Incidence and Significance of Early Recurrences of Atrial Fibrillation After Cryoballoon Ablation
Bibliographic record
Abstract
BACKGROUND: Early recurrence of atrial fibrillation (ERAF) is common after radiofrequency catheter ablation for AF. We sought to determine the incidence and prognostic significance of ERAF after cryoballoon ablation. Moreover, the benefit of early reablation for ERAF after cryoballoon ablation is undetermined. METHODS AND RESULTS: The Sustained Treatment of Paroxysmal Atrial Fibrillation (STOP AF) trial randomized 245 patients with paroxysmal AF to medical therapy versus cryoballoon-based pulmonary vein ablation. Patients were followed for 12 months. ERAF was defined as any recurrence of AF >30 seconds during the first 3 months of follow-up. Late recurrence (LR) was defined as any recurrence of AF >30 seconds between 3 and 12 months. Of the 163 patients randomized to cryoablation, 84 patients experienced ERAF (51.5%). The only significant factor associated with ERAF was male sex (hazard ratio [HR], 2.18; 95% confidence interval [CI], 1.03-4.61; P=0.041). LR was observed in 41 patients (25.1%), and was significantly related to ERAF (55.6% LR with ERAF versus 12.7% without ERAF; P<0.001). Among patients with ERAF, only current tobacco use (HR, 3.84; 95% CI, 1.82-8.11; P<0.001) was associated with LR. Conversely, early reablation was associated with greater freedom from LR (3.3% LR with early reablation versus 55.6% without; HR, 0.04; 95% CI, 0.01-0.32; P=0.002). CONCLUSIONS: ERAF after cryoballoon ablation occurs in ≈50% of patients and is strongly associated with LR. Early reablation for ERAF is associated with excellent long-term freedom from recurrent AF.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".