Wearable gadgets such as smartwatches could be used to predict a higher risk of developing heart failure and abnormal heart rhythms in later life, according to a recent study by UCL researchers.
A peer-reviewed study published in The European Heart Journal Digital Health looked at data from 83,000 people who underwent a 15-second electrocardiogram (ECG) comparable to that done using smart watches and phone devices.
Researchers have identified EKG recordings containing an extra heartbeat, which is usually benign but, if it occurs frequently, is linked to conditions such as heart failure and arrhythmias (irregular heartbeats).
They found that people with an extra heartbeat in this short record (one in 25 of the total) had twice the risk of developing heart failure or an irregular heart rhythm (atrial fibrillation) over the next 10 years.
The ECG recordings analyzed came from people between the ages of 50 and 70 who had no known cardiovascular disease at the time.
Heart failure is a condition where the heart pump is weakened. It often cannot be treated. Atrial fibrillation occurs when abnormal electrical impulses suddenly start firing in the heart’s upper chambers (atria), causing an irregular and often abnormally fast heart rate. It can be life-limiting, causing problems including dizziness, breathlessness and fatigue, and is linked to a fivefold increase in the risk of stroke.
Lead author Dr Michele Orini (UCL Institute of Cardiovascular Science) said: “Our study suggests that ECGs from consumer wearables can help detect and prevent future heart disease.
“The next step is to explore how screening people using wearables might work best in practice.
“Such screening could potentially be combined with the use of artificial intelligence and other computer tools to quickly identify ECGs indicating higher risk, as we did in our study, leading to a more accurate assessment of risk in the population and helping to reduce burden.” these diseases.”
Lead author Professor Pier D. Lambiase (UCL Institute of Cardiovascular Science and Barts Heart Centre, Barts NHS Health Trust) said: “Being able to identify people at risk of heart failure and arrhythmias at an early stage would mean we could assess for higher risk. cases more effectively and help prevent cases by early treatment and lifestyle advice on the importance of regular, moderate exercise and diet.”
In an EKG, sensors attached to the skin are used to detect the electrical signals produced by the heart each time it beats. In a clinical setting, at least 10 sensors are placed around the body and the recordings are looked at by a medical expert to see if there are signs of a possible problem. Consumer wearables rely on two sensors (one-wire) built into one device and are less cumbersome as a result, but can be less accurate.
For the new paper, the research team used machine learning and an automated computer tool to identify recordings with extra beats. These extra beats were classified as either premature ventricular contractions (PVCs), coming from the lower chambers of the heart, or premature atrial contractions (PACs), coming from the upper chambers.
Recordings for which extra times were detected, and some recordings that were not judged as extra recordings, were then reviewed by two experts to ensure that the classification was correct.
The researchers first looked at data from 54,016 participants in the UK Biobank project, with a median age of 58, whose health was followed for an average of 11.5 years after their ECGs were recorded. They then looked at a second group of 29,324 participants with a median age of 64 who were followed for 3.5 years.
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