1 Introduction
Atrial fibrillation (AF) is one of the most common arrhythmias, affecting an estimated 33.5 million patients worldwide1. It is a serious public health problem because of its increasing incidence and prevalence in the aging population and its association with elevated risks of cardiovascular events and death2. Catheter ablation is increasingly common in AF treatment because of reduction of symptoms. However, asymptomatic recurrence of AF after ablation is substantial and a frequent monitoring strategy is warranted for early detection of AF episode and subsequent change of medical treatment3.
Asymptomatic AF is difficult to diagnose based on a short electrocardiography (ECG) recording, especially when the episode is paroxysmal. It has been demonstrated that traditional monitoring methods, including ECG and Holter monitoring, may overestimate the effectiveness of catheter ablation4. The portable devices used to monitor AF and artificial intelligence (AI) algorithm applied has the potential to improve accuracy in rhythm monitoring and diagnosis.
We therefore undertook a randomized controlled trial with the portable device versus traditional follow-up strategy in a post-ablation population to evaluate the feasibility and veracity of the self-applied ECG monitoring device in detection of atrial fibrillation.