Led by researchers from the cardAIc group at the University of Birmingham, the team used artificial intelligence to help analyse over 140 million datapoints for heart rate in 53 individuals over 20 weeks. They found that digoxin and beta-blockers had a similar effect on heart rate, even after accounting for differences in physical activity. This was in contrast to previous studies that had only assessed the short-term impact of digoxin.
A neural network that took account of missing information was developed to avoid an over-optimistic view of the wearable data stream. Using this approach, the team found that the wearables were equivalent to standard tests often used in hospitals and clinical trials that require staff time and resources. The average age of participants in the study was 76 years, highlighting possible future value regardless of age or experience with technology.
Professor Dipak Kotecha from the Institute of Cardiovascular Sciences at the University of Birmingham and the lead author of the study said:
“People across the world are increasingly using wearable devices in their daily lives to help monitor their activity and health status. This study shows the potential to use this new technology to assess the response to treatment and make a positive contribution to the routine care of patients.”
“Heart conditions such as atrial fibrillation and heart failure are expected to double in prevalence over the next few decades, leading to a large burden on patients as well as substantial healthcare cost. This study is an exciting showcase for how artificial intelligence can support new ways to help treat patients better.”
The study was funded as part of the BigData@Heart consortium from the European Union’s Innovative Medicines Initiative. The RATE-AF trial was funded by the UK National Institute for Health and Care Research.