An innovative artificial intelligence (AI) tool is revolutionizing the early detection of atrial fibrillation (AF), a condition associated with irregular and rapid heart rates that significantly increase the risk of stroke. The tool, developed by scientists and clinicians from the University of Leeds and Leeds Teaching Hospitals NHS Trust, is currently under trial in West Yorkshire, England, as part of the Find-AF study.
Backed by funding from the British Heart Foundation (BHF) and Leeds Hospitals Charity, the AI scours general practitioners’ (GP) records to identify “red flags” in patients potentially at risk of AF. The algorithm analyzes risk factors such as age, sex, ethnicity, and co-existing medical conditions like high blood pressure, heart failure, and diabetes.
AF, often asymptomatic, affects an estimated 1.6 million people in the UK, though thousands remain undiagnosed. Early diagnosis and treatment can significantly reduce stroke risk, a goal that the Find-AF trial aims to achieve. AF contributes to approximately 20,000 strokes annually in the UK, a statistic this breakthrough technology seeks to mitigate.
One notable beneficiary of this trial is John Pengelly, a 74-year-old retired Army captain from Apperley Bridge, Bradford. Participating in the study led to the detection of his AF, despite his lack of symptoms. “You never think these things will happen to you,” said Pengelly. “I now take a few pills every day that will hopefully keep me going for a good few more years yet.”
The AI tool’s integration into several GP surgeries in West Yorkshire has yielded promising results. Chris Gale, Professor of Cardiovascular Medicine at the University of Leeds, emphasized the urgency of addressing undiagnosed AF. “All too often, the first sign someone has undiagnosed AF is a stroke, which can be devastating,” he noted.
Dr. Ramesh Nadarajah of Leeds Teaching Hospitals NHS Trust expressed optimism about scaling the initiative. “The West Yorkshire study could pave the way for a UK-wide trial, hopefully preventing numerous avoidable strokes,” he said.
The success of Find-AF highlights the transformative potential of AI in healthcare, enabling earlier interventions and improving patient outcomes. By identifying at-risk individuals before symptoms appear, the trial marks a significant step toward proactive cardiovascular care and stroke prevention.
