Prediction of small for gestational age neonates: screening by maternal factors, fetal biometry, and biomarkers at 35-37 weeks' gestation
Prediction of small for gestational age neonates: screening by maternal factors, fetal biometry, and biomarkers at 35-37 weeks' gestation
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DOI：
10.1016/j.ajog.2019.01.227
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发表时间：
2019-05-01
影响因子：
9.8
通讯作者：
Nicolaides, Kypros H.
中科院分区：
文献类型：
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作者：
Ciobanu, Anca;Rouvali, Angeliki;Nicolaides, Kypros H.
背景：小于胎龄儿(SGA)围产期死亡和发病的风险增加；然而，如果在产前发现这种情况，风险可以大大降低，因为在这种情况下，可以进行密切的监测和适当的分娩时间和及时的新生儿护理。传统的识别SGA胎儿妊娠的方法是孕妇腹部触诊和联合眼底高度的连续测量，但这种方法的检出率不到30%。孕晚期超声胎儿生物测量法筛查SGA的效果较好；在妊娠30-34周筛查发现约80%的SGA新生儿早产，但仅有50%的足月分娩新生儿筛查阳性，筛查阳性率为10%。有证据表明，妊娠36周的常规超声检查对预测SGA新生儿的出生比32周的检查更有效。目的：探讨妊娠35(+0)-36(+6)周的超声估计胎儿体重(EFW)和胎盘受损的生物标志物在预测SGA新生儿出生方面的潜在价值。材料和方法：将19209例孕35(+0)-36(+6)周的单胎妊娠筛查数据分为训练组和验证组。使用训练数据集建立多变量Logistic回归分析模型，以确定子宫动脉搏动指数(UTA-PI)、脐动脉搏动指数(UA-PI)、胎儿大脑中动脉搏动指数(MCA-PI)、母体血清胎盘生长因子(PlGF)和可溶性FMS样酪氨酸激酶-1(SFlt)在预测SGA新生儿分娩时是否会改善母体因素和EFW的表现。结果：首先，在训练数据集中，在SGA组中，与出生体重在>；=10%组相比，PlGF和MCA-PI的中位数(MOM)降低，而UTA-PI、UA-PI和sFlt增加。第二，多元回归分析表明，在预测SGA中
BACKGROUND: Small for gestational age (SGA) neonates are at increased risk for perinatal mortality and morbidity; however, the risks can be substantially reduced if the condition is identified prenatally, because in such cases close monitoring and appropriate timing of delivery and prompt neonatal care can be undertaken. The traditional approach of identifying pregnancies with SGA fetuses is maternal abdominal palpation and serial measurements of symphysial-fundal height, but the detection rate of this approach is less than 30%. A higher performance of screening for SGA is achieved by sonographic fetal biometry during the third trimester; screening at 30-34 weeks' gestation identifies about 80% of SGA neonates delivering preterm but only 50% of those delivering at term, at a screen-positive rate of 10%. There is some evidence that routine ultrasound examination at 36 weeks' gestation is more effective than that at 32 weeks in predicting birth of SGA neonates.OBJECTIVE: To investigate the potential value of maternal characteristics and medical history, sonographically estimated fetal weight (EFW) and biomarkers of impaired placentation at 35(+0)-36(+6) weeks' gestation in the prediction of delivery of SGA neonates.MATERIALS AND METHODS: A dataset of 19,209 singleton pregnancies undergoing screening at 35(+0)-36(+6) weeks' gestation was divided into a training set and a validation set. The training dataset was used to develop models from multivariable logistic regression analysis to determine whether the addition of uterine artery pulsatility index (UtA-PI), umbilical artery PI (UA-PI), fetal middle cerebral artery PI (MCA-PI), maternal serum placental growth factor (PlGF) and soluble fms-like tyrosine kinase-1 (sFLT) would improve the performance of maternal factors and EFW in the prediction of delivery of SGA neonates. The models were then tested in the validation dataset to assess performance of screening.RESULTS: First, in the training dataset, in the SGA group, compared to those with birthweight in >= 10th percentile, the median multiple of the median (MoM) values of PlGF and MCA-PI were reduced, whereas UtA-PI, UA-PI, and sFLT were increased. Second, multivariable regression analysis demonstrated that in the prediction of SGA in