Designed specifically for female patients, the model could enable doctors to identify high-risk women earlier, thereby enabling better treatment and care. The research was led by Imperial College London and is detailed in The Lancet Digital Health.
In their British Heart Foundation funded study, the researchers used artificial intelligence to analyse over one million ECGs from 180,000 patients, of whom 98,000 were female.
The researchers developed a score that measures how closely an individual's ECG matches ‘typical’ patterns of ECGs for men and women, and which showed a range of risk for each sex. Women whose ECGs more closely matched the typical ‘male’ pattern – such as having an increased size of the electrical signal – tended to have larger heart chambers and more muscle mass.
These women were also found to have a significantly higher risk of cardiovascular disease, future heart failure, and heart attacks, compared to women with ECGs more closely matching the ‘typical female’ ECG.
Previous evidence has shown that men tend to be at higher risk of cardiovascular disease. Because of this, healthcare professionals and the public believe that women’s risk of cardiovascular disease is low, even though the risk for women is high with women twice as likely to die of coronary heart disease than from breast cancer in the UK.
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In a statement, research lead Dr Arunashis Sau, Academic Clinical Lecturer at Imperial College London’s National Heart and Lung Institute, and cardiology registrar at Imperial College Healthcare NHS Trust, said: "Our work has underlined that cardiovascular disease in females is far more complex than previously thought. In the clinic we use tests like ECGs to provide a snapshot of what’s going on, but as a result this may involve grouping patients by sex in a way that doesn’t take into account their individual physiology. The AI enhanced ECGs give us a more nuanced understanding of female heart health – and we believe this could be used to improve outcomes for women at risk of heart disease.”
The research group recently published another paper on the related AI-ECG risk estimation (AIRE) model that can predict patients’ risk of developing and worsening disease from an ECG. NHS trials of AIRE are planned for late 2025. These will evaluate the benefits of implementing the model with patients from hospitals across Imperial College Healthcare NHS Trust and Chelsea and Westminster Hospital NHS Foundation Trust. This latest model will be trialled in conjunction with AIRE.
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