Prevalence, burden and manifestation of atrial fibrillation: a large-scale analysis of cardiac patch monitors.

Abstract

Atrial fibrillation (AF) is frequently paroxysmal and asymptomatic, making its detection and burden quantification challenging. The distribution of AF burden across clinically monitored populations remains poorly characterised. We sought to describe the distribution of AF burden and its variation by monitoring indication, symptomatology, arrhythmia characteristics and geography. This study analysed cardiac patch monitor reports collected between May 2017 and July 2023. Analyses were stratified by monitoring indication, AF burden grouping and geography. AF burden subgroups were defined based on the burden detected during recording, and divided into four subgroups: (1) no AF (AF burden=0%); (2) low burden AF (>0 to ≤10%); (3) moderate burden AF (>10% to <100%); and (4) continuous AF (100%). Across 142 346 monitoring reports, AF was detected in 15 678 cases (11.17%), with a median AF burden of 100% (IQR 4.67-100.00). When stratified by monitoring indication, AF was detected in 28.2% of monitors indicated due to suspected or history of AF, 4.5% for stroke/transient ischaemic attack (TIA), 6.5% for syncope/pre-syncope and 4.9% for palpitations. In the stroke/TIA monitoring population, AF detection was time-dependent, with 58.8% of cases identified within 24 hours, increasing to 88.0% identified at 7 days. Among all patients with AF detected, patients with continuous AF (100% AF burden) exhibited lower heart rates and symptom burden compared with those with low (≤10%) and moderate (10% to <100%) AF burden. AF detection was higher in the UK than Canada (12.2% vs 10.9%), as was median burden among detected cases (100.0 vs 55.0%), despite shorter prescribed monitoring durations in the UK (median 48.00 hours (IQR 24.00-168.00) vs 168.00 hours (IQR 168.00-336.00)). In patients undergoing clinically indicated patch monitoring, AF burden varied by monitoring indication, symptomatology and geography, identifying potentially distinct AF subgroups. Characterising AF burden can inform the development and evaluation of AF monitoring and treatment strategies.