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Background: The current version of the Fetal Medicine Foundation competing risks model for preeclampsia prediction has not been previously validated in Brazil., Objective: This study aimed (1) to validate the Fetal Medicine Foundation combined algorithm for the prediction of preterm preeclampsia in the Brazilian population and (2) to describe the accuracy and calibration of the Fetal Medicine Foundation algorithm when considering the prophylactic use of aspirin by clinical criteria., Study Design: This was a cohort study, including consecutive singleton pregnancies undergoing preeclampsia screening at 11 to 14 weeks of gestation, examining maternal characteristics, medical history, and biophysical markers between October 2010 and December 2018 in a university hospital in Brazil. Risks were calculated using the 2018 version of the algorithm available on the Fetal Medicine Foundation website, and cases were classified as low or high risk using a cutoff of 1/100 to evaluate predictive performance. Expected and observed cases with preeclampsia according to the Fetal Medicine Foundation-estimated risk range (≥1 in 10; 1 in 11 to 1 in 50; 1 in 51 to 1 in 100; 1 in 101 to 1 in 150; and <1 in 150) were compared. After identifying high-risk pregnant women who used aspirin, the treatment effect of 62% reduction in preterm preeclampsia identified in the Combined Multimarker Screening and Randomized Patient Treatment with Aspirin for Evidence-Based Preeclampsia Prevention trial was used to evaluate the predictive performance adjusted for the effect of aspirin. The number of potentially unpreventable cases in the group without aspirin use was estimated., Results: Among 2749 pregnancies, preterm preeclampsia occurred in 84 (3.1%). With a risk cutoff of 1/100, the screen-positive rate was 25.8%. The detection rate was 71.4%, with a false positive rate of 24.4%. The area under the curve was 0.818 (95% confidence interval, 0.773-0.863). In the risk range ≥1/10, there is an agreement between the number of expected cases and the number of observed cases, and in the other ranges, the predicted risk was lower than the observed rates. Accounting for the effect of aspirin resulted in an increase in detection rate and positive predictive values and a slight decrease in the false positive rate. With 27 cases of preterm preeclampsia in the high-risk group without aspirin use, we estimated that 16 of these cases of preterm preeclampsia would have been avoided if this group had received prophylaxis., Conclusion: In a high-prevalence setting, the Fetal Medicine Foundation algorithm can identify women who are more likely to develop preterm preeclampsia. Not accounting for the effect of aspirin underestimates the screening performance., (© 2024 The Authors.)

Background: Numerous fetal growth curves have been developed from various subpopulations and geographic locations worldwide., Objective: To determine the birthweight standard at the Maternity School and compare it to currently used standards in the clinical practice services., Study Design: Cross-sectional, observational, and descriptive study. Data from infants born between 2011 and 2016 were collected from the Maternity School Hospital of the Federal University of Rio de Janeiro to define the 10th, 25th, 50th, 75th, and 90th percentiles of the birthweight by gestational age. It was determined the performance of the INTERGROWTH-21st, Fenton, Alexander, and Lubchenco for the Maternity School standards., Results: After the 33rd week of pregnancy, the INTERGROWTH standard was similar to the local standard for small-for-gestational-age infants and Fenton for large-for-gestational-age infants at Maternity School Hospital. The INTERGROWTH standard was found to be inadequate to classify small-for-gestational-age infants, which are babies at major risk for morbidity and mortality at the onset of the 33rd week of pregnancy., Conclusion: It was possible to define reference values for birthweight for the maternal school hospital considering at least 33 weeks of pregnancy with a 95% confidence interval. The comparison of the INTERGROWTH, Fenton, Alexander, and Lubchenko standards to the maternal school hospital curve showed that the Fenton curve was the most suitable for the diagnosis of small for gestational age., (© 2024 The Authors.)

Background: FMF2012 is an algorithm developed by the Fetal Medicine Foundation (FMF) to predict pre-eclampsia on the basis of maternal characteristics combined with biophysical and biochemical markers. Afro-Caribbean ethnicity is the second risk factor, in magnitude, found in populations tested by FMF, which was not confirmed in a Brazilian setting., Objective: This study aimed to analyze the performance of pre-eclampsia prediction software by customization of maternal ethnicity., Methods: This was a cross-sectional observational study, with secondary evaluation of data from FMF first trimester screening tests of singleton pregnancies. Risk scores were calculated from maternal characteristics and biophysical markers, and they were presented as the risk for early pre-eclampsia (PE34) and preterm pre-eclampsia (PE37). The following steps were followed: (1) identification of women characterized as black ethnicity; (2) calculation of early and preterm pre-eclampsia risk, reclassifying them as white, which generated a new score; (3) comparison of the proportions of women categorized as high risk between the original and new scores; (4) construction of the receiver operator characteristic curve; (5) calculation of the area under the curve, sensitivity, and false positive rate; and (6) comparison of the area under the curve, sensitivity, and false positive rate of the original with the new risk by chi-square test., Results: A total of 1531 cases were included in the final sample, with 219 out of 1531 cases (14.30; 95% CI 12.5-16.0) and 182 out of 1531 cases (11.88%; 95% CI 10.3-13.5) classified as high risk for pre-eclampsia development, originally and after recalculating the new risk, respectively. The comparison of FMF2012 predictive model performance between the originally estimated risks and the estimated new risks showed that the difference was not significant for sensitivity and area under the curve, but it was significant for false positive rate., Conclusions: We conclude that black ethnicity classification of Brazilian pregnant women by the FMF2012 algorithm increases the false positive rate. Suppressing ethnicity effect did not improve the test sensitivity. By modifying demographic characteristics, it is possible to improve some performance aspects of clinical prediction tests., (©Karina Bilda De Castro Rezende, Antonio José Ledo Alves Cunha, Joffre Amim Jr, Wescule De Moraes Oliveira, Maria Eduarda Belloti Leão, Mariana Oliveira Alves Menezes, Ana Alice Marques Ferraz De Andrade Jardim, Rita Guérios Bornia. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.11.2019.)