Predictive value of biomarker dynamics for atrial fibrillation recurrence after pulmonary vein isolation: a prospective cohort study

EP Europace Journal

23 May 2025
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ESC Journals

Abstract

AbstractBackground

Pulmonary vein isolation (PVI) is a primary treatment for atrial fibrillation (AF), yet recurrence of atrial arrhythmia remains common, particularly in patients with persistent AF. Current predictors of AF relapse do not fully account for outcomes, underscoring the need for novel markers to guide post-ablation management.

Purpose

This study aimed to determine if perioperative changes in specific biomarkers related to inflammation and myocardial injury during PVI could predict AF recurrence. We hypothesized that these biomarkers could provide insights into procedural success, potentially indicating lesion transmurality or atrial tissue quality, within a standardized ablation protocol at a high-volume center over one year.

Methods

In this single-center prospective cohort study, 134 patients with paroxysmal or persistent AF undergoing radiofrequency (RF) PVI were enrolled. Biomarkers associated with inflammation (e.g., IL-6, CRP, NLR), myocardial injury (hs-TnT, LDH), and complete blood counts were measured at baseline, post-ablation, and at discharge. Biomarker level changes were indexed to the energy delivered during ablation, termed the "Power to Release Ratio" (PTRr), to refine prediction of procedural success. Patients were monitored for arrhythmia recurrence via regular ECGs and Holter monitoring, with a median follow-up of 166 days.

Results

AF recurrence was observed in 28% of patients during follow-up. Lower increases in hs-TnT (p = 0.023) and mean platelet volume (MPV) (p = 0.025) immediately post-ablation were associated with higher recurrence rates. Troponin changes were more predictive in men, while MPV was more predictive in women. Additionally, lower PTRr increases for LDH and troponin, and higher PTRr increases for iron levels (p = 0.032, 0.012, and 0.025, respectively), predicted AF recurrence, with the overall model showing moderate predictive capability for arrhythmia relapse (R² = 0.45).

Conclusion

Dynamic changes in biomarkers, particularly when indexed to the energy delivered, show good prediction of AF recurrence following RF ablation. These findings could aid in refining risk stratification and enabling more personalized post-ablation therapy. Further research in larger cohorts is recommended to validate these biomarkers and explore their application in other energy-based ablation methods, such as pulse field ablation (PFA), potentially supporting decisions on antiarrhythmic and anticoagulant therapy post-ablation.

ESC 365 is supported by