In a significant development in healthcare, artificial intelligence (AI) is being used to identify people at risk of heart conditions even before they show symptoms. A new, ground-breaking AI tool is currently being tested to find early warning signs of atrial fibrillation (AF), a serious heart condition that can lead to stroke if left untreated. This AI-powered innovation could be the key to preventing thousands of strokes each year.
Atrial fibrillation causes the heart to beat irregularly and often abnormally fast. According to the British Heart Foundation (BHF), people with AF have a significantly higher risk of suffering a stroke. Symptoms, such as heart palpitations, dizziness, and shortness of breath, may be experienced by some individuals, but others may remain unaware of the condition as it often presents without any noticeable signs. Around 1.6 million people in the UK have been diagnosed with AF, but experts believe many thousands more cases remain undiagnosed.
John Pengelly, a former Army captain, was fortunate to have his AF risk identified early through the AI tool. He expressed his gratitude, saying, “I’m really grateful that my AF risk had been detected by the algorithm. I now take a couple of pills a day to reduce my heightened chance of a potentially deadly stroke.” His case is a testament to the life-saving potential of this innovative technology.
The AI tool, part of the Find-AF trial, uses a sophisticated algorithm to examine GP records for potential “red flags” that indicate a patient’s risk of developing AF. The project is funded by the BHF and the Leeds Hospitals Charity and is being led by scientists and clinicians at the University of Leeds and Leeds Teaching Hospitals NHS Trust. The algorithm was trained using anonymized health records from over 2.1 million people, helping it learn to detect early warning signs of AF.
Currently, the tool is being tested at several GP surgeries in West Yorkshire, where it is evaluating patient records to identify those who may be at risk of developing AF in the next six months. High-risk patients are then offered further testing, including the use of handheld electrocardiography (ECG) machines to monitor their heart rhythms. If AF is detected, the patient’s GP is alerted and treatment options can be discussed. The AI tool takes into account various factors, including age, sex, ethnicity, and the presence of other conditions like heart failure, high blood pressure, diabetes, and chronic obstructive pulmonary disease.
The potential of this AI tool to prevent strokes is significant. It is estimated that AF contributes to around 20,000 strokes annually in the UK, and experts believe that early detection and treatment could substantially reduce this number. Chris Gale, professor of cardiovascular medicine at the University of Leeds, emphasized the importance of early detection, noting, “All too often, the first sign that someone is living with undiagnosed AF is a stroke. This can be devastating for patients and their families, changing their lives in an instant.”
The impact of undiagnosed AF extends beyond health consequences; it also poses a considerable financial burden on healthcare services. Professor Gale added, “It also has major cost implications for health and social care services—costs which could have been avoided if the condition were spotted and treated earlier.”
Dr. Sonya Babu-Narayan, associate medical director at the British Heart Foundation, highlighted the promise of AI in transforming healthcare. She said, “By harnessing the power of routinely collected healthcare data and prediction algorithms, this research offers a real opportunity to identify more people who are at risk of AF and who may benefit from treatment to reduce their risk of a devastating stroke.”
AI’s role in improving healthcare outcomes through data-driven insights was further endorsed by Dr. Ramesh Nadarajah from Leeds Teaching Hospitals NHS Trust, who explained, “Data are collected about patients in every interaction they have with the NHS. These data have huge potential to make early identification of and testing for conditions like AF easier and more efficient.”
Earlier this month, Health Secretary Wes Streeting referred to AI and big data as “game-changing” technologies for healthcare. He praised their potential to revolutionize the way diseases are diagnosed and treated, stating, “We can use AI, machine learning, genomics, big data, to not only intervene early with earlier diagnosis and earlier treatment, but to actually predict and prevent illness, which is the game-changing paradigm shift in healthcare in this century.”
This promising AI tool could help reshape the future of healthcare, ensuring that more individuals with atrial fibrillation are identified before they suffer the devastating consequences of an undiagnosed condition. With ongoing trials and future plans for wider implementation, the hope is that this technology will prevent countless avoidable strokes, saving lives and reducing the strain on healthcare resources.
By incorporating cutting-edge AI into healthcare practices, we witness an intersection of science, compassion, and stewardship, ensuring the health and dignity of individuals are upheld. As Catholics, we are called to care for the vulnerable, and such technological advancements represent a modern-day means of safeguarding human life—a reflection of God’s call to protect the sanctity of life in all its stages.
