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.