Prevalence, timing, and impact of early recurrence of atrial tachyarrhythmias after pulsed field ablation: A secondary analysis of the PULSED AF trial
Bibliographic record
Abstract
BACKGROUND: Early recurrence of atrial tachyarrhythmias (ERAT) within 3 months of thermal ablation for atrial fibrillation (AF) is common and often considered transient. Pulsed field ablation (PFA) is a nonthermal energy source in which ERAT is not well described. OBJECTIVE: The purpose of this study was to analyze ERAT in patients with AF undergoing PFA in the Pulsed Field Ablation to Irreversibly Electroporate Tissue and Treat AF (PULSED AF) trial. METHODS: This analysis included 154 (52.4%) paroxysmal AF and 140 (47.6%) persistent AF who had ≥10 rhythm assessments during the 90-day blanking period. ERAT was defined as any instance of ≥30 seconds of AF, atrial flutter, or atrial tachycardia on transtelephonic monitoring (weekly and symptomatic) or ≥10 seconds on electrocardiography (at 3 months), both within 90 days. Late recurrence of atrial tachyarrhythmias (LRAT) was defined as observed atrial tachyarrhythmias between 90 days and 12 months. RESULTS: The overall prevalence of ERAT was 27.1% in patients with paroxysmal AF and 31.6% in patients with persistent AF. In patients with ERAT, 73% had ERAT onset within the first month of the procedure. The presence of ERAT was associated with LRAT in patients with paroxysmal AF (hazard ratio 6.4; 95% confidence interval 3.6-11.3) and patients with persistent AF (hazard ratio 3.8; 95% confidence interval 2.2-6.6). Yet, in 29.4% of patients with paroxysmal AF and 34.3% of patients with persistent AF with ERAT, LRAT was not observed. LRAT was positively correlated with the number of ERAT observations. CONCLUSION: ERAT after PFA predicted LRAT in patients with paroxysmal and persistent AF. However, the concept of a blanking period after PFA is still valid, as approximately one-third of patients with ERAT did not continue to have LRAT during follow-up and may not need reablation.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".