AI Could Predict Heart Attack Risk A Decade in Advance, Oxford Study Reveals

Artificial intelligence (AI) has made significant strides in various fields, including medical research. AI technologies are being used to analyze large datasets, identify patterns, and make predictions, which can be particularly valuable in the complex and data-rich domain of healthcare.

Now, a groundbreaking study has revealed the potential of artificial intelligence to predict an individual's risk of suffering a heart attack up to a decade in advance. This revolutionary technology holds the promise of saving countless lives and revolutionizing the treatment of heart disease.

The study, funded by the British Heart Foundation (BHF), explains that AI technology could potentially save the lives of thousands with chest pain who may not have been identified as at risk of a heart attack and therefore may not have received appropriate treatment to lower their risk.

The new study, led by Professor Charalambos Antoniades at the University of Oxford, analyzed data from over 40,000 people undergoing routine cardiac CT scans at eight UK hospitals. Participants were followed for a median of 2.7 years. They found that while those with significant coronary artery narrowings were more likely to have serious cardiac events or death, twice as many patients with no significant narrowings experienced heart attacks and cardiac deaths.

The team used a new AI tool, trained using information on changes in the fat around inflamed arteries, as well as information on narrowings of the arteries and other clinical risk factors. Further testing over a longer period revealed it could independently and accurately predict the risk of cardiac events.

Among those with no obstructions to their arteries, those with the highest levels of inflammation in their blood vessels had a more than 10-fold higher risk of cardiac death compared to those with lower levels of inflammation.

As per a release by Oxford, In a world-first pilot, the team provided AI-generated risk scores to clinicians for 744 consecutive patients and found that in up to 45 percent of cases, clinicians altered patients' treatment plans, indicating that this AI tool could be hugely valuable in guiding and informing how patients with chest pain are managed, ensuring early identification and preventative treatment of those at highest risk.