Researchers from the Stanford University School of Medicine today presented preliminary results of the Apple Heart Study, an unprecedented virtual study with over 400,000 enrolled participants.
Researchers from the Stanford University School of Medicine today presented preliminary results of the Apple Heart Study, an unprecedented virtual study with over 400,000 enrolled participants. The researchers reported that wearable technology can safely identify heart rate irregularities that subsequent testing confirmed to be atrial fibrillation, a leading cause of stroke and hospitalization in the United States.
The study was launched with sponsorship by Apple Inc. in November 2017 to determine whether a mobile app that uses data from a heart-rate pulse sensor on the Apple Watch can identify atrial fibrillation. The condition often remains hidden because many people don’t experience symptoms.
Key findings from the study include:
- Overall, only 0.5 percent of participants received irregular pulse notifications, an important finding given concerns about potential over-notification.
- Comparisons between irregular pulse-detection on Apple Watch and simultaneous electrocardiography patch recordings showed the pulse detection algorithm (indicating a positive tachogram reading) has a 71 percent positive predictive value. Eighty-four percent of the time, participants who received irregular pulse notifications were found to be in atrial fibrillation at the time of the notification.
- One-third (34 percent) of the participants who received irregular pulse notifications and followed up by using an ECG patch over a week later were found to have atrial fibrillation. Since atrial fibrillation is an intermittent condition, it’s not surprising for it to go undetected in subsequent ECG patch monitoring.
- Fifty-seven percent of those who received irregular pulse notifications sought medical attention.
Read more at Stanford University
Image: Examples of the notifications that participants in the Apple Heart Study receive.
Courtesy of Apple