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Objective: To compare the predictive performance of three different mathematical models for first‐trimester screening of pre‐eclampsia (PE), which combine maternal risk factors with mean arterial pressure (MAP), uterine artery pulsatility index (UtA‐PI) and serum placental growth factor (PlGF), and two risk‐scoring systems. Methods: This was a prospective cohort study performed in eight fetal medicine units in five different regions of Spain between September 2017 and December 2019. All pregnant women with singleton pregnancy and a non‐malformed live fetus attending their routine ultrasound examination at 11 + 0 to 13 + 6 weeks' gestation were invited to participate in the study. Maternal characteristics and medical history were recorded and measurements of MAP, UtA‐PI, serum PlGF and pregnancy‐associated plasma protein‐A (PAPP‐A) were converted into multiples of the median (MoM). Risks for term PE, preterm PE (< 37 weeks' gestation) and early PE (< 34 weeks' gestation) were calculated according to the FMF competing‐risks model, the Crovetto et al. logistic regression model and the Serra et al. Gaussian model. PE classification was also performed based on the recommendations of the National Institute for Health and Care Excellence (NICE) and the American College of Obstetricians and Gynecologists (ACOG). We estimated detection rates (DR) with their 95% CIs at a fixed 10% screen‐positive rate (SPR), as well as the area under the receiver‐operating‐characteristics curve (AUC) for preterm PE, early PE and all PE for the three mathematical models. For the scoring systems, we calculated DR and SPR. Risk calibration was also assessed. Results: The study population comprised 10 110 singleton pregnancies, including 32 (0.3%) that developed early PE, 72 (0.7%) that developed preterm PE and 230 (2.3%) with any PE. At a fixed 10% SPR, the FMF, Crovetto et al. and Serra et al. models detected 82.7% (95% CI, 69.6–95.8%), 73.8% (95% CI, 58.7–88.9%) and 79.8% (95% CI, 66.1–93.5%) of early PE; 72.7% (95% CI, 62.9–82.6%), 69.2% (95% CI, 58.8–79.6%) and 74.1% (95% CI, 64.2–83.9%) of preterm PE; and 55.1% (95% CI, 48.8–61.4%), 47.1% (95% CI, 40.6–53.5%) and 53.9% (95% CI, 47.4–60.4%) of all PE, respectively. The best correlation between predicted and observed cases was achieved by the FMF model, with an AUC of 0.911 (95% CI, 0.879–0.943), a slope of 0.983 (95% CI, 0.846–1.120) and an intercept of 0.154 (95% CI, –0.091 to 0.397). The NICE criteria identified 46.7% (95% CI, 35.3–58.0%) of preterm PE at 11% SPR and ACOG criteria identified 65.9% (95% CI, 55.4–76.4%) of preterm PE at 33.8% SPR. Conclusions: The best performance of screening for preterm PE is achieved by mathematical models that combine maternal factors with MAP, UtA‐PI and PlGF, as compared to risk‐scoring systems such as those of NICE and ACOG. While all three algorithms show similar results in terms of overall prediction, the FMF model showed the best performance at an individual level. © 2024 International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR]

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]

Objective: To evaluate the diagnostic accuracy of the Fetal Medicine Foundation (FMF) competing‐risks model, incorporating maternal characteristics, mean arterial pressure (MAP), uterine artery pulsatility index (UtA‐PI) and placental growth factor (PlGF) (the 'triple test'), for the prediction at 11–13 weeks' gestation of preterm pre‐eclampsia (PE) in a Spanish population. Methods: This was a prospective cohort study performed in eight fetal medicine units in five different regions of Spain between September 2017 and December 2019. All pregnant women with a singleton pregnancy and a non‐malformed live fetus attending a routine ultrasound examination at 11 + 0 to 13 + 6 weeks' gestation were invited to participate. Maternal demographic characteristics and medical history were recorded and MAP, UtA‐PI, serum PlGF and pregnancy‐associated plasma protein‐A (PAPP‐A) were measured following standardized protocols. Treatment with aspirin during pregnancy was also recorded. Raw values of biomarkers were converted into multiples of the median (MoM), and audits were performed periodically to provide regular feedback to operators and laboratories. Patient‐specific risks for term and preterm PE were calculated according to the FMF competing‐risks model, blinded to pregnancy outcome. The performance of screening for PE, taking into account aspirin use, was assessed by calculating the area under the receiver‐operating‐characteristics curve (AUC) and detection rate (DR) at a 10% fixed screen‐positive rate (SPR). Risk calibration of the model was assessed. Results: The study population comprised 10 110 singleton pregnancies, including 72 (0.7%) that developed preterm PE. In the preterm PE group, compared to those without PE, median MAP MoM and UtA‐PI MoM were significantly higher, and median serum PlGF MoM and PAPP‐A MoM were significantly lower. In women with PE, the deviation from normal in all biomarkers was inversely related to gestational age at delivery. Screening for preterm PE by a combination of maternal characteristics and medical history with MAP, UtA‐PI and PlGF had a DR, at 10% SPR, of 72.7% (95% CI, 62.9–82.6%). An alternative strategy of replacing PlGF with PAPP‐A in the triple test was associated with poorer screening performance for preterm PE, giving a DR of 66.5% (95% CI, 55.8–77.2%). The calibration plot showed good agreement between predicted risk and observed incidence of preterm PE, with a slope of 0.983 (95% CI, 0.846–1.120) and an intercept of 0.154 (95% CI, −0.091 to 0.397). Conclusions: The FMF model is effective in predicting preterm PE in the Spanish population at 11–13 weeks' gestation. This method of screening is feasible to implement in routine clinical practice, but it should be accompanied by a robust audit and monitoring system, in order to maintain high‐quality screening. © 2023 International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR]

Antecedentes: La exploración ecográfica entre las semanas 11 y 14 tiene un papel fundamental en el cribado de anomalías cromosómicas, siendo la medida de la translucencia nucal un método bien establecido y ampliamente aceptado para este fin. Objetivo: Evaluar retrospectivamente la evolución de los fetos con translucencia nucal aumentada y cariotipo normal. Método: Se recogieron los datos de 104 fetos con TN >percentil 95 (p95) entre las semanas 11 y 14, evaluados en nuestro centro. En los 61 que resultaron eu-ploides, se estudió la incidencia de anomalías estructurales diagnosticadas tanto prenatalmente como tras el nacimiento, así como las pérdidas fetales anteparto. De estos fetos, nacieron sanos el 80% cuando la TN estaba entre p95 y 3,4 mm, el 50% con TN entre 3,5 y 4,4 mm, el 30% con TN entre 4,5 y 5,4 mm, y el 18% con TN > 5,5 mm. Entre los 4 recién nacidos euploides con patología, hubo 3 con cardiopatía. Conclusión: La presencia de TN aumentada entre las 11 -14 semanas en fetos euploides se asocia a un incremento del riesgo de anomalías estructurales mayores, principalmente cardiacas. La prevalencia de malformaciones aumenta significativamente con TN >3,5 mm, y el pronóstico gestacional adverso empeora conforme aumenta la medida de la TN.Background: Ultrasound scan has a main role at the 11-14 weeks screening for chromosomal abnormalities. The measurement of nuchal translucency (NT) thickness is a widespread stablished method to achieve this target. Objective: To assess retrospectively the outcome of fetuses with increased nuchal translucency and normal karyotype. Method: Data were collected from 104 fetuses with NT > 95th percentile at 11 to 14 weeks of gestation, followed in our institution. The sixty one euploid fetuses were studied in order to determine the incidence of structural abnormalities, diagnosed either before or after delivery, as well as antenatal fetal loss. Among these fetuses, there were no malformations at birth in 80% for NT between the 95th percentile and 3.4 mm; 50% for NT between 3.5 and 4.4 mm; 30% for NT of 4.5-5.4 mm; and 18% for NT > 5.5 mm. There were 4 euploid newborns with some kind of structural defect at birth, 3 of them presented a cardiac malformation. Conclusion: The presence of increased NT at 11-14 weeks scan in euploid fetuses it's associated with a higher risk of major structural abnormalities, mainly cardiac ones. The prevalence of malformations is significantly increased for NT > 3.5 mm, and the adverse perinatal outcome is directly associated with the thickness of NT.

Objectives: To compare the performance of three sonographic techniques, the 'reverse-face', 'flipped-face' and 'oblique-face' methods, for visualizing the hard and soft palate in diagnosing cleft lip and palate (CLP). Methods: A total of 60 fetuses (10 with CLP) with a gestational age ranging from 20 to 33 weeks were examined. We compared visualization of the secondary palate with the previously described reverse-face and flipped-face methods (the latter modified by us) and the oblique-face method developed by us using Oblique View imaging technology. Results: Among the 10 fetuses with CLP the defect involved the lip, alveolus and secondary palate in seven, and the primary palate only in the remaining three. The upper lip and alveolar ridge were well visualized in all cases with all three methods. Involvement of the hard palate was diagnosed correctly in 71% (5/7) of the cases using the reverse-face view, in 86% (6/7) with the flipped-face view, and in 100% (7/7) with the oblique-face view; the hard palate was correctly found to be intact in 78%, 84% and 86%, respectively, of the 50 normal fetuses examined with each view. Involvement of the soft palate was diagnosed correctly in only one of the seven fetuses with defects of the secondary palate in flipped-face and oblique-face views, and was correctly considered intact in only 16% of normal fetuses in flipped-face view and in 26% in oblique-face images. Conclusions: Accurate visualization of the soft palate requires an excellent initially acquired volume, fluid between the fetal tongue and palate, and curving of the plane to follow the structure of the palate. The oblique-face or flipped-face views make it possible to visualize the soft palate well in selected cases. [ABSTRACT FROM AUTHOR]

An abstract of the article "Diagnosis of fetal orofacial clefts in the first trimester: a three-dimensional (3D) ultrasound study," by P. Martinez-Ten and colleagues is presented.

In this paper, the scientific societies SEGO, SEQC ML and AEDP provide a series of consensus-based recommendations for prenatal screening and diagnosis of genetic abnormalities. A set of evaluation indicators are also proposed as a means to improve the quality of the biochemical, ultrasound, and genetic processes involved in prenatal screening and diagnosis of genetic anomalies. Some recommendations are also proposed in relation to invasive prenatal diagnostic procedures, more specifically regarding sample collection and genetic testing. The purpose of this proposal is to unify performance criteria and quality indicators at national level, with audits performed on a regular basis. It is strongly recommended that a national prenatal screening strategy be established and provided with the resources necessary to evaluate the performance of quality indicators and diagnostic procedures under the supervision of health authorities. Protocols should be revised on a regular basis to consider the incorporation of new cost-effective technologies., Competing Interests: Competing interests: Authors state no conflict of interest., (© 2020 Belén Prieto et al., published by De Gruyter, Berlin/Boston.)