American researchers have developed an analysis of heart function during sleep using artificial intelligence that allows for the assessment of the risk of stroke and heart disease in the future.
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The researchers trained a software model using data from about 16,000 people who underwent electrocardiograms (ECGs) during sleep, and then tested the model on two additional groups, comprising about 23,000 patients.
The researchers found that data from a single electrocardiogram electrode attached to the chest was sufficient to assess risks, as artificial intelligence analyzed changes in heart rhythms during sleep and identified signs associated with the development of future diseases.
With each one standard deviation increase in the risk score calculated by the software model, the probability of stroke increased by 19 to 40%, the risk of heart failure increased by 69 to 133%, and the risk of atrial fibrillation – a heart rhythm disorder – increased by 103 to 172%.
Researchers have found that the early stage of sleep is of great importance in identifying risks, as during this period rapid changes occur in the nervous system, which may make hidden heart rhythm disturbances more apparent.
According to the researchers, this method may help identify people who are at higher risk of stroke and other cardiovascular diseases long before symptoms appear.
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