Combining early (<11 weeks' gestation) ultrasound features and maternal factors to predict small-for-gestational age neonates.

OBJECTIVES

Placental related adverse pregnancy outcomes such as fetal growth restriction have significant short- and long-term implications for both mother and fetus. This study aimed to determine if conventional and novel early first trimester ultrasound measures are associated with small for gestational age (SGA) neonates. In addition, we aimed to assess whether a combination of ultrasound measures, maternal characteristics and biochemistry improved the prediction of this adverse pregnancy outcome.

METHODS

This was a prospective cohort study including ultrasound measurements: trophoblast thickness (TT), trophoblast volume (TV), mean uterine artery pulsatility index, crown-rump length, fetal heart rate, mean sac diameter (MSD) and yolk sac diameter. Biochemical markers considered in the analysis were placental growth factor (PIGF), pregnancy - associated plasma protein A (PAPP-A), beta human chorionic gonadotropin and alpha fetoprotein. Regression models were fitted for ultrasound parameters using multiples of the median (MoM). All measures were compared with normal birthweight (BW) ≥10th centile and SGA (BW < 10th centile). Logistic regression analysis was used to create a clinical prediction model for SGA based on maternal characteristics, ultrasound measurements at <11 weeks gestational age and maternal biochemistry collected at 10-14 weeks.

RESULTS

As compared to pregnancies delivered of babies with normal BW (n = 1068), MoM values for TT, TV, MSD, PAPP-A and PIGF were significantly reduced (P < 0.05) in pregnancies delivered of SGA babies (n = 73). The proposed logistic regression model includes maternal height, TV and PIGF resulting in an area under the receiver operator curve 0.70 (95% CI 0.63-0.76) for the prediction of SGA.

CONCLUSION

A significantly decreased TV, measured <11 weeks gestation, is predictive of BW < 10th centile. With addition of maternal height and PIGF, this three-marker algorithm provided a reasonable predictive value for the development of SGA later in pregnancy.