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Updated: Apr 3, 2026

Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
Published on: July 20, 2022
Contributions of Biological Aging to Longitudinal Incidence and Dynamic Progression of Atrial Fibrillation: A
Zhixing Fan1,2,3,4, Xinyi Liu1,2,3, Hui Wu1,2,3
1Department of Cardiology, The First College of Clinical Medical Sciences, China Three Gorges University, 443003 Yichang, Hubei, China.
Background:
The role of biological aging in the progression of atrial fibrillation (AF) remains unclear. Therefore, the present study aimed to investigate the influence of biological aging markers on transitions from health to AF, complications, and death.
Methods:
Two UK Biobank datasets were analyzed: 260,198 participants for the Klemera-Doubal method for biological age (KDM-BA) and PhenoAge analyses, and 339,603 for telomere length analyses, excluding those with AF, complications (heart failure, myocardial infarction, cerebral infarction, dementia, and arterial embolic diseases) at baseline. The present study employed a multi-state model to evaluate the associations between biological aging markers and the progression of AF. Mediation analyses were utilized to assess the role of systemic inflammation.
Results:
During the follow-up period, 9.51-9.67% of patients in the two datasets developed AF, among whom 17.59-17.85% progressed to complications, with 8.20-10.83% of these patients dying from AF-related complications. In comparison with Q1, Q4 of the KDM-BA and PhenoAge analyses was associated with elevated risks across transitions, particularly from baseline to AF (hazard ratios (HR): 1.09, 95% confidence interval (CI): 1.04-1.14; HR: 1.30, 95% CI: 1.25-1.35), baseline to death (HR: 1.10, 95% CI: 1.04-1.16; HR: 1.11, 95% CI: 1.06-1.16), and AF to complication (HR: 1.75, 95% CI: 1.58-1.94; HR: 1.52, 95% CI: 1.37-1.68). Moreover, Q4 of the telomere length analyses showed protective effects against AF onset (HR: 0.83, 95% CI: 0.80-0.86), progression to complications (HR: 0.78, 95% CI: 0.72-0.84), and from baseline to death (HR: 0.91, 95% CI: 0.88-0.94). Systemic inflammation was associated with up to 29.95% of these associations.
Conclusions:
Associations were found between biological aging markers (higher KDM-BA and PhenoAge, and shorter telomere length) and the risk of AF transitions, particularly with respect to an increased risk of AF and progression to complications. These findings underscore the importance of biological age in AF risk stratification and prevention.
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