Search

Objective: Effective first‐trimester screening for pre‐eclampsia (PE) can be achieved using a competing‐risks model that combines risk factors from the maternal history with multiples of the median (MoM) values of biomarkers. A new model using artificial intelligence through machine‐learning methods has been shown to achieve similar screening performance without the need for conversion of raw data of biomarkers into MoM. This study aimed to investigate whether this model can be used across populations without specific adaptations. Methods: Previously, a machine‐learning model derived with the use of a fully connected neural network for first‐trimester prediction of early (< 34 weeks), preterm (< 37 weeks) and all PE was developed and tested in a cohort of pregnant women in the UK. The model was based on maternal risk factors and mean arterial blood pressure (MAP), uterine artery pulsatility index (UtA‐PI), placental growth factor (PlGF) and pregnancy‐associated plasma protein‐A (PAPP‐A). In this study, the model was applied to a dataset of 10 110 singleton pregnancies examined in Spain who participated in the first‐trimester PE validation (PREVAL) study, in which first‐trimester screening for PE was carried out using the Fetal Medicine Foundation (FMF) competing‐risks model. The performance of screening was assessed by examining the area under the receiver‐operating‐characteristics curve (AUC) and detection rate (DR) at a 10% screen‐positive rate (SPR). These indices were compared with those derived from the application of the FMF competing‐risks model. The performance of screening was poor if no adjustment was made for the analyzer used to measure PlGF, which was different in the UK and Spain. Therefore, adjustment for the analyzer used was performed using simple linear regression. Results: The DRs at 10% SPR for early, preterm and all PE with the machine‐learning model were 84.4% (95% CI, 67.2–94.7%), 77.8% (95% CI, 66.4–86.7%) and 55.7% (95% CI, 49.0–62.2%), respectively, with the corresponding AUCs of 0.920 (95% CI, 0.864–0.975), 0.913 (95% CI, 0.882–0.944) and 0.846 (95% CI, 0.820–0.872). This performance was achieved with the use of three of the biomarkers (MAP, UtA‐PI and PlGF); inclusion of PAPP‐A did not provide significant improvement in DR. The machine‐learning model had similar performance to that achieved by the FMF competing‐risks model (DR at 10% SPR, 82.7% (95% CI, 69.6–95.8%) for early PE, 72.7% (95% CI, 62.9–82.6%) for preterm PE and 55.1% (95% CI, 48.8–61.4%) for all PE) without requiring specific adaptations to the population. Conclusions: A machine‐learning model for first‐trimester prediction of PE based on a neural network provides effective screening for PE that can be applied in different populations. However, before doing so, it is essential to make adjustments for the analyzer used for biochemical testing. © 2023 International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR]

This article, published in the journal Ultrasound in Obstetrics & Gynecology, examines the effectiveness of the cerebro-placental ratio (CPR) in predicting adverse perinatal outcomes in uncomplicated singleton pregnancies attending a 40-42 week appointment. The study analyzed data from 3143 pregnancies and found that maternal age, body mass index, racial origin, parity, and labor induction were significant predictors of adverse perinatal outcomes. However, the addition of the CPR did not improve the predictive performance, and the CPR alone had a low detection rate. Therefore, the study concludes that the CPR is not a reliable predictor of adverse perinatal outcomes in post-term pregnancies. [Extracted from the article]

Objective: To describe our experience in first-trimester screening for trisomies 21 and 18 firstly by the combined test alone and secondly by cell-free (cf) DNA testing contingent on the results from a previously performed combined test.Methods: Women with singleton pregnancies attending Torrejon University Hospital in Madrid, Spain, from November 2011 to January 2016, were screened for trisomy (T)21 and T18 by the combined test at 11-13 weeks. Before the introduction of cfDNA testing, women at high risk (>1 in 250) were offered invasive testing (IT) and from January 2015 they were offered cfDNA test as well as IT.Results: Combined test was performed in 6011 pregnancies. The risk was high in 202 (3.4%) cases. There was complete follow-up for 5507 (91.6%) pregnancies. Detection rate (DR) for T21 was 83.3% (15/18) and 100% (4/4) for T18. Additionally, 2/2 (100%) cases of T13 and 2/2 (100%) cases of triploidy were also detected. False positive rate (FPR) was 3.2% (174/5488). The introduction of this contingent model was followed by a 73% reduction on the IT rate in the high-risk group, from 76.3% to 20.8%.Conclusion: Contingent screening for trisomies 21 and 18 by cfDNA testing at 11-13 weeks is feasible and has a lower IT rate than combined testing alone. [ABSTRACT FROM AUTHOR]

Background and Objectives : The aim of this study was to analyze the association between maternal risk factors, such as age, body mass index (BMI), and cigarette smoking, and perinatal outcomes. Materials and Methods : We conducted a retrospective analysis based on prospectively collected data at Hospital Universitario de Torrejón (Madrid, Spain) between September 2017 and December 2019. All pregnant women with singleton pregnancies and non-malformed live fetuses attending their routine ultrasound examination at 11+0 to 13+6 weeks' gestation were invited to participate. The association between preeclampsia, preterm birth, gestational diabetes mellitus (GDM), small-for-gestational-age (SGA) or fetal-growth-restricted (FGR) neonates, and type of delivery and maternal age, BMI, and cigarette smoking was studied. Logistic mixed models were used to analyze the data. Results : A total of 1921 patients were included in the analysis. Women who were ≥40 years old had a significantly higher risk of having GDM (odds ratio (OR) 1.61, 95% confidence interval (CI) 1.08 to 2.36) and SGA neonates (OR 1.54, 95% CI 1.00 to 2.37). Women with a BMI < 18 had an increased rate of giving birth to SGA and FGR neonates (OR 3.28, 95% CI 1.51 to 7.05, and OR 3.73, 95% CI 1.54 to 8.37, respectively), whereas women with a BMI ≥ 35 had a higher risk of GDM (OR 3.10, 95% CI 1.95 to 4.89). Smoking increased the risk of having SGA and FGR neonates (OR 1.83, 95% CI 1.36 to 2.46, and OR 1.91, 95% CI 1.29 to 2.78). Conclusions : Advanced maternal age, low or high BMI, and smoking status are significant risk factors for pregnancy complications. Both clinicians and society should concentrate their efforts on addressing these factors to enhance reproductive health.

Background and Objectives: Over the last few years, great interest has arisen in the role of the cerebroplacental ratio (CPR) to identify low-risk pregnancies at higher risk of adverse pregnancy outcomes. This study aimed to assess the predictive capacity of the CPR for adverse perinatal outcomes in all uncomplicated singleton pregnancies attending an appointment at 40-42 weeks. Materials and Methods : This is a retrospective cohort study including all consecutive singleton pregnancies undergoing a routine prenatal care appointment after 40 weeks in three maternity units in Spain and the United Kingdom from January 2017 to December 2019. The primary outcome was adverse perinatal outcomes defined as stillbirth or neonatal death, cesarean section or instrumental delivery due to fetal distress during labor, umbilical arterial cord blood pH < 7.0, umbilical venous cord blood pH < 7.1, Apgar score at 5 min < 7, and admission to the neonatal unit. Logistic mixed models and ROC curve analyses were used to analyze the data. Results: A total of 3143 pregnancies were analyzed, including 537 (17.1%) with an adverse perinatal outcome. Maternal age (odds ratio (OR) 1.03, 95% confidence interval (CI) 1.01 to 1.04), body mass index (OR 1.04, 95% CI 1.03 to 1.06), racial origin (OR 2.80, 95% CI 1.90 to 4.12), parity (OR 0.36, 95% CI 0.29 to 0.45), and labor induction (OR 1.79, 95% CI 1.36 to 2.35) were significant predictors of adverse perinatal outcomes with an area under the ROC curve of 0.743 (95% CI 0.720 to 0.766). The addition of the CPR to the previous model did not improve performance. Additionally, the CPR alone achieved a detection rate of only 11.9% (95% CI 9.3 to 15) when using the 10th centile as the screen-positive cutoff. Conclusions: Our data on late-term unselected pregnancies suggest that the CPR is a poor predictor of adverse perinatal outcomes.

Background: Fetal smallness affects 10% of pregnancies. Small fetuses are at a higher risk of adverse outcomes. Their management using estimated fetal weight and feto-maternal Doppler has a high sensitivity for adverse outcomes; however, more than 60% of fetuses are electively delivered at 37 to 38 weeks. On the other hand, classification using angiogenic factors seems to have a lower false-positive rate. Here, we present a protocol for the Fetal Growth Restriction at Term Managed by Angiogenic Factors Versus Feto-Maternal Doppler (GRAFD) trial, which compares the use of angiogenic factors and Doppler to manage small fetuses at term., Objective: The primary objective is to demonstrate that classification based on angiogenic factors is not inferior to estimated fetal weight and Doppler at detecting fetuses at risk of adverse perinatal outcomes., Methods: This is a multicenter, open-label, randomized controlled trial conducted in 20 hospitals across Spain. A total of 1030 singleton pregnancies with an estimated fetal weight ≤10th percentile at 36+0 to 37+6 weeks+days will be recruited and randomly allocated to either the control or the intervention group. In the control group, standard Doppler-based management will be used. In the intervention group, cases with a soluble fms-like tyrosine kinase to placental growth factor ratio ≥38 will be classified as having fetal growth restriction; otherwise, they will be classified as being small for gestational age. In both arms, the fetal growth restriction group will be delivered at ≥37 weeks and the small for gestational age group at ≥40 weeks. We will assess differences between the groups by calculating the relative risk, the absolute difference between incidences, and their 95% CIs., Results: Recruitment for this study started on September 28, 2020. The study results are expected to be published in peer-reviewed journals and disseminated at international conferences in early 2023., Conclusions: The angiogenic factor-based protocol may reduce the number of pregnancies classified as having fetal growth restriction without worsening perinatal outcomes. Moreover, reducing the number of unnecessary labor inductions would reduce costs and the risks derived from possible iatrogenic complications. Additionally, fewer inductions would lower the rate of early-term neonates, thus improving neonatal outcomes and potentially reducing long-term infant morbidities., Trial Registration: ClinicalTrials.gov NCT04502823; https://clinicaltrials.gov/ct2/show/NCT04502823., International Registered Report Identifier (irrid): DERR1-10.2196/37452., (©Pablo Garcia-Manau, Manel Mendoza, Erika Bonacina, Raquel Martin-Alonso, Lourdes Martin, Ana Palacios, Maria Luisa Sanchez, Cristina Lesmes, Ivan Hurtado, Esther Perez, Albert Tubau, Patricia Ibañez, Marina Alcoz, Nuria Valiño, Elena Moreno, Carlota Borrero, Esperanza Garcia, Eva Lopez-Quesada, Sonia Diaz, Jose Roman Broullon, Mireia Teixidor, Carolina Chulilla, Maria M Gil, Monica Lopez, Amparo Candela-Hidalgo, Andrea Salinas-Amoros, Anna Moreno, Francesca Morra, Oscar Vaquerizo, Beatriz Soriano, Marta Fabre, Elena Gomez-Valencia, Ana Cuiña, Nicolas Alayon, Jose Antonio Sainz, Angels Vives, Esther Esteve, Vanesa Ocaña, Miguel Ángel López, Anna Maroto, Elena Carreras. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 11.10.2022.)