P1396Incidence and significance of early AF recurrences with the second generation cryoballoon: insights from the STOP-AF post approval study
Bibliographic record
Abstract
On behalf of: STOP AF PAS Study Investigators Funding Acknowledgements: Medtronic Background/Introduction: Early recurrence of atrial fibrillation (ERAF) is common after catheter ablation for atrial fibrillation (AF). ERAF after ablation with the second-generation cryoballoon (CB2) has not been extensively studied. Purpose: The purpose of this analysis was to evaluate the incidence and prognostic significance of ERAF in patients participating in the largest prospective multi-center trial evaluating cryoballoon ablation using CB2. Methods: The STOP-AF post approval study is a prospective, multi-center, non-randomized study designed to provide long-term safety and efficacy data for cryoballoon ablation patients with drug-refractory, recurrent symptomatic paroxysmal AF. ERAF was defined as any recurrence of AF >30 seconds or a repeat AF ablation during the first 90 days of follow-up. Late recurrence (LR) was defined as any documented AF lasting longer than 30 seconds and/or a repeat AF ablation after 90 days. Cox regression was utilized to assess the relationship between ERAF and LR. Results: 344 patients were enrolled and the mean follow-up was 27 ± 9 months. Of these patients, 16% (56/344) experienced ERAF with a mean time to ERAF of 39±30 days. Baseline characteristics of the patients with and without ERAF are reported in the table below. Repeat ablations were performed in 14% (8/56) during the blanking period. LR was significantly associated with ERAF (55% [31/56] LR in ERAF subjects vs. 23% [65/288] LR in non-ERAF subjects, p<0.01). Mean time to LR was shorter in ERAF subjects (251 ± 224 in ERAF, 479 ± 317 days in non-ERAF). Conclusion: ERAF with CB2 occurs in 16% of patients and is significantly associated with LR post ablation and an earlier time to LR. Predictors of AF Recurrence
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".