Early detection of isolated severe congenital heart defects is associated with a lower threshold to terminate the pregnancy

Introduction: Early detection of isolated severe congenital heart defects (CHDs) allows extra time for chromosomal analysis and informed decision making, resulting in improved perinatal management and patient satisfaction. Therefore, the aim of this study was to assess the value of an additional first-trimester screening scan compared to only a second-trimester scan in fetuses diagnosed with isolated severe CHDs. Prenatal detection rate, time of prenatal diagnosis, and pregnancy outcome were evaluated in the Netherlands after implementation of a national screening program.Materials and methods: We performed a retrospective geographical cohort study and included 264 pre- and postnatally diagnosed isolated severe CHD cases between January 1, 2007, and December 31, 2015, in the Amsterdam region. Severe CHD was defined as potentially life threatening if intervention within the first year of life was required. Two groups were defined: those with a first- and second-trimester anomaly scan (group 1) and those with a second-trimester anomaly scan only (group 2). A first-trimester scan was defined as a scan between 11 + 0 and 13 + 6 weeks of gestation.Results: Overall, the prenatal detection rate for isolated severe CHDs was 65%; 63% were detected before 24 weeks of gestation (97% of all prenatally detected CHDs). Prenatal detection rate was 70.2% in the group with a first- and second-trimester scan (group 1) and 58% in the group with a second-trimester scan only (group 2) (p Conclusion: Prenatal detection rate of isolated severe CHDs and termination of pregnancy rate was higher in the group with both a first- and second-trimester scan. We found no differences between timing of terminations. The additional time after diagnosis allows for additional genetic testing and optimal counseling of expectant parents regarding prognosis and perinatal management, so that well-informed decisions can be made.</p

Widespread DNA hypomethylation at gene enhancer regions in placentas associated with early-onset pre-eclampsia.

Pre-eclampsia is a serious complication of pregnancy that can affect both maternal and fetal outcomes. Early-onset pre-eclampsia (EOPET) is a severe form of pre-eclampsia that is associated with altered physiological characteristics and gene expression in the placenta. DNA methylation is a relatively stable epigenetic modification to DNA that can reflect gene expression, and can provide insight into the mechanisms underlying such expression changes. This case-control study focused on DNA methylation and gene expression of whole chorionic villi samples from 20 EOPET placentas and 20 gestational age-matched controls from pre-term births. DNA methylation was also assessed in placentas affected by late-onset pre-eclampsia (LOPET) and normotensive intrauterine growth restriction (nIUGR). The Illumina HumanMethylation450 BeadChip was used to assess DNA methylation at >480 000 cytosine-guanine dinucleotide (CpG) sites. The Illumina HT-12v4 Expression BeadChip was used to assess gene expression of >45 000 transcripts in a subset of cases and controls. DNA methylation analysis by pyrosequencing was used to follow-up the initial findings in four genes with a larger cohort of cases and controls, including nIUGR and LOPET placentas. Bioinformatic analysis was used to identify overrepresentation of gene ontology categories and transcription factor binding motifs. We identified 38 840 CpG sites with significant (false discovery rate 12.5% methylation difference compared with the controls. Significant sites were enriched at the enhancers and low CpG density regions of the associated genes and the majority (74.5%) of these sites were hypomethylated in EOPET. EOPET, but not associated clinical features, such as intrauterine growth restriction (IUGR), presented a distinct DNA methylation profile. CpG sites from four genes relevant to pre-eclampsia (INHBA, BHLHE40, SLC2A1 and ADAM12) showed different extent of changes in LOPET and nIUGR. Genome-wide expression in a subset of samples showed that some of the gene expression changes were negatively correlated with DNA methylation changes, particularly for genes that are responsible for angiogenesis (such as EPAS1 and FLT1). Results could be confounded by altered cell populations in abnormal placentas. Larger sample sizes are needed to fully address the possibility of sub-profiles of methylation within the EOPET cohort. Based on DNA methylation profiling, we conclude that there are widespread DNA methylation alterations in EOPET that may be associated with changes in placental function. This property may provide a useful tool for early screening of such placentas. This study identifies DNA methylation changes at many loci previously reported to have altered gene expression in EOPET placentas, as well as in novel biologically relevant genes we confirmed to be differentially expressed. These results may be useful for DNA- methylation-based non-invasive prenatal diagnosis of at-risk pregnancies

External validation, update and development of prediction models for pre-eclampsia using an Individual Participant Data (IPD) meta-analysis: the International Prediction of Pregnancy Complication Network (IPPIC pre-eclampsia) protocol.

Background: Pre-eclampsia, a condition with raised blood pressure and proteinuria is associated with an increased risk of maternal and offspring mortality and morbidity. Early identification of mothers at risk is needed to target management. Methods/design: We aim to systematically review the existing literature to identify prediction models for pre-eclampsia. We have established the International Prediction of Pregnancy Complication Network (IPPIC), made up of 72 researchers from 21 countries who have carried out relevant primary studies or have access to existing registry databases, and collectively possess data from more than two million patients. We will use the individual participant data (IPD) from these studies to externally validate these existing prediction models and summarise model performance across studies using random-effects meta-analysis for any, late (after 34 weeks) and early (before 34 weeks) onset pre-eclampsia. If none of the models perform well, we will recalibrate (update), or develop and validate new prediction models using the IPD. We will assess the differential accuracy of the models in various settings and subgroups according to the risk status. We will also validate or develop prediction models based on clinical characteristics only; clinical and biochemical markers; clinical and ultrasound parameters; and clinical, biochemical and ultrasound tests. Discussion: Numerous systematic reviews with aggregate data meta-analysis have evaluated various risk factors separately or in combination for predicting pre-eclampsia, but these are affected by many limitations. Our large-scale collaborative IPD approach encourages consensus towards well developed, and validated prognostic models, rather than a number of competing non-validated ones. The large sample size from our IPD will also allow development and validation of multivariable prediction model for the relatively rare outcome of early onset pre-eclampsia. Trial registration: The project was registered on Prospero on the 27 November 2015 with ID: CRD42015029349

External validation of prognostic models to predict stillbirth using the International Prediction of Pregnancy Complications (IPPIC) Network database: an 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. (c) 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.Peer reviewe

Severity of antenatal hydronephrosis as a predictor of urologic anomalies after birth

Poster abstract 342Ravi de Roo, Emily Kleinrouweler, Tonny Bouts, Ben Mol, Eva Pajkr

Determination of threshold value for follow-up of isolated antenatal hydronephrosis detected in the second trimester

Abstract not availableRavi de Roo, Bart J. Voskamp, C. Emily Kleinrouweler, Ben W. Mol, Eva Pajkrt, Antonia H.M. Bout

Follow-up ultrasound in second-trimester low-positioned anterior and posterior placentae: prospective cohort study

Abstract not available.C.H.J.R. Jansen, C.E. Kleinrouweler, A.W. Kastelein, L. Ruiter, E. Van Leeuwen, B.W. Mol, and E. Pajkr

Is short first-trimester crown-rump length associated with spontaneous preterm birth?

ObjectiveTo assess the association between first-trimester crown-rump length (CRL) and the risk of spontaneous preterm birth before 32 weeks' gestation.MethodsWe performed a matched case-control study of 129 women with spontaneous preterm birth at ResultsCRL-MoM was not associated with spontaneous preterm birth: odds ratio (OR) 1.10 (95% CI, 0.89-1.36) per 0.10 MoM increase in CRL. Timing of measurement did not influence the model (P = 0.59). This was confirmed when restricting the analysis to the 93 pairs with CRL measurements made between 10 + 0 and 13 + 6 weeks: OR for preterm birth 1.07 (95% CI, 0.83-1.37) per 0.10 MoM increase in CRL.ConclusionA short CRL in the first trimester is not associated with spontaneous preterm birth before 32 weeks' gestation, thus short CRL cannot be used to identify women at increased risk of preterm birth.B. M. Kazemier, C. E. Kleinrouweler, M. A. Oudijk, J. A. M. Van der post, B. W. J. Mol, J. Y. Vis and E. Pajkr

Influence of cut-off value on prevalence of short cervical length

Research into fetal development and medicin