Diagnostic Tests in the Prediction of Neonatal Outcome in Early Placental Fetal Growth Restriction.

Background and

Objectives

Monitoring pregnancies with fetal growth restriction (FGR) presents a challenge, especially concerning the time of delivery in cases of early preterm pregnancies below 32 weeks. The aim of our study was to compare different diagnostic parameters in growth-restricted preterm neonates with and without morbidity/mortality and to determine sensitivity and specificity of diagnostic parameters for monitoring preterm pregnancies with early preterm fetal growth restriction below 32 weeks. Materials and

Methods

Our clinical study evaluated 120 cases of early preterm deliveries, with gestational age ≤ 32 + 0 weeks, with prenatally diagnosed placental FGR. All the patients were divided into three groups of 40 cases each based on neonatal condition,: I-Neonates with morbidity/mortality (NMM); II-Neonates without morbidity with acidosis/asphyxia (NAA); III-Neonates without neonatal morbidity/acidosis/asphyxia (NWMAA).

Results

Amniotic fluid index (AFI) was lower in NMM, while NWMAA had higher biophysical profile scores (BPS). UA PI was lower in NWMAA. NWMAA had higher MCA PI and CPR and fewer cases with CPR <5th percentile. NMM had higher DV PI, and more often had ductus venosus (DV) PI > 95th‱ or absent/reversed A wave, and pulsatile blood flow in umbilical vein (UV). The incidence of pathological fetal heart rate monitoring (FHRM) was higher in NMM and NAA, although the difference was not statistically significant. ROC calculated by defining a bad outcome as NMM and a good outcome as NAA and NWMAA showed the best sensitivity in DV PIi. ROC calculated by defined bad outcome in NMM and NAA and good outcome in NWMAA showed the best sensitivity in MCA PI.

Conclusions

In early fetal growth restriction normal cerebral blood flow strongly predicts good outcomes, while pathological venous blood flow is associated with bad outcomes. In fetal growth restriction before 32 weeks, individualized expectant management remains the best option for the optimal timing of delivery.