Prediction of small-for-gestational-age neonates: screening by biophysical and biochemical markers at 30-34 weeks.

Abstract

To investigate the potential value of combined screening by maternal characteristics and medical history (maternal factors), estimated fetal weight (EFW), uterine artery pulsatility index (UtA-PI), mean arterial pressure (MAP) and serum levels of placental growth factor (PlGF) and soluble fms-like tyrosine kinase-1 (sFlt-1) at 30-34 weeks' gestation in the prediction of delivery of small-for-gestational-age (SGA) neonates, in the absence of pre-eclampsia (PE). This was a screening study in 9472 singleton pregnancies at 30-34 weeks' gestation, comprising 469 that delivered SGA neonates and 9003 cases unaffected by SGA, PE or gestational hypertension. Multivariable logistic regression analysis was used to determine if UtA-PI, MAP and serum PlGF or sFlt-1, individually or in combination, improved the prediction of SGA neonates provided from screening by maternal factors and EFW. Compared to the normal group, mean log10 multiples of the median (MoM) values of UtA-PI, MAP and serum sFlt-1 were significantly higher and log10 MoM PlGF was lower in the SGA group. Multivariable logistic regression analysis demonstrated that in the prediction of SGA neonates with a birth weight < 5(th) percentile, delivering < 5 weeks and ≥ 5 weeks after assessment, there were significant independent contributions from maternal factors, EFW, UtA-PI, MAP, and serum PlGF and sFlt-1, but the best performance was provided by a combination of maternal factors, EFW, UtA-PI, MAP and serum PlGF, excluding sFlt-1. Combined screening predicted, at a 10% false-positive rate, 89%, 94%, 96% of SGA neonates delivering at 32-36 weeks' gestation with birth weight < 10(th) , < 5(th) and < 3(rd) percentiles, respectively; the respective detection rates of combined screening for SGA neonates delivering ≥ 37 weeks were 57%, 65% and 72%. Combined screening by maternal factors and biophysical and biochemical markers at 30-34 weeks' gestation could identify a high proportion of pregnancies that will deliver SGA neonates.