Title: Decision-support for individualised risk assessment of fetal health during labour: preventing fetal brain damage and death by utilising large, routinely collected datasets of cardiotocography and clinical risk factors
Funder: Department of Health and Social Care

Abstract: Our overarching goal is to improve clinical decision-making around labour management and cardiotocography (CTG) monitoring by providing timely, data-driven and individualised assessment of fetal wellbeing, so that fetal damage due to oxygen deprivation intrapartum can be avoided. We have already developed a prototype Oxford System (OxSys) for continuous risk assessment throughout labour, running at the Oxford maternity ward (research only). It is based on combined evaluation of clinical risk factors and CTG data (captured wirelessly in real-time from hospital fetal monitors) and is displayed on a prototype tablet/mobile App. The aim of this proposal is to produce an independently validated, trustworthy and clinically relevant OxSys3.0, that is fully scalable and ready for commercialisation. We have formed a multidisciplinary team of experts in obstetrics, neonatology, maternity and CTG data, computer science, signal processing, Deep Learning (DL), statistical prediction models, qualitative research, and health economics. We propose Technical, Clinical and Commercial work-packages to: Enhance CTG information extraction using DL; Develop the App s technical capabilities incorporating relevant regularity requirements; Finalise OxSys3.0 for continuous risk assessment and validate it independently with external data; Ensure OxSys3.0 benefits midwives/obstetricians and mothers/families by understanding their needs/requirements, iterative App co-design, and formal usability studies; Test OxSys3.0 in a pilot prospective study to provide feasibility data; Develop NHS adoption strategy and early health economic model. The Public and Patient Involvement and Advisory Panels will be central in ensuring that: work is relevant to all stakeholders; diverse viewpoints and voices are incorporated throughout; developments/results reach the widest possible audience. At completion, we will also have: designed large-scale clinical effectiveness studies with funding applications submitted or in preparation; licensed-out OxSys3.0 to commercial partners or formed a dedicated company. This project will maximise the likelihood of OxSys3.0 for clinical impact, benefitting individuals, society, and clinicians, and bringing considerable cost-savings to the NHS.

Lay abstract: Aim To help midwives and doctors prevent brain damage and death of term babies during childbirth by using a new, computer-based system which interprets the fetal heart rate. Background Contractions during labour squeeze the placenta and umbilical cord which reduces the oxygen supply reaching the baby. Most babies cope well but a small percentage are at risk of suffocation. As a result, each year in the UK alone, around 100 babies die and 1,100 sustain brain damage during labour at term - a devastating tragedy for them and their families. Babies at risk would benefit from emergency Caesarean section or assisted delivery. That is why midwives and doctors monitor babies wellbeing during labour using a cardiotocogram (CTG) &ndash; continuous graphs displaying the womb's contractions and the baby's heart rate. Clinicians visually interpret the graphs to identify babies at risk of oxygen deprivation. But the complex CTG patterns are difficult to interpret by eye, our understanding of the CTG needs improvement, and interpretation depends on the clinical context. Our failure to monitor babies well is reflected in the NHS maternity-related litigation bill that amounted to &pound;1.2bn in 2018-19. With today s computing power, intelligent computer-based methods can learn from large datasets. Computers can support clinical decision-making by providing data-based, objective risk-assessment in the clinical context of each birth. We have already completed major work using data from ~60,000 births. Our research prototype system (OxSys), which combines CTG interpretation with clinical risk factors, performed favourably compared to decision-making in clinical practice, when tested on past data. It is running (only as a research tool) on a wireless tablet in Oxford, analysing all CTGs in real-time during labour. Plan We have assembled a strong multidisciplinary team of scientists, clinicians, partners and stakeholders to finalise OxSys development and ensure it is ready for large-scale clinical testing and successful translation into the NHS. With the help of Advisory and Patient/Public Involvement Panels, we plan to: 1. Improve OxSys accuracy using new data (100,000 births) and enhanced data-analysis methods, and test/validate the next version with additional data (40,000 births). 2. Develop further the OxSys App/Display to ensure it meets mothers/families and clinicians needs and is easy and safe to use; and conduct first clinical tests at the Oxford labour ward. 3. Ensure OxSys is NHS-ready, meeting the regulatory requirements, establishing its place in the current healthcare pathways and its cost-saving potential. Output This project will provide fetal monitoring in a way that has never been possible before as the labour experiences of 100,000 babies will be distilled into the computer-memory of a clinical decision-support system. We will continue sharing our progress through academic publications, social media, engagement events, patient/charitable organisations, and involving members of the public throughout.

Research activity codes: 4.2 EVALUATION OF MARKERS AND TECHNOLOGIES;4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES;7.3 MANAGEMENT AND DECISION MAKING
Health categories: REPRODUCTIVE HEALTH AND CHILDBIRTH