Prevalence and determinants of atrial fibrillation progression in paroxysmal atrial fibrillation

Abstract

Objective: Atrial fibrillation (AF) often progresses from paroxysmal AF (PAF) to more permanent forms. To improve personalised medicine, we aim to develop a new AF progression risk prediction model in patients with PAF.

Methods: In this interim-analysis of the Reappraisal of AF: Interaction Between HyperCoagulability, Electrical Remodelling, and Vascular Destabilisation in the Progression of AF study, patients with PAF undergoing extensive phenotyping at baseline and continuous rhythm monitoring during follow-up of ≥1 year were analysed. AF progression was defined as (1) progression to persistent or permanent AF or (2) progression of PAF with >3% burden increase. Multivariable analysis was done to identify predictors of AF progression.

Results: Mean age was 65 (58-71) years, 179 (43%) were female. Follow-up was 2.2 (1.6-2.8) years, 51 of 417 patients (5.5%/year) showed AF progression. Multivariable analysis identified, PR interval, impaired left atrial function, mitral valve regurgitation and waist circumference to be associated with AF progression. Adding blood biomarkers improved the model (C-statistic from 0.709 to 0.830) and showed male sex, lower levels of factor XIIa:C1-esterase inhibitor and tissue factor pathway inhibitor, and higher levels of N-terminal pro-brain natriuretic peptide, proprotein convertase subtilisin/kexin type 9 and peptidoglycan recognition protein 1 were associated with AF progression.

Conclusion: In patients with PAF, AF progression occurred in 5.5%/year. Predictors for progression included markers for atrial remodelling, sex, mitral valve regurgitation, waist circumference and biomarkers associated with coagulation, inflammation, cardiomyocyte stretch and atherosclerosis. These prediction models may help to determine risk of AF progression and treatment targets, but validation is needed.

Trial registration number: NCT02726698.

Keywords: atrial fibrillation; biomarkers; risk factors.

Conflict of interest statement

Competing interests: US reports grants from Roche Diagnostics, EP Solutions, Dutch Heart Foundation, European Union, personal fees from Roche Diagnostics, EP Solutions, other from YourRhythmics BV, outside the submitted work. In addition, US has a patent Noninvasive classification of AF licensed to YourRhythmics. JDeG reports grants and personal fees from Atricure, Bayer, Daiichi Sankyo, Johnson&Johnson, grants from Boston Scientific, personal fees from Novartis and Servier, outside the submitted work. JL reports consultancy agreement Medtronic. HTC reports grants from Bayer and Pfizer and consultancy agreements for Pfizer, Alveron, STAGO, Leo Pharma, Daiichi Sankyo, Gilead/Galapagos, Portola/Aexia and Coagulation Profile. All other authors have nothing to disclose.

© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.

Figures

Figure 1

Examples of continuous rhythm monitoring. Examples of individual patients without AF progression (group 1 and group 2) and with AF progression (group 3 and 4) during follow-up. The X-axis presents follow-up in years, the Y-axis is the time of the day. Shaded areas indicate nightly hours. Black triangle presents day of end of analysis. White means no AF is present, and blue represents ongoing episodes of AF. AF initiations are shown in red and AF terminations are shown in green. AF, atrial fibrillation.

Figure 2

Flow chart of all patients. Four-hundred seventeen patients were included in current analysis. One patient died during follow-up and was included in the analysis until last rhythm monitoring date. AAD, anti-arrhythmic drugs; AF, atrial fibrillation; ECV, electrical cardioversion; PVI, pulmonary vein isolation.

Figure 3

Predictors of atrial fibrillation (AF) progression in the Reappraisal of AF: Interaction Between HyperCoagulability, Electrical Remodelling, and Vascular Destabilisation in the Progression of AF study. Clinical markers and blood biomarkers as predictors for atrial fibrillation progression and their physiological and pathophysiological mechanisms. The blue boxes represent the multivariable predictors of atrial fibrillation progression. The green boxes represent the physiological mechanisms, the yellow boxes represent the pathophysiological mechanisms. NTproBNP, N-terminal pro-brain natriuretic peptide; PCSK9, proprotein convertase subtilisin/kexin type 9; PGLYRP1, peptidoglycan recognition protein 1; TFPI, tissue factor pathway inhibitor.