Predictors of atrial fibrillation recurrence after ablation in holter measurements
EP Europace Journal

Abstract
Atrial fibrillation (AF) is a prevalent cardiac arrhythmia associated with increased morbidity and mortality. Pulmonary vein isolation (PVI) is an effective treatment for AF; however, recurrence after ablation remains a significant clinical challenge. Identifying predictors of AF recurrence is essential for optimising post-ablation patient management. Holter monitoring provides continuous electrocardiographic data and may reveal patterns predictive of recurrence.
To identify predictors of AF recurrence after ablation by analyzing post-operative Holter monitoring data.
We conducted a retrospective study involving patients who underwent PVI for AF. The dataset included intervention details, clinical history, and echocardiographic parameters collected from 2020 to 2024. We excluded those Holter recordings, where a recurrence of AF was observed. We analyzed Holter measurements during two 4-hour segments during daytime ("peri-noon", 10:00–14:00) and night time ("peri-midnight", 22:00–02:00). From these segments, we calculated heart rate variability (HRV) and P-wave, PR-interval duration distribution.
A total of 92 patients had Holter monitoring within the three-year follow-up period. AF recurrence was observed in 30 patients. P-wave duration during the night significantly predicted AF recurrence, with a univariate Cox regression hazard ratio (HR) of 1.60 (95% confidence interval [CI]: 1.09–2.34; p = 0.017). A longer PR interval during both day and night periods predicted recurrence (day: HR 1.87 [95% CI: 1.33–2.63], night: HR 1.80 [95% CI: 1.25–2.60]; p < 0.001). From the HRV data, the 80th percentile of normal-to-normal (NN) intervals was the most important predictor (HR 1.76 [95% CI: 1.19–2.61]; p = 0.004).
Easily obtainable parameters from Holter ECG recordings may significantly contribute to the prediction of atrial fibrillation recurrence after pulmonary vein isolation. Furthermore, analyzing samples from different time periods of the day may have distinct predictive power. In particular,a longer P-wave duration during the peri-midnight period and a longer PR interval in both the peri-midnight and the peri-noon samples showed a correlation with AF recurrence.

