostic models for PE that contained predictors commonly available were eligible for external validation. Results: 3,736 women were included; 87 (2.3%) developed PE. Calibration was poor due to overestimation. Discrimination of 9 models for LO-PE ranged from 0.58 to 0.71 and of 9 models for all PE from 0.55 to 0.75. Conclusion: Only a few easily applicable prognostic models for all PE showed discrimination above 0.70, which is considered an acceptable performance
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