Improving the management of extremely early onset fetal growth restriction

Abstract

Fetal growth restriction (FGR) is a common complication of pregnancy and the single largest risk factor for stillbirth in high-resource settings. FGR can be classified by the gestation at diagnosis, using 32-34 weeks' gestation to differentiate early-onset from late-onset disease. Within early-onset FGR there appears to be an extreme subset, typically diagnosed before 28 weeks' and delivered prior to 33 weeks' gestation which is associated with more severe placental disease and worse outcomes. It is this extreme subtype, termed eFGR, which forms the focus of this thesis. With no therapeutic interventions available, eFGR management is based upon antenatal surveillance using ultrasonography and fetal heart rate monitoring. The goal of management is optimise outcome, whilst avoiding preventable stillbirth. However, there is a paucity of eFGR specific knowledge about survival and outcome, and further study is required to provide better information for clinicians and parents of affected babies. It was hypothesised that in cases of eFGR, antenatal factors, ultrasonography and FHR patterns can be used to better predict outcomes. This hypothesis was tested by: 1) Using population level and local data to determine the current incidence of eFGR and investigate the relationship between gestational age at delivery, birthweight and survival; 2) Performing a prognostic factor study to better characterise eFGR and identify if antenatal and ultrasound characteristics can be used to reliably predict outcome in individual cases of eFGR; 3) Prospectively examining the validity and potential value of ambulatory 24-hour fetal heart rate monitoring in cases of eFGR. The incidence of eFGR was confirmed to be 3 per 1000 births in the general maternity population. The relationship between gestational age, birthweight and neonatal death in preterm infants was explored to suggest the two can be combined to predict outcome. In the case of eFGR infants with static growth, there is likely to be little advantage by gaining gestation. On an individual level, a combination of ultrasound measurements at diagnosis can be used to predict the likelihood of stillbirth. In addition, longitudinal data collected over the course of an eFGR pregnancy relating to fetal growth and Doppler progression can be used to modify risk predictions as the pregnancy progresses. Finally, a comparison of computerised cardiotocography parameters in eFGR and normal pregnancies, although highlighting differences between the two, suggests that further work is required in this area to determine how analysis of fetal heart rate can be improved as a tool for predicting prognosis in these high-risk pregnancies. This set of studies has provided improved predictions of pregnancy outcomes for both clinicians and affected families. It has highlighted areas for further development which should translate in the future to improved management, subsequently reducing associated morbidity and mortality.

Date of Award	1 Aug 2021
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Emma Ingram (Supervisor), Edward Johnstone (Supervisor) & Alexander Heazell (Supervisor)