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Updated: Mar 2, 2026

Non-fluoroscopic Catheter Tracking for Fluoroscopy Reduction in Interventional Electrophysiology
Published on: May 26, 2015
Very early recurrence predicts long-term outcome in patients after atrial fibrillation catheter ablation: a
Yangjing Xue1, Xiaoning Wang2, Saroj Thapa1
1Department of Cardiology, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Xueyuanxi Road, No 109, Wenzhou, Zhejiang, 325000, China.
Background:
Long-term recurrence (LR) is a tendency that re-occurs within 3 months after catheter ablation for atrial fibrillation (AF). Whether very early recurrence (VER) within 7 days of post ablation is a prognostic factor of LR or not is unclear. For this reason, present study sought to examine the relationship between VER and LR.
Methods:
In this prospective analysis 378 consecutive patients underwent an initial catheter ablation for paroxysmal or persistent AF. The association between VER and LR was analyzed by univariate and multivariate Cox regression, as well as time-dependent receiver operator characteristic (ROC) analysis.
Results:
After a mean follow-up of 14.71 ± 8.58 months, 81 (65.90%) patients with VER experienced LR and were associated with lower event of free survival from LR (Log rank test, P < 0.001). Multivariate Cox regression analysis revealed that VER (HR = 7.02, 95% CI = 4.78-10.31; P < 0.001), left atrial enlargement (HR = 2.92, 95% CI = 1.88-4.54; P < 0.001), tendency in advanced age (HR = 1.50, 95% CI = 0.99-2.28; P = 0.054), and tendency in male (HR = 0.71, 95% CI = 0.50-1.01; P = 0.060) were independent predictors of LR. According to time-dependent ROC analysis, it was found that VER was more sensitive than common risk factors in predicting LR (0.74 vs 0.66, P < 0.001) and combination model further improved the C statistic for predicting LR (0.82 vs 0.66, P < 0.001).
Conclusions:
After a single procedure of catheter ablation, patients with VER were strongly associated with LR and combination of VER and common risk factors could further improve prediction of patients who were at high risk for LR.
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