Incremental Efficacy for Repeat Ablation Procedures for Catheter Ablation of Atrial Fibrillation
Why this work is in the frame
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Bibliographic record
Abstract
Background: Catheter ablation atrial fibrillation (AF) is effective, but 20% to 40% of patients will require a repeat ablation. The role of more than 1 repeat ablation is not well known. Objectives: The purpose of this study was to evaluate the effectiveness and incremental benefits of multiple repeat catheter ablations to treat AF in patients. Methods: We retrospectively included patients who underwent their first, second, third, and fourth AF ablation between 2004 and 2019. They were monitored with a 24-to-48-hour Holter every 3 months postablation the first year and every 6 to 12 months thereafter. Recurrence was defined as documented atrial arrhythmia >30 seconds. Outcomes are analyzed by Kaplan-Meier curves and compared by log rank test. Results: We included a total of 2,194 patients (64% with paroxysmal and 36% with nonparoxysmal AF). Mean age was 71 ± 10 years; 67% were male. After 1 ablation, freedom from AF was 52%. Among those 1,052 patients who had recurrences, 576 (55%) underwent a second ablation, 103 (10%) underwent a third procedure, and 20 (2%) underwent a fourth. Success rates for the second, third, and fourth ablation were 57%, 60%, and 40%, respectively, at 5-year follow-up. After the second ablation, freedom from AF in our entire cohort increased from 52% to 66%, with marginal changes after the third (67%) and fourth (67%) procedures. Conclusions: Although repeated ablations demonstrated significant benefits at the individual level, the success rate may drop off after a third. The overall success of the initial cohort was not significantly influenced by the success rates of multiple follow-up ablations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it