Beyond burden metrics: Wearable photoplethysmography-derived spatiotemporal progression of atrial fibrillation linked to clinical outcomes

Background Traditional atrial fibrillation (AF) classification lacks dynamic quantification. Current AF burden assessment is constrained by intermittent monitoring and simplistic metrics. Objective To establish a continuous, multidimensional AF progression model using wearable photoplethysmography (PPG) for real-world, dynamic burden quantification. Methods In this prospective cohort, 110 patients with paroxysmal AF underwent synchronized PPG (Huawei Watch GT3) and 24-hour Holter monitoring. We developed a multi-scale fusion AF algorithm and a five-dimensional (5D) spatiotemporal progression model quantifying episode frequency, duration, clustering, circadian rhythm, and tachycardia burden. Results The fusion algorithm achieved an accuracy of 0.97. The 5D model showed strong concordance with Holter monitoring, with near-perfect correlation for episode duration (r=0.97) and high interchangeability (ICC>0.75). It demonstrated excellent diagnostic performance for burden trajectories (AUC=0.98). A composite AF burden score ≥ 0.59 identified patients at high risk for AF-related symptoms or heart rate issues. Clinically, AF burden increased with worsening EHRA symptoms (p=0.04), varied by risk profile (p=0.03), and differed between ablation and drug-treated patients (episode duration: p