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    Prediction models for early fetal growth restriction (FGR) have been exhibited in many researches. However, prediction models for late FGR are limited. Late-onset FGR is easy to miss clinically because of its insidious onset. This study aimed to develop a simple combined first- and second-trimester prediction model for screening late-onset FGR in fetuses. This retrospective study included 2746 women who had singleton pregnancies and received routine ultrasound scans as training dataset. Late FGR is that diagnosed >32 weeks. Multivariate logistic regression was used to develop a prediction model. One hundred and twenty-nine fetuses were identified as late-onset FGR. The significant predictors for late-onset FGR were maternal height, weight, and medical history; the first-trimester mean arterial pressure, the second-trimester head circumference/ abdominal circumference ratio; and the second-trimester estimated fetal weight. This model achieved a detection rate (DR........) of 51.6% for late-onset FGR at a 10% false positive rate (FPR) (area under the curve (AUC): 0.80, 95%CI 0.76-0.84). A multivariate model combining first- and second-trimester default tests can detect 51.6% of cases of late-onset FGR at a 10% FPR. Further studies with more screening markers are needed to improve the detection rate. Copyright © 2021 The Authors. Published by Elsevier Masson SAS.. All rights reserved.


    Yan Feng, Haiqing Zheng, Dajun Fang, Shanshan Mei, Wei Zhong, Guanglan Zhang. Prediction of late-onset fetal growth restriction using a combined first- and second-trimester screening model. Journal of gynecology obstetrics and human reproduction. 2022 Feb;51(2):102273

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    PMID: 34813940

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