Effectiveness of a Standardized Approach to Repeat Paroxysmal Atrial Fibrillation Ablation: Insights Into the Value of Extrapulmonary Vein Targets
Bibliographic record
Abstract
BACKGROUND: The optimal approach to repeat catheter ablation for recurrent paroxysmal atrial fibrillation (PAF) is unknown. METHODS: Consecutive patients undergoing repeat PAF ablation were studied. The following 6-step approach was used in all cases: re-isolation of reconnected pulmonary veins (PVs); ablation of left atrial low-voltage areas (LVAs); targeted ablation of clinical or inducible atrial flutter/tachycardia; non-PV trigger ablation; ablation of inducible supraventricular tachycardia; and additional empirical ablation based on operator judgement. The primary study outcome was atrial arrhythmia-free survival at 1 year. RESULTS: One hundred thirteen patients were included in the study (mean age 63.7 ± 8.6 years, 28.3% women). In this cohort, 73.5% had PV reconnection(s), 31.9% had LVAs, 10.6% had identifiable non-PV triggers, 5.3% had inducible atrioventricular nodal re-entrant tachycardia, 31.9% underwent atrial flutter/tachycardia ablation, and 12.4% had additional empirical ablation performed. Arrhythmia-free survival at 1 year was 53.1%. Patients with arrhythmia recurrence were more likely to be older, female, have hypertension, have durably isolated PVs, and to have undergone LVA ablation. In multivariable analysis, female sex and LVA ablation remained predictive of arrhythmia recurrence. Among patients with durably isolated PVs, only female sex was (negatively) associated with procedural success. CONCLUSIONS: A comprehensive protocol for repeat PAF ablation resulted in arrhythmia-free survival at 1 year in 53% of patients. Durably isolated PVs were observed in 26.5% of cases. None of the ablation protocol's steps was suggested to independently improve procedural success. Further research to determine the optimal ablation strategy in patients undergoing repeat ablation for PAF is needed, a growing proportion of whom are expected to have durably isolated PVs.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".