'Artificial intelligence could spot UTI linked to millions of deaths – and fast'

06 February 2023 , 23:32

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As we get older, UTIs get more common and more problematic (Image: Getty Images)

Urinary tract infections are one of the most common types of infection, and are linked to millions of deaths worldwide each year.

But despite being so ­prevalent, early signs of a UTI can be challenging to recognise because symptoms – ­including pain, ­temperature, frequency of urination, changes in sleep patterns and tremors – vary due to a person’s age and ­pre-existing health conditions.

Diagnosis can be difficult too, with lab tests that provide the only ­definitive result taking up to 48 hours.

As we get older, UTIs get more common and more problematic. They’re also more difficult to keep track of and so may become chronic and difficult to eradicate.

So a quick, non-invasive way of ­diagnosing UTIs early would be a boon to doctors and patients, especially in care home settings.

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The £1.1million FEATHER project, led by Edinburgh University scientists, is developing artificial intelligence and talking robots to help detect urinary tract infections in vulnerable people.

Researchers hope by using AI and robotics, infections will be picked up early and lessen the over-prescription of antibiotics for the condition. To this end, experts from the universities of Edinburgh and Heriot-Watt are collaborating with care firms Leuchie House and Blackwood Homes and Care to develop software and robots.

Sensors, placed in residents’ rooms, will gather data about their daily ­activities. The technology will be able to spot changes in a person’s ­behaviour or activity levels, which will then trigger the robot.

This kind of tech could detect signs of infection such as variations in walking pace and movement, altered sleep patterns and increased visits to the bathroom, before a UTI takes hold. By raising the alert early, a GP will have time to wait for lab results from urine tests and give antibiotics, which improves outcomes and reduces the cost to the NHS.

Early diagnosis would mean fewer visits to A&E and cases of sepsis, kidney failure and loss of life.

Project lead Professor Kia Nazarpour, of ­Edinburgh University, says: “This data ­platform will help ­individuals, carers and clinicians to recognise the signs of potential urinary tract infections far earlier, helping to prompt the investigations and medical tests needed.

“Earlier detection makes timely treatment possible, improving outcomes for patients, lowering the number of people presenting at A&E, and reducing costs to the NHS.”

Colin Foskett of Blackwood Homes and Care said: “Early UTI detection could prevent hospital admissions, associated decline and ensure people can continue to live independently.”

Miriam Stoppard