AI Tool Predicts Type 2 Diabetes Risk Years in Advance: NHS Launches World-First Trial

Hospitals trial AI to spot type 2 diabetes risk

Early work suggests they system can spot risk about 70% of the time. Giving the AI extra details about other background risk factors, such as the patients age, sex and whether they already have high blood pressure and or are overweight, can improve the predictive power, says lead researcher Dr Fu Siong Ng. He told BBC News: "It is already quite good just with the ECG data, but it is even better when you add in those." An ECG (electrocardiogram) records and can reveal problems with the electrical activity of the heart, including the rate and rhythm. Dr Fu says the ECG changes that the system detects are too varied and subtle for even highly skilled doctors to interpret with the naked eye. "It's not as simple as saying it's this or that bit of the ECG. It's looking at a combination of subtle things." As part of the trial up to 1,000 patients at both hospitals will have ECG scans read by the AI system to see if it helps detect and predict disease. It's not something that will be offered to routinely yet, although the experts hope it could be rolled out more widely on the NHS. That could take five years or more, says Dr Fu.

NHS to begin world-first trial of AI tool to identify type 2 diabetes risk

Exclusive: Two London hospital trusts to trial tool that can predict those at risk up to 13 years before condition develops The NHS in England is launching a world-first trial of a "gamechanging" artificial intelligence tool that can identify patients at risk of type 2 diabetes more than a decade before they develop the condition. More than 500 million people worldwide have type 2 diabetes, and finding new ways to spot people at risk before they develop the condition is a major global health priority. Estimates suggest 1 billion people will have type 2 diabetes by 2050. The condition is a leading cause of blindness, kidney failure, heart attacks, strokes and lower limb amputation. It is often linked to being overweight or inactive, or having a family history of type 2 diabetes, although not all those diagnosed are in those categories. Now doctors and scientists have developed a transformative AI tool that can predict those at risk of the condition as much as 13 years before it begins to develop. The technology analyses electrocardiogram (ECG) readings during routine heart scans. It can detect subtle changes too small to be noticed by the human eye that could raise the alarm early about a patient on the road to getting type 2 diabetes. It could enable early interventions and potentially help people avoid developing the condition altogether by, for example, making changes to their diet and lifestyle. The NHS will begin trialling the tool in 2025 at Imperial College healthcare NHS trust and Chelsea and Westminster hospital NHS foundation trust, and will be the first healthcare system in the world to do so, the Guardian has learned. Those involved in developing the technology, called the AI-ECG risk rstimation for diabetes mellitus (Aire-DM), hope it could be rolled out across the health service in England and in other countries within the next few years. "AI holds enormous potential to transform care that could lead to substantial improvements in health," said Dr Libor Pastika, a clinical research training fellow at Imperial. "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. "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, preventive care, helping people avoid the condition and its associated complications." A team led by Dr Fu Siong Ng and Dr Arunashis Sau at Imperial developed the tool using 1.2m ECGs from hospital records. They then used data from the UK Biobank, which holds the genetic data and medical records of more than 500,000 participants, to validate the tool's ability to detect subtle changes in ECGs. The tool maps tiny ECG patterns more common in those who will go on to develop type 2 diabetes in the future - and then looks for those same patterns in new ECGs. The telltale signs include variations in how the heart's electrical signal travels, such as small changes in the timing, shape, or patterns of certain electrical waves. The tool can also identify longer electrical activation times or differences in the way the heart's electrical signals reset. While these changes may seem minor, they reflect early effects of diabetes on the heart's structure and function, well before symptoms appear. Tests have already shown the tool accurately predicts risk in people of various ages, genders, ethnicities and socioeconomic backgrounds about 70% of the time. When the AI predictions were combined with genetic and clinical information, such as age and blood pressure, accuracy improved further, providing an even clearer picture of risk, the researchers said. Prof Bryan Williams, the chief scientific and medical officer of the British Heart Foundation, a charity that helped fund the development of the tool, 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."