000112449 001__ 112449 000112449 005__ 20240319080951.0 000112449 0247_ $$2doi$$a10.3390/jpm12050762 000112449 0248_ $$2sideral$$a128523 000112449 037__ $$aART-2022-128523 000112449 041__ $$aeng 000112449 100__ $$aDieste-Pérez, Peña$$uUniversidad de Zaragoza 000112449 245__ $$aPersonalized Model to Predict Small for Gestational Age at Delivery Using Fetal Biometrics, Maternal Characteristics, and Pregnancy Biomarkers: A Retrospective Cohort Study of Births Assisted at a Spanish Hospital 000112449 260__ $$c2022 000112449 5060_ $$aAccess copy available to the general public$$fUnrestricted 000112449 5203_ $$aSmall for gestational age (SGA) is defined as a newborn with a birth weight for gestational age < 10th percentile. Routine third-trimester ultrasound screening for fetal growth assessment has detection rates (DR) from 50 to 80%. For this reason, the addition of other markers is being studied, such as maternal characteristics, biochemical values, and biophysical models, in order to create personalized combinations that can increase the predictive capacity of the ultrasound. With this purpose, this retrospective cohort study of 12,912 cases aims to compare the potential value of third-trimester screening, based on estimated weight percentile (EPW), by universal ultrasound at 35–37 weeks of gestation, with a combined model integrating maternal characteristics and biochemical markers (PAPP-A and β-HCG) for the prediction of SGA newborns. We observed that DR improved from 58.9% with the EW alone to 63.5% with the predictive model. Moreover, the AUC for the multivariate model was 0.882 (0.873–0.891 95% C.I.), showing a statistically significant difference with EPW alone (AUC 0.864 (95% C.I.: 0.854–0.873)). Although the improvements were modest, contingent detection models appear to be more sensitive than third-trimester ultrasound alone at predicting SGA at delivery. 000112449 536__ $$9info:eu-repo/grantAgreement/ES/DGA/E46-20R$$9info:eu-repo/grantAgreement/ES/MICINN/PID2020-116873GB-I00 000112449 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/ 000112449 590__ $$a3.4$$b2022 000112449 592__ $$a0.665$$b2022 000112449 591__ $$aMEDICINE, GENERAL & INTERNAL$$b67 / 169 = 0.396$$c2022$$dQ2$$eT2 000112449 593__ $$aMedicine (miscellaneous)$$c2022$$dQ2 000112449 591__ $$aHEALTH CARE SCIENCES & SERVICES$$b42 / 106 = 0.396$$c2022$$dQ2$$eT2 000112449 594__ $$a2.6$$b2022 000112449 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000112449 700__ $$0(orcid)0000-0001-9585-0187$$aSavirón-Cornudella, Ricardo$$uUniversidad de Zaragoza 000112449 700__ $$0(orcid)0000-0003-4720-8231$$aTajada-Duaso, Mauricio$$uUniversidad de Zaragoza 000112449 700__ $$0(orcid)0000-0002-2801-416X$$aPérez-López, Faustino R. 000112449 700__ $$0(orcid)0000-0002-9048-121X$$aCastán-Mateo, Sergio$$uUniversidad de Zaragoza 000112449 700__ $$0(orcid)0000-0002-3007-302X$$aSanz, Gerardo 000112449 700__ $$0(orcid)0000-0002-6474-2252$$aEsteban, Luis Mariano$$uUniversidad de Zaragoza 000112449 7102_ $$12007$$2265$$aUniversidad de Zaragoza$$bDpto. Métodos Estadísticos$$cÁrea Estadís. Investig. Opera. 000112449 7102_ $$11003$$2027$$aUniversidad de Zaragoza$$bDpto. Anatom.Histolog.Humanas$$cArea Anatom.Embriol.Humana 000112449 7102_ $$11013$$2645$$aUniversidad de Zaragoza$$bDpto. Cirugía$$cÁrea Obstetricia y Ginecología 000112449 773__ $$g12, 5 (2022), 762 [12 pp.]$$pJ. pers. med.$$tJournal of Personalized Medicine$$x2075-4426 000112449 8564_ $$s1788892$$uhttps://zaguan.unizar.es/record/112449/files/texto_completo.pdf$$yVersión publicada 000112449 8564_ $$s2907895$$uhttps://zaguan.unizar.es/record/112449/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada 000112449 909CO $$ooai:zaguan.unizar.es:112449$$particulos$$pdriver 000112449 951__ $$a2024-03-18-13:03:10 000112449 980__ $$aARTICLE