Title: Towards preventing fetal brain injury and death whilst reducing the rate of emergency deliveries: making use of large datasets of fetal heart rate monitoring
Funder: Department of Health and Social Care

Abstract: Background: Annually, in the UK, about 100 healthy babies die and about 1,100 sustain brain injury during labour at term. Nearly 50% of the NHS litigation bill is due to obstetric claims (3.1bn in 2000-10), most of which relate to shortcomings in labour management and cardiotocography (CTG) interpretation. In clinical practice, CTG is used to monitor high-risk labours and make decisions about the need for emergency operative deliveries. Classic' CTG patterns were identified empirically in the 1980s with little refinement since. The patterns are complex; their relation to impending fetal compromise is confounded by maternal and fetal risk factors; visual interpretation is difficult and poorly reproducible; and CTG has relatively low sensitivity. Consequently, many unnecessary operative deliveries (Caesarean and instrumental vaginal births) are performed (a worldwide concern); whilst babies at risk are not always delivered in a timely fashion. Both problems, under-intervention and over-intervention, can cause harm. Aims: My goal is to develop a data-driven' diagnostic system (i.e. derived from large datasets) to replace empirical assessment of CTG patterns and prevent fetal injuries and death during term labour, whilst avoiding unnecessary operative deliveries. The underlying concept is that assessing fetal health during labour can be substantially improved if existing large datasets are analysed to derive diagnostic CTG-based indices in relation to clinical confounders and a range of perinatal outcomes: (i) severe compromise, excluding congenital abnormalities (a composite outcome of stillbirth, neonatal death, neonatal encephalopathy, seizures, resuscitation followed by 48hr intensive care); (ii) umbilical arterial blood acidaemia at delivery; and (iii) normal non-acidaemic infants. Research Plan: This proposal arises from my extensive prior work with the Oxford database of 59,279 term deliveries with digital intrapartum CTG records linked to detailed clinical data. My work to-date has demonstrated the potential benefits of my approach. I have developed (i) 64 computerised CTG features, both classic' and new data-driven ones; (ii) a diagnostic system prototype (OxSys), which triggers an alarm if the risk for the fetus is increased. OxSys already performs better on the Oxford cohort than assessment in clinical practice. I propose two main sections: Discovery and Translation with interlinked (but not interdependent) aims. In the Discovery part of my proposal, I will: (1)Determine the time-course of numerical CTG features in the different outcome groups to account for the evolving nature of intrapartum hypoxia and, thus, improve CTG interpretation. (2)Determine the CTG patterns related to specific neuro-injuries and early childhood development of term babies with hypoxic-ischemic encephalopathy (HIE). This will utilise recent progress with imaging techniques which allows more precise diagnosis of acute peripartum insult and antenatally established injury. (3)Identify how clinical risk factors can be combined with computerised CTG to provide individualised risk assessment for each labour. In the Translation part, I will incorporate in OxSys the findings from Discovery. I can test the contribution of each new finding towards increasing the sensitivity and/or reducing the false positive rate of OxSys. I will thus iteratively develop improved versions of OxSys. Subsequently, I will validate OxSys on a large additional cohort collected at Oxford in 2012-18 (approx. 23,000 births) and ensure external datasets for future validation. I will develop the technical capability of a real-time CTG-analysis tablet for the Oxford Labour Ward. This Minimal Viable Product' will be crucial for innovation, attracting future funding, and generating feedback from clinicians (beyond this Fellowship). Potential benefits: This interdisciplinary project will allow evidence-based risk assessment of the fetus in a way that has not been possible before. Such data-based screening of the fetus will benefit families, clinicians, society and the NHS by minimising brain injury, perinatal deaths and unnecessary interventions.

Lay abstract: Aim: to help clinicians prevent neonatal brain injury and death of term babies during labour and reduce the number of emergency deliveries by using better diagnostics. Motivation: Oxygen reaches the baby in the womb from the mother via the placenta and umbilical cord. During labour, the contractions squeeze the placenta and cord reducing the supply of oxygen to the baby. Most healthy babies cope well, but a small percentage are at risk of suffocation and brain injury. This causes each year in the UK about 100 healthy babies to die and about 1,100 to sustain brain injury during labour at term. A baby which is at higher risk can be delivered urgently by emergency Caesarean section or instrumental vaginal extraction. To continuously monitor the baby during labour, midwives and doctors use the cardiotocogram (CTG), which continuously displays the womb's contractions and the baby's heart rate. But our understanding of how to read the CTG is limited and the patterns are difficult to interpret by eye, so some babies end up injured while at the same time many unnecessary emergency Caesareans and instrumental extractions are performed. Widely adopted in the 1970s, CTG monitoring has barely improved since. Also, because of the uncertainty with CTG interpretation, it is contra-indicated in the UK for low-risk labours, even though deciding who is at low-risk is in itself problematic. As a result, sometimes babies who would benefit from CTG monitoring do not have it. Nearly 50% of the NHS litigation bill relates to maternity claims (between the years 2000 to 2010 these amounted to 3.1bn) and the majority of these related to shortcomings in labour management and CTG interpretation. Plan: With current computing power, it is finally possible to improve CTG interpretation by studying the relation of the CTG patterns during labour to the baby's health at birth. I have already completed substantial work using routinely collected data from nearly 60,000 labours (all monitored babies in Oxford between 1993 and 2011). This database is very large which is crucial if we want to draw meaningful conclusions, especially because fetal problems are rare. I have derived from the data a first prototype of a diagnostic system (OxSys) that can reliably interpret the CTG and performs comparably to current clinical practice. This proposal aims to substantially improve its performance as I plan to design OxSys to detect early as many as possible of the babies with problems but provoke as few as possible unnecessary emergency deliveries. To achieve this I plan to use advanced mathematical methods for 'optimisation' called meta-heuristics - meaning that we can determine from the data what is the best system configuration. Furthermore, I will investigate the effect of risk factors, such as maternal condition and demographics, use of drugs in labour, and known fetal problems. This will ensure that individualised risk assessment is provided for each individual labour - thus OxSys will operate in the broader clinical context. In the next three years I will also ensure OxSys is translated into a robust tablet prototype for future clinical testing. Finally, I will ensure that additional large datasets from UK and other EU countries are available, on which OxSys can be tested and validated before large testing in clinical practice.Output: This project will allow evidence-based risk assessment of the fetus in a way that has never been possible before. The labour experiences of nearly 60,000 babies will be distilled into the memory of the new computer-based diagnostic system. The main output from this research will be a diagnostic tool in the delivery room displaying the risk for the baby helping to prevent fetal injury and reduce the rate of emergency deliveries. This should make CTG interpretation more reliable and potentially allow CTG monitoring of low-risk labours. I will endeavour to publish my findings in relevant scientific journals but also in the public domain through social media, the University's press office, and through engagement and dissemination events such as the Oxfordshire Science Festival. I will actively involve members of the public and hold meetings with representatives every nine months.

Research activity codes: 4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: REPRODUCTIVE HEALTH AND CHILDBIRTH;INJURIES AND ACCIDENTS