Heart scanning tool could predict risk of developing type 2 diabetes using AI
Technology offers possibility for early interventions to help people reduce their chances of developing type 2 diabetes and related complications.
An artificial intelligence (AI) tool that analyses ECG (electrocardiogram) readings during routine heart scans could identify people at risk of type 2 diabetes as much as 10 years before they begin to develop the condition.
The innovative technology could allow for early interventions, helping people take steps to reduce their risk of developing type 2 diabetes in future.
Research funded by the British Heart Foundation was presented recently at the American Heart Association’s Scientific Sessions 2024, in Chicago.
Around 5.6 million people in the UK are living with diabetes, and it is thought up to 1.2 million of those have the condition and are yet to be diagnosed. Type 2 diabetes and ‘prediabetes’ are diagnosed using a blood test.
Early detection is vital in reducing risk of type 2 diabetes and its associated complications, which can include problems with the heart, eyes and feet.
The research team, led by Dr Fu Siong Ng and Dr Arunashis Sau at Imperial College London, developed the AI-ECG Risk Estimation for Diabetes Mellitus (AIRE-DM) tool, using around 1.2 million ECGs from hospital records.
Using figures from the UK Biobank, they were able to validate the AI’s ability to detect subtle changes in routine ECGs that could show that someone might be at higher risk of type 2 diabetes, years before their blood sugar levels begin to rise.
AIRE-DM predicted future risk in people of various ages, genders, ethnicities and socioeconomic backgrounds with a success rate of around 70%.
Researchers suggested using this tool could help spot people who might otherwise not have been identified as likely to develop the condition.
When the team incorporated the AI predictions with genetic and clinical information, including age and blood pressure, it improved the accuracy even further, providing an even clearer picture of risk.
AIRE-DM could also accurately assess results collected from single-lead ECGs, which are often used in wearable devices, indicating that it could in future be applied to millions of smart devices.
The AI will be piloted in the next year, and the researchers hope it could be rolled out in the NHS in the next few years.
Dr Libor Pastika, Clinical Research Training Fellow at Imperial College London, and first author said: “AI holds enormous potential to transform care that could lead to substantial improvements in health. By using AI to unlock insights hidden within ECG data, AIRE-DM could be revolutionary in identifying future risk of type 2 diabetes early on.
“By offering a cheap, accessible, non-invasive way to predict type 2 diabetes risk early, AIRE-DM could open up a new window of opportunity for more targeted, preventative care. Supporting people early on to make simple lifestyle changes could help more people avoid type 2 diabetes, and its associated complications.”
Professor Bryan Williams, Chief Scientific and Medical Officer at the British Heart Foundation, said: “This exciting research uses powerful artificial intelligence to analyse ECGs, revealing how AI can spot things that cannot usually be observed in routinely collected health data. This kind of insight could be a gamechanger in predicting future risk of developing type 2 diabetes, years before the condition begins.
“Type 2 diabetes is a rapidly growing health challenge that increases the risk of developing heart disease, however with the right support it is possible for people to reduce their risk of developing the condition. We look forward to seeing how this technology could be incorporated into clinical practice, providing an opportunity to intervene early to help reduce risk and even prevent type 2 diabetes and its associated complications, altogether.”
The research is supported by the NIHR (National Institute for Health and Care Research) Imperial Biomedical Research Centre, a translational research partnership between Imperial College Healthcare NHS Trust and Imperial College London.
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