Continuous EKG Monitoring Using S-Patch Ex : Prospective Observational Study (S-patch Registry)

Atrial fibrillation (AF) is associated with increased mortality and morbidity, and is a dominant, yet preventable, cause of cardioembolic stroke, which has more severe outcomes than other ischaemic stroke causes if left untreated. Approximately 10% of ischemic strokes are associated with AF (AF) first diagnosed at the time of stroke. Detecting asymptomatic AF would provide an opportunity to prevent these strokes by instituting appropriate anticoagulation.

Early diagnosis of AF might enable oral anticoagulant therapy and prevent unwanted consequences of undetected disease, leading to the suggestion that screening for AF might be beneficial in populations at risk. However, there is still debate about whether screen-detected AF bears a similar stroke and mortality risk profile to clinically detected AF, particularly when AF screening is done at a higher intensity than single-time point.

The absence of studies reporting on hard clinical endpoints in AF screening has led to differences in recommendations globally. Most notably, systematic screening for AF is to be considered according to 2020 European guidelines, whereas the US Preventive Services Task Force concluded that current evidence is insufficient to assess the balance of benefits and harms of screening for AF.

The incidence of screen-detected AF strongly depends on the population screened and duration/intensity of screening. Single-time point screening of a general population ≥65 years of age detects undiagnosed AF in 1.4%, and the AF detected is largely persistent. In a large population-based study of individuals 75 to 76 years of age, a more intense 2-week screening program using twice-daily intermittent handheld ECG recordings identified AF in 3.0% (0.5% on the initial ECG4). The identical protocol restricted to those with ≥1 additional stroke risk factor identified 7.4% with AF.

This study was designed in to two arms. The purpose of Arm 1 is to upgrade the artificial intelligence by collecting the continued ECG monitoring data in patients with previous diagnosed AF. The purpose of Arm 2 is to investigate the detection rate of AF using systematic, intensive AF screening with continuous ECG monitoring and the rate of clinical outcome in individuals at high risk during one year follow-up.