Small for gestational age (SGA) is common in pregnancy and it has been associated with an increase in adverse perinatal outcomes, predisposition for neurological and cognitive delay in childhood and cardiovascular and endocrine diseases in adulthood.
The classification is not consensual, having been defined in different studies as estimated fetal weight, abdominal circumference or birthweight below the 10th, 5th or 3rd percentiles, with the prevalence varying with the definition that is used.
The increased risk of perinatal mortality and morbidity can be substantially reduced in cases identified prenatally, as close monitoring, timely delivery and prompt neonatal care can be undertaken, in comparison to those cases detected after birth.
Over time, several screening methods have been introduced, in order to optimize the detection rate for SGA. These approaches range from abdominal palpation, symphyseal-fundal height measurement, fetal biometries, uterine artery doppler assessment and, more recently, biochemical markers.
The aim of this thesis is to develop a model for prediction of SGA neonates in the absence of pre-eclampsia, based on maternal characteristics, clinical history, fetal biometry, uterine pulsatility index (Ut PI), mean arterial blood pressure (MAP) and serum biochemical markers (serum placental growth factor: PlGF; Soluble fms-like tyrosine kinase-1: sFlt-1) at 35-37 gestational weeks.
This was a prospective screening project for detection of SGA neonates, in women attending for their third-trimester hospital visit in pregnancy at King's College Hospital (London) and Medway Maritime Hospital (Kent). The project comprised three studies.
The first study included biophysical measurements of 5515 pregnant women, including 278 that delivered SGA (<5th) neonates. A SGA predictive model was developed based on the combination of maternal factors, clinical history and estimated fetal weight.
In the second study, a subset of 5121 pregnant women was evaluated, 245 of which had SGA (<5th) newborns. A model was developed based on the combination of maternal factors, clinical history, estimated fetal weight, mean arterial pressure and uterine artery 9 dopplers. It was found that the additional use of mean arterial pressure and pulsatility index of the uterine arteries did not significantly improve the performance of screening for delivery of SGA neonates in comparison to the first study.
In the third study, a subset of 3859 pregnant women was evaluated, comprising 158 SGA newborns. The SGA prediction model combined the following parameters: maternal factors, estimated fetal weight and biochemical values (serum placental growth factor, PlGF; fms-like soluble tyrosine kinase-1, sFlt-1). It was found that sFlt-1, when combined with maternal factors and fetal biometries, did not remain an independent factor in this predictive model. Additionally, serum PlGF only marginally improved the SGA screening performance when compared to the model of the first study.
Hence, based on the findings, the best prediction was provided by the combination of maternal factors, estimated fetal weight and serum placental growth factor (PlGF). This combined screening predicted, at a 10% false positive rate, 88, 96 and 94% of SGA neonates with birth weight below the 10th, 5th and 3rd percentiles delivering at <2 weeks following assessment. The respective values for SGA delivering ≥37 weeks were 64, 75 and 80%.
In conclusion, combined screening by maternal factors, biophysical and biochemical markers at 35-37 weeks can identify a high percentage of pregnancies that will deliver SGA neonates.European Union 7th Framework Programme - FP7-HEALTH-2013-INNOVATION-2 (ASPRE Project #601852)The Fetal Medicine Foundation (Charity No: 1037116)Roche Diagnostics Limite
