J Miranda1,2, M Rodriguez-Lopez1,2, S Triunfo1,2, M Sairanen3, H Kouru3, M Parra-Saavedra1,4, F Crovetto1,2, F Figueras1,2, F Crispi1,2, E Gratacós1,2. 1. BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine, Hospital Clínic and Hospital Sant Joan de Deu, IDIBAPS, University of Barcelona, Spain. 2. Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain. 3. PerkinElmer, Inc., Turku, Finland. 4. Maternal-Fetal Unit, CEDIFETAL, Centro de Diagnostico de Ultrasonido e Imágenes, CEDIUL, Barranquilla, Colombia.
Abstract
OBJECTIVES: To compare the performance of third-trimester screening, based on estimated fetal weight centile (EFWc) vs a combined model including maternal baseline characteristics, fetoplacental ultrasound and maternal biochemical markers, for the prediction of small-for-gestational-age (SGA) neonates and late-onset fetal growth restriction (FGR). METHODS: This was a nested case-control study within a prospective cohort of 1590 singleton gestations undergoing third-trimester (32 + 0 to 36 + 6 weeks' gestation) evaluation. Maternal baseline characteristics, mean arterial pressure, fetoplacental ultrasound and circulating biochemical markers (placental growth factor (PlGF), lipocalin-2, unconjugated estriol and inhibin A) were assessed in all women who subsequently delivered a SGA neonate (n = 175), defined as birth weight < 10th centile according to customized standards, and in a control group (n = 875). Among SGA cases, those with birth weight < 3rd centile and/or abnormal uterine artery pulsatility index (UtA-PI) and/or abnormal cerebroplacental ratio (CPR) were classified as FGR. Logistic regression predictive models were developed for SGA and FGR, and their performance was compared with that obtained using EFWc alone. RESULTS: In SGA cases, EFWc, CPR Z-score and maternal serum concentrations of unconjugated estriol and PlGF were significantly lower, while mean UtA-PI Z-score and lipocalin-2 and inhibin A concentrations were significantly higher, compared with controls. Using EFWc alone, 52% (area under receiver-operating characteristics curve (AUC), 0.82 (95% CI, 0.77-0.85)) of SGA and 64% (AUC, 0.86 (95% CI, 0.81-0.91)) of FGR cases were predicted at a 10% false-positive rate. A combined screening model including a-priori risk (maternal characteristics), EFWc, UtA-PI, PlGF and estriol (with lipocalin-2 for SGA) achieved a detection rate of 61% (AUC, 0.86 (95% CI, 0.83-0.89)) for SGA cases and 77% (AUC, 0.92 (95% CI, 0.88-0.95)) for FGR. The combined model for the prediction of SGA and FGR performed significantly better than did using EFWc alone (P < 0.001 and P = 0.002, respectively). CONCLUSIONS: A multivariable integrative model of maternal characteristics, fetoplacental ultrasound and maternal biochemical markers modestly improved the detection of SGA and FGR cases at 32-36 weeks' gestation when compared with screening based on EFWc alone.
OBJECTIVES: To compare the performance of third-trimester screening, based on estimated fetal weight centile (EFWc) vs a combined model including maternal baseline characteristics, fetoplacental ultrasound and maternal biochemical markers, for the prediction of small-for-gestational-age (SGA) neonates and late-onset fetal growth restriction (FGR). METHODS: This was a nested case-control study within a prospective cohort of 1590 singleton gestations undergoing third-trimester (32 + 0 to 36 + 6 weeks' gestation) evaluation. Maternal baseline characteristics, mean arterial pressure, fetoplacental ultrasound and circulating biochemical markers (placental growth factor (PlGF), lipocalin-2, unconjugated estriol and inhibin A) were assessed in all women who subsequently delivered a SGA neonate (n = 175), defined as birth weight < 10th centile according to customized standards, and in a control group (n = 875). Among SGA cases, those with birth weight < 3rd centile and/or abnormal uterine artery pulsatility index (UtA-PI) and/or abnormal cerebroplacental ratio (CPR) were classified as FGR. Logistic regression predictive models were developed for SGA and FGR, and their performance was compared with that obtained using EFWc alone. RESULTS: In SGA cases, EFWc, CPR Z-score and maternal serum concentrations of unconjugated estriol and PlGF were significantly lower, while mean UtA-PI Z-score and lipocalin-2 and inhibin A concentrations were significantly higher, compared with controls. Using EFWc alone, 52% (area under receiver-operating characteristics curve (AUC), 0.82 (95% CI, 0.77-0.85)) of SGA and 64% (AUC, 0.86 (95% CI, 0.81-0.91)) of FGR cases were predicted at a 10% false-positive rate. A combined screening model including a-priori risk (maternal characteristics), EFWc, UtA-PI, PlGF and estriol (with lipocalin-2 for SGA) achieved a detection rate of 61% (AUC, 0.86 (95% CI, 0.83-0.89)) for SGA cases and 77% (AUC, 0.92 (95% CI, 0.88-0.95)) for FGR. The combined model for the prediction of SGA and FGR performed significantly better than did using EFWc alone (P < 0.001 and P = 0.002, respectively). CONCLUSIONS: A multivariable integrative model of maternal characteristics, fetoplacental ultrasound and maternal biochemical markers modestly improved the detection of SGA and FGR cases at 32-36 weeks' gestation when compared with screening based on EFWc alone.
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