Browsing by Author "De Paco Matallana, C."
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Item New approach for estimating risk of miscarriage after chorionic villus sampling.(Ultrasound in Obstetrics & Gynecology, 2020) Gil Mira, María del Mar; Santacruz Martín, Belén; De Paco Matallana, C.Objective To estimate the risk of miscarriage associated with chorionic villus sampling (CVS). Methods This was a retrospective cohort study of women attending for routine ultrasound examination at 11 + 0 to 13 + 6 weeks' gestation at one of eight fetal-medicine units in Spain, Belgium and Bulgaria, between July 2007 and June 2018. Two populations were included: (1) all singleton pregnancies undergoing first-trimester assessment at Hospital Clínico Universitario Virgen de la Arrixaca in Murcia, Spain, that did not have CVS (non-CVS group); and (2) all singleton pregnancies that underwent CVS following first-trimester assessment at one of the eight participating centers (CVS group). We excluded pregnancies diagnosed with genetic anomalies or major fetal defects before or after birth, those that resulted in termination and those that underwent amniocentesis later in pregnancy. We used propensity score (PS) matching analysis to estimate the association between CVS and miscarriage. We compared the risk of miscarriage of the CVS and non-CVS groups after PS matching (1:1 ratio). This procedure creates two comparable groups balancing the maternal and pregnancy characteristics that are associated with CVS, in a similar way to that in which randomization operates in a randomized clinical trial. Results The study population consisted of 22 250 pregnancies in the non-CVS group and 3613 in the CVS group. The incidence of miscarriage in the CVS group (2.1%; 77/3613) was significantly higher than that in the non-CVS group (0.9% (207/22 250); P < 0.0001). The PS algorithm matched 2122 CVS with 2122 non-CVS cases, of which 40 (1.9%) and 55 (2.6%) pregnancies in the CVS and non-CVS groups, respectively, resulted in a miscarriage (odds ratio (OR), 0.72 (95% CI, 0.48–1.10); P = 0.146). We found a significant interaction between the risk of miscarriage following CVS and the risk of aneuploidy, suggesting that the effect of CVS on the risk of miscarriage differs depending on background characteristics. Specifically, when the risk of aneuploidy is low, the risk of miscarriage after CVS increases (OR, 2.87 (95% CI, 1.13–7.30)) and when the aneuploidy risk is high, the risk of miscarriage after CVS is paradoxically reduced (OR, 0.47 (95% CI, 0.28–0.76)), presumably owing to prenatal diagnosis and termination of pregnancies with major aneuploidies that would otherwise have resulted in spontaneous miscarriage. For example, in a patient in whom the risk of aneuploidy is 1 in 1000 (0.1%), the risk of miscarriage after CVS will increase to 0.3% (0.2 percentage points higher). Conclusions The risk of miscarriage in women undergoing CVS is about 1% higher than that in women who do not have CVS, although this excess risk is not solely attributed to the invasive procedure but, to some extent, to the demographic and pregnancy characteristics of the patients. After accounting for these risk factors and confining the analysis to low-risk pregnancies, CVS seems to increase the risk of miscarriage by about three times above the patient's background risk. Although this is a substantial increase in relative terms, in pregnancies without risk factors for miscarriage, the risk of miscarriage after CVS remains low and similar to, or slightly higher than, that in the general population. © 2020 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.Item Performance of first-trimester combined screening for preterm pre-eclampsia: findings from cohort of 10 110 pregnancies in Spain.(Ultrasound in Obstetrics & Gynecology, 2023) Gómez, DC; De Paco Matallana, C.; Rolle, V.; Valiño, N; Revello, R; Adiego, B; Mendoza, M; Molina, FS; Carrillo, MP; Delgado, JL; Wright, A.; Santacruz Martín, Belén; Gil Mira, María del MarObjective 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.Item Risk of fetal loss after chorionic villus sampling in twin pregnancy derived from propensity score matching analysis.(Ultrasound in Obstetrics & gynecology, 2021) Gil Mira, María del Mar; Rodríguez Fernández, Miguel; Elger, Tania; Akolekar, R.; Syngelaki, A.; De Paco Matallana, C.; Molina, ,F. S.; Gallardo Arocena, M.; Chaveeva, P.; Persico, N.; Accurti, V.; Kagan, K. O.; Prodan, N.; Cruz, J.; Nicolaides, K. H.Objective To estimate the risk of fetal loss associated with chorionic villus sampling (CVS) in twin pregnancy, using propensity score analysis. Methods This was a multicenter cohort study of women with twin pregnancy undergoing ultrasound examination at 11–13 weeks' gestation, performed in eight fetal medicine units in which the leadership were trained at the Harris Birthright Research Centre for Fetal Medicine in London, UK, and in which the protocols for screening, invasive testing and pregnancy management are similar. The risk of death of at least one fetus was compared between pregnancies that had and those that did not have CVS, after propensity score matching (1:1 ratio). This procedure created two comparable groups by balancing the maternal and pregnancy characteristics that lead to CVS being performed, similar to how randomization operates in a randomized clinical trial. Results The study population of 8581 twin pregnancies included 445 that had CVS. Death of one or two fetuses at any stage during pregnancy occurred in 11.5% (51/445) of pregnancies in the CVS group and in 6.3% (515/8136) in the non-CVS group (P < 0.001). The propensity score algorithm matched 258 cases that had CVS with 258 non-CVS cases; there was at least one fetal loss in 29 (11.2%) cases in the CVS group and in 35 (13.6%) cases in the matched non-CVS group (odds ratio (OR), 0.81; 95% CI, 0.48–1.35; P = 0.415). However, there was a significant interaction between the risk of fetal loss after CVS and the background risk of fetal loss; when the background risk was higher, the risk of fetal loss after CVS decreased (OR, 0.46; 95% CI, 0.23–0.90), while, in pregnancies with a lower background risk of fetal loss, the risk of fetal loss after CVS increased (OR, 2.45; 95% CI, 0.95–7.13). The effects were statistically significantly different (P-value of the interaction = 0.005). For a pregnancy in which the background risk of fetal loss was about 6% (the same as in our non-CVS population), there was no change in the risk of fetal loss after CVS, but, when the background risk was more than 6%, the posterior risk was paradoxically reduced, and when the background risk was less than 6%, the posterior risk increased exponentially; for example, if the background risk of fetal loss was 2.0%, the relative risk was 2.8 and the posterior risk was 5.6%. Conclusion In twin pregnancy, after accounting for the risk factors that lead to both CVS and spontaneous fetal loss and confining the analysis to pregnancies at lower prior risk, CVS seems to increase the risk of fetal loss by about 3.5% above the patient's background risk. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.Item Risk of miscarriage after chorionic villus sampling.(Ultrasound in Obstetrics and Gynecology, 2020) Gil Mira, María del Mar; Molina, F. S.; Rodríguez Fernández, M.; Delgado, J. L.; Carrillo, M. P.; Jani, J.; Plasencia, W.; Stratieva, V.; Maíz, N.; Carretero, P.; Lismonde, A.; Chaveeva, P.; Burgos, J.; Santacruz Martín, Belén; Zamora, J.; De Paco Matallana, C.Objective To estimate the risk of miscarriage associated to chorionic villus sampling (CVS). Methods This was a retrospective cohort study performed in eight fetal‐medicine units in Spain, Belgium and Bulgaria. Two populations were included: first, all singleton pregnancies attending to their first‐trimester assessment in Murcia, Spain, and second, all singleton pregnancies having a CVS following first‐trimester assessment at any of the participating centers. We used propensity score matching analysis to estimate the association between CVS and miscarriage. We compared risks of miscarriage of CVS and non‐CVS groups after propensity score matching (1:1 ratio). This procedure creates two comparable groups balancing the maternal and pregnancy characteristics that lead to CVS, in a similar way in which randomization operates in a randomized clinical trial. Results The study population consisted of 22,250 participants in the non‐CVS group and 3,613 in the CVS group. The incidence of miscarriage in the CVS group was 2.1% (77/3,613), which was significantly higher than the 0.9% (207/22,250) in the non‐CVS group (p <0.001). The propensity score algorithm matched 2,122 CVS cases with 2,122 non‐CVS cases including 40 (1.9%) and 55 (2.6%) miscarriages in the CVS and non‐CVS groups, respectively (OR 0.72 [95% CI 0.48 to 1.10]; p = 0.146). However, we found a significant interaction between the CVS risk of miscarriage and the risk of aneuploidies, suggesting a different effect of the CVS for different baseline characteristics in such a way that, when the risk of aneuploidies is low, the risk after CVS increases (OR 2.87 [95% CI 1.13 to 7.30]) but when the risk is high, the risk after CVS is paradoxically reduced (OR 0.47 [95% CI 0.28 to 0.76]), presumably due to prenatal diagnosis and termination of major aneuploidies that would have otherwise resulted in spontaneous miscarriage. Conclusions The risk of miscarriage in women having a CVS is about 1% higher than in women without CVS, although this excess risk is not entirely due to the invasive procedure but to some extent the demographic and pregnancy characteristics of the patient undergoing CVS. After accounting for these risk factors and confining the analysis to low‐risk pregnancies, CVS seems to increase the risk of miscarriage about three times above the patient’s background‐risk. Although this is a substantial increase in relative terms, in pregnancies without risk factors, the risk of miscarriage after CVS will still remain low and similar to or slightly higher than that of the general population. For example, if her risk of aneuploidy is 1 in a 1,000 (0.1%), her risk of miscarriage after CVS will increase to 0.3% (0.2% higher).Item Validation of machine-learning model for first-trimester prediction of pre-eclampsia using cohort from PREVAL study.(Ultrasound in Obstetrics & Gynecology, 2024) Gil Mira, María del Mar; Cuenca Gómez, D.; Rolle, V.; Pertegal, M.; Valiño, N.; Revello, R.; Adiego, B.; Mendoza, M.; Molina, F. S.; Santacruz Martín, Belén; Ansbacher-Feldman, Z.; Meiri, H.; Martín Alonso, R.; Louzoun, Y.; De Paco Matallana, C.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.