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First-trimester screening model for small-for-gestational-age using maternal clinical characteristics, serum screening markers, and placental volume: prospective cohort study

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dc.contributor.author정인경-
dc.date.accessioned2023-03-03T03:03:21Z-
dc.date.available2023-03-03T03:03:21Z-
dc.date.issued2022-12-
dc.identifier.issn1476-7058-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/192972-
dc.description.abstractObjective: To examine predictive value of first trimester placental volume, maternal clinical characteristics, and serum biomarkers in predicting small-for-gestational-age (SGA) singleton pregnancy. Methods: We conducted a prospective study to determine whether SGA is associated with maternal clinical factors. Between November 2016 to May 2018, 351 women were enrolled. We included pregnant women who underwent an integrated test for aneuploidy screening. Placental volume, maternal clinical characteristics, and maternal serum pregnancy-associated plasma protein A (PAPP-A) levels in the first trimester (at 10+0-13+6 weeks) and maternal serum biomarkers after 15+0-22+6 weeks were measured. We measured the width, height, and thickness of the placenta and calculated the placental volume using an established mathematical formula; then, we analyzed the association between SGA at delivery, estimated placental volume (EPV), maternal clinical characteristics, and maternal serum biomarkers by multiple logistic regression analysis. Results: In this study, 12.3% (43/351) neonates were delivered before 37 weeks of gestation, and the birth weight of 23.6% (83/351) was below the 10th percentile according to gestational age. On multivariate logistic regression, the MSAFP multiples of the median (MoM) showed the strongest association with SGA in singleton pregnancy (p < .01), and the PAPP-A MoM showed a weaker association in the multiple logistic regression than in the univariate regression (p = .0073 and .0068, respectively). Our prediction model using maternal age, maternal smoking, PAPP-A, and EPV achieved an area under the curve of 0.668 in singleton pregnancy. Conclusion: During the first trimester, maternal clinical characteristics, serum biomarkers, and EPV may be used for predicting the risk of SGA in singleton pregnancy.-
dc.description.statementOfResponsibilityrestriction-
dc.languageEnglish-
dc.publisherInforma Healthcare-
dc.relation.isPartOfJOURNAL OF MATERNAL-FETAL & NEONATAL MEDICINE-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.subject.MESHBiomarkers-
dc.subject.MESHFemale-
dc.subject.MESHFetal Growth Retardation / diagnosis-
dc.subject.MESHHumans-
dc.subject.MESHInfant, Newborn-
dc.subject.MESHInfant, Newborn, Diseases*-
dc.subject.MESHInfant, Small for Gestational Age-
dc.subject.MESHPlacenta / metabolism-
dc.subject.MESHPlacenta Growth Factor-
dc.subject.MESHPregnancy-
dc.subject.MESHPregnancy Trimester, First-
dc.subject.MESHPregnancy-Associated Plasma Protein-A* / metabolism-
dc.subject.MESHProspective Studies-
dc.titleFirst-trimester screening model for small-for-gestational-age using maternal clinical characteristics, serum screening markers, and placental volume: prospective cohort study-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Biomedical Systems Informatics (의생명시스템정보학교실)-
dc.contributor.googleauthorYoung Ran Kim-
dc.contributor.googleauthorGoeun Park-
dc.contributor.googleauthorEun Hui Joo-
dc.contributor.googleauthorJi Hyon Jang-
dc.contributor.googleauthorEun Hee Ahn-
dc.contributor.googleauthorSang Hee Jung-
dc.contributor.googleauthorInkyung Jung-
dc.contributor.googleauthorHee Young Cho-
dc.identifier.doi10.1080/14767058.2021.1875434-
dc.contributor.localIdA03693-
dc.relation.journalcodeJ01577-
dc.identifier.eissn1476-4954-
dc.identifier.pmid33472455-
dc.identifier.urlhttps://www.tandfonline.com/doi/full/10.1080/14767058.2021.1875434-
dc.subject.keywordSmall for gestational age-
dc.subject.keywordestimated placenta volume-
dc.subject.keywordmaternal serum biomarker-
dc.contributor.alternativeNameJung, In Kyung-
dc.contributor.affiliatedAuthor정인경-
dc.citation.volume35-
dc.citation.number25-
dc.citation.startPage5149-
dc.citation.endPage5154-
dc.identifier.bibliographicCitationJOURNAL OF MATERNAL-FETAL & NEONATAL MEDICINE, Vol.35(25) : 5149-5154, 2022-12-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers

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