Strokes represent one of the leading causes of death and disability in the UK, impacting around 100,000 people each year.
However, with one in seven strokes seen as preventable, a new project aims to enhance the ability to predict whether a person is likely to experience a stroke in the future.
Funded by a £300,000 grant from the Medical Research Council, the project is led by experts at the University of Plymouth, University Hospitals Plymouth NHS Trust, the University of Exeter and NIHR Applied Research Collaboration South West Peninsula (PenARC). They will also work with two commercial medical investigation providers, Express Diagnostics and Ultracardiac.
The project will assess past brain scans and other medical test results of stroke survivors and aims to see if there are patterns which could have identified them as being at higher risk of stroke.
The researchers will then look to develop a series of artificial intelligence (AI) models that can predict whether someone is at greater risk of experiencing a stroke at any point over the next decade.
With the first five years of care post-stroke costing the NHS around £3.6 billion, and 13.7% of strokes regarded as being preventable, the project team hopes its work will not only improve lives but also prove cost-effective at a time when the health system is under greater financial pressure than ever.
Dr Stephen Mullin, Associate Professor in Neurology at the University of Plymouth’s Peninsula Medical School and Consultant Neurologist at University Hospitals Plymouth NHS Trust, is the project’s principal investigator. He said:
“Strokes can have a significant impact on both the people who experience them and their families. Often when we review the brain scans people who have had a major stroke, we see features – including what we call ‘silent strokes’ – that could have identified them as being at risk. We hope that by applying our expertise to create a way of improving stroke prediction, it will both prevent people developing a stroke and in the process save money which can be used to improve patient care elsewhere.”
The project brings together researchers with expertise in health data science, data governance, statistics, radiology/imaging, and neurology.
It will initially build a database of results from patients seen at University Hospitals Plymouth NHS Trust, and benefits from the support and collaboration of the national Sentinel Stroke National Audit Programme (SSNAP).
This database will include the results of magnetic resonance imaging (MRI) and computer tomography (CT) brain scans, electrocardiograms (ECG) and echocardiograms (ECGs), standard tests currently carried out when a person is suspected of having had a stroke.
It will be used to train an AI computer model, which the researchers hope can predict who will later develop strokes based on patterns within the data collected.
The work will leverage state-of-the-art techniques with AI, collectively known as ‘explainability’. These tools allow visualisation and identification of the factors driving predictions. This allows researchers to be certain that the predictions being made are accurate and hopefully will identify new factors which contribute to the risk of developing a stroke.
An opportunity will be given for patients at UHPNT to opt out of the use of their data in this project, with the research team currently compiling the database which will be used in the analysis.
Dr Mike Allen, PenARC Senior Research Fellow in Applied Healthcare Modelling and Data Science at the University of Exeter, added:
“This project is an exciting opportunity to apply cutting-edge AI technologies to routinely collected patient data. Through that we hope to identify patients at high risk of stroke, so that measures may be put in place to tackle that risk, and help those people live longer, happier, and more productive lives.”