How do maternal factors impact preeclampsia prediction in Brazilian population?. (3rd April 2019)

• Record Type: Journal Article
• Authors: Rezende, Karina Bilda de Castro; Cunha, Antônio José Ledo Alves da; Pritsivelis, Cristos; Faleiro, Edson Chaves; Amim Junior, Joffre; Bornia, Rita Guérios
• Is Part Of: Journal of maternal-fetal & neonatal medicine. Volume 32:Number 7(2019)
• Page Start: 1051
• Page End: 1056
• Publication Date: 2019-04-03
• Subjects: First trimester screening -- maternal history -- preeclampsia -- risk factors; Obstetrics -- Periodicals; Perinatology -- Periodicals; Infants (Newborn) -- Diseases -- Periodicals; Neonatology -- Periodicals; 618.2
• DOI: 10.1080/14767058.2017.1399115
• Languages: English
• ISSNs: 1476-7058

Abstract

Abstract: Objective: To evaluate the impacts of maternal risk factors described by the Fetal Medicine Foundation's 2012 algorithm (FMF2012) in a Brazilian population. Methods: All singleton pregnancies submitted to first-trimester preeclampsia (PE) screening using the FMF2012 algorithm were considered for study inclusion. Maternal factors, recorded via a patient questionnaire, were described and compared between PE outcome groups. A Gaussian regression model was derived to measure the effects of maternal factors, and to identify factors that contributed significantly ( p < .05) to the alteration of gestational age at delivery, in pregnancies with PE. Results: Of the 1934 cases considered for study inclusion, the final sample consisted of 1531 cases. The sample included 120 (7.8%) cases of PE, of which 26 (1.7%) were preterm PE (PE < 37 weeks) and 11 (0.72%) were early PE (PE < 34 weeks). The PE rate did not differ according to ethnicity, smoking, family history of PE, or use of assisted reproductive technology. Significant differences ( p < .05) between the normal and PE groups in maternal age, maternal weight, previous history of PE, chronic hypertension, and types 1 and 2 diabetes were detected. Conclusions: The significance and magnitude of associations of maternal factors in our sample differed from those incorporated in the FMF2012 model, implying the need to derive a fitted model for our population.