Crovetto F, Triunfo S, Crispi F, Rodriguez-Sureda V, Dominguez C, Figueras F, Gratacos E
BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), IDIBAPS, University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain.
Department of Obstetrics and Gynecology, Fondazione Ca' Granda, Ospedale Maggiore Policlinico, Università degli Studi di Milano, Milan, Italy.
Ultrasound Obstet Gynecol. 2017 Mar;49(3):349-356. doi: 10.1002/uog.15919.
To assess the ability of integrated first-trimester screening, combining maternal characteristics and biophysical and biochemical markers, to predict delivery of a small-for-gestational-age (SGA) neonate, and compare this with its ability to predict fetal growth restriction (FGR).
This was a prospective cohort study of singleton pregnancies undergoing routine first-trimester screening. SGA was defined as birth weight (BW) < 10 percentile and FGR was defined as an ultrasound estimated fetal weight < 10 percentile plus Doppler abnormalities, or BW < 3 percentile. Logistic regression-based predictive models were developed for predicting SGA and FGR. Models incorporated the a-priori risk from maternal characteristics, and mean arterial pressure, uterine artery Doppler, placental growth factor and soluble fms-like tyrosine kinase-1.
In total, 9150 births were included. Of these, 979 (10.7%) qualified for a postnatal diagnosis of SGA and 462 (5.0%) for a prenatal diagnosis of FGR. For predicting SGA, the model achieved a detection rate of 35% for a false-positive rate (FPR) of 5% and 42% for a 10% FPR. The model's performance was significantly higher for predicting FGR (P < 0.001), with detection rates of 59% and 67%, for a FPR of 5% and 10%, respectively.
The predictive performance of first-trimester screening for cases with growth impairment by a combination of maternal characteristics and biophysical and biochemical markers is improved significantly when a prenatal and strict definition of FGR is used rather than a postnatal definition based on BW. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.
评估整合孕早期筛查(结合孕妇特征以及生物物理和生化标志物)预测小于胎龄儿(SGA)新生儿分娩的能力,并将其与预测胎儿生长受限(FGR)的能力进行比较。
这是一项对接受常规孕早期筛查的单胎妊娠进行的前瞻性队列研究。SGA定义为出生体重(BW)低于第10百分位数,FGR定义为超声估计胎儿体重低于第10百分位数加多普勒异常,或BW低于第3百分位数。建立了基于逻辑回归的预测模型来预测SGA和FGR。模型纳入了来自孕妇特征的先验风险,以及平均动脉压、子宫动脉多普勒、胎盘生长因子和可溶性fms样酪氨酸激酶-1。
总共纳入了9150例分娩。其中,979例(10.7%)符合SGA产后诊断标准,462例(5.0%)符合FGR产前诊断标准。对于预测SGA,该模型在假阳性率(FPR)为5%时检测率为35%,在FPR为10%时检测率为42%。该模型在预测FGR方面的表现显著更高(P<0.001),在FPR为5%和10%时,检测率分别为59%和67%。
当使用FGR的产前严格定义而非基于BW的产后定义时,通过结合孕妇特征以及生物物理和生化标志物进行的孕早期筛查对生长受限病例的预测性能显著提高。版权所有©2016国际妇产科超声学会。由约翰·威利父子有限公司出版。