Further information

Atrial fibrillation (AF) is a common cause of stroke, especially ischemic stroke. Until today all available data demonstrating a beneficial effect by oral anticoagulation for stroke prevention have been collected and documented in populations by conventional ECG screening. It is known that the mayority of AF episodes is undiagnosed ("silent AF") and many of these patients have a stroke as the first clinical symptom of AF. In fact, 5% of stroke patients have unknown AF when enroling into a stroke unit and another 5% show undiagnosed paroxysmal AF within a 72-hours ECG monitoring.

Earlier treatment with anticoagulation could prevent stroke and systemic embolism and reduce cardiovascular mortality in patients. The known risk of bleeding associated with anticoagulation therapy must be considered, which is estimated at 2-4% per year with oral anticoagulants without vitamin K antagonists (NOACs). Long-term ECG monitoring, and in particular rhythm monitoring with implanted devices for an unlimited period of time, can detect atrial arrhythmia (AA) including atrial fibrillation (AF). For constant monitoring, it is uncertain, whether these biological signals (atrial arrhythmias detected by constant monitoring) identify a group of patients who benefit from oral anticoagulation. For patients with implanted devices, this is currently being tested in the NOAH – AFNET 6 and ARTESiA studies.

Only a minority of the population has an implanted device and most of the vulnerable population do not have access to proper health care. Therefore there is a social need to test the initiation of anticoagulation using monitoring that is accessible to a larger part of the population in risk. There are more smartphones than people worldwide. Smartphones and increasingly wearables are widely used in the population and can be used to detect rhythm disturbances, although with limited specificity and sensitivity compared to medical devices.

Existing studies evaluating smartphone-based screening on AF use “opportunistic screening” in a polulation that already have a smartwatch. They do screening on younger, technologically savvy and wealthier population. Screening for undetected AF is required in an eldely population with cardiovascular diseases, where the risk of AF is higher and there is an increased risk of AF-related complications. Therefore, we propose to test the hypothesis that a low-threshold, accessible screening can detect AA in elderly people as at-risk population, when provided a wristband in combination with a solid algorithm for analyzing biosignals from smartphones and wearables.