A new artificial intelligence tool (AI) developed in the UK can rapidly rule out heart attacks in people attending A&E and help tens of thousands avoid unnecessary hospital stays each year, according to its creators.
Known as Rapid-RO, the AI tool has been found to successfully rule out heart attacks in over a third of patients across four UK hospitals during trials.
Professor James Leiper, associate medical director at the British Heart Foundation (BHF), which funded the study, said: “This research demonstrates the important role AI could play in guiding treatment decision for heart patients.
“By quickly identifying patients who are safe to be discharged, this technology could help people avoid unnecessary hospital stays, allowing valuable NHS time and resource to be redirected to where it could have the greatest benefit.”
Blood tests are generally used to confirm diagnosis when a patient arrives at hospital with a suspected heart attack.
This research demonstrates the important role AI could play in guiding treatment decision for heart patients— Prof James Leiper
These tests measure levels of a protein called troponin which rises when there is damage to the heart muscle.
However, this increase may not be reliably seen until hours later so people are often kept in hospital for further troponin tests and monitoring.
Some of these patients will eventually be discharged without needing treatment after a heart attack is ruled out.
Dario Sesia, a PhD student supported by BHF at Imperial College London, developed Rapid-RO to identify patients who are at very low risk of heart attack.
Rapid-RO was trained using data from over 60,000 patients across the UK and then tested on more than 35,000 patients.
It works by combining the data from the initial troponin blood test with other patient information collected during hospital admission, which is then analysed by the algorithm.
Patients are then identified as either being in a very low risk group for having a heart attack, or not.
Rapid-RO was able to successfully rule out heart attacks in 36% of patients, compared to 27% ruled out by troponin blood testing alone.
It was also found to be more accurate at identifying heart attack cases.
Many patients require multiple troponin tests to confirm they're not having a heart attack, resulting in longer hospital stays and increased costs— Dr Amit Kaura
Troponin tests missed four times as many heart attacks (108 cases) compared to the AI tool (27 cases), the researchers said.
It was also effective regardless of ethnicity, sex and whether patients had Covid-19, they added.
Dr Amit Kaura, postgraduate clinical research fellow in cardiology from Imperial College London, said: “Current methods for ruling out a heart attack combine a clinical assessment with a blood test measuring troponin, a blood marker of heart muscle damage.
“Many patients require multiple troponin tests to confirm they’re not having a heart attack, resulting in longer hospital stays and increased costs.
“We developed an artificial intelligence-based model, using age, the first set of blood tests – including troponin – and other basic health information, to help doctors to rule out heart attacks quicker compared to current methods, whilst maintaining high accuracy across different ages and in patients with different health conditions.
“Our study shows how artificial intelligence can assist doctors in making more timely decisions about patient care, preventing unnecessary hospital stays, all while maintaining patient safety.”
As part of the next steps, the researchers are hoping to turn Rapid-RO into an app that could be used by doctors.
Professor Leiper said: “We look forward to more research to understand how Rapid-RO could in future be used to accelerate clinical decisions, improving patient treatment and care.”
The findings were presented at the British Cardiovascular Society Conference in Manchester.
