AI to help GPs identify those at high risk of heart-related death

A new artificial intelligence (AI) algorithm can identify those at highest risk of conditions leading to heart-related death, including kidney failure and diabetes, according to new research funded by us.

The findings, presented at the European Society of Cardiology Congress in London, reveal that the AI tool could allow GPs to spot those at highest risk earlier. Offering these patients preventative treatments sooner or altering their medications could help reduce their risk of heart-related death. Researchers hope the AI could be available within two years.

Network of organ systems

Around 80 per cent of people with heart and circulatory diseases have at least one other health condition, or comorbidity. The body is made up of a network of organ systems that work together to keep the body functioning.

A normally functioning heart and circulatory system supplies them with blood that carries oxygen and nutrients, so when things go wrong with this system, things can go wrong in other organs too. If something goes wrong in one system, such as the cardiovascular system, it can affect others around the body.

The team led by Professor Chris P Gale, Consultant Cardiologist at Leeds Teaching Hospitals NHS Trust and University of Leeds, and Dr Ramesh Nadarajah, Health Data Research UK fellow at the University of Leeds, trained the AI by analysing health records of over two million patients.

OPTIMISE

The AI tool, OPTIMISE, identified over 400,000 people as being at high risk of dying from a heart cause. This group made up almost three quarters (74 per cent) of participants who died of a heart-related condition at 10 year follow up.

The team piloted OPTIMISE on a group of 82 high risk-patients. One in five received a diagnosis of kidney disease that would not have been picked up otherwise. More than half of those with high blood pressure were given different medication to better manage their risk of heart-related death.

Researchers found that in many cases patients had undiagnosed conditions, or had not received the medications that could help reduce their risk. OPTIMISE identified patients at an earlier stage and more accurately than current methods, which led to improved management of risk factors, ultimately preventing conditions from worsening and reducing chances of heart-related death.

Push of a button

The researchers hope the tool could be implemented into GP systems to allow them to identify high-risk patients at the simple push of a button. Next, they will carry out a larger clinical trial and hope to roll out OPTIMISE for use by GPs within two years.

Professor Bryan Williams, our Chief Scientific and Medical Officer, said: "A quarter of all deaths in the UK are caused by heart and circulatory diseases and this new and exciting study harnesses the power of ever-evolving AI technology to detect the multitude of conditions that contribute to it.

"Early diagnosis is key to reducing hospital admissions and heart-related deaths, allowing people to live longer lives in good health. We look forward to seeing how this will help accelerate and inform clinical decision-making, ensuring patients receive timely and effective treatment and support."

'Constellation of factors'

Dr Ramesh Nadarajah, a Health Data Research UK fellow at the University of Leeds, said: "Heart-related deaths are often caused by a constellation of factors. This AI uses readily available data to gather new insights that could help healthcare professionals ensure that they are providing timely care for their patients.

"We hope our research will ultimately benefit patients living with heart and circulatory diseases, as well as helping relieve pressure off our NHS systems, as prevention is often a cheaper solution than treatment. Next, we plan to perform a clinical trial where we are providing doctor led care to patients."

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