Targeting nonpulmonary vein triggers during atrial fibrillation ablation
Bibliographic record
Abstract
PURPOSE OF REVIEW: Triggers for atrial fibrillation are found outside the pulmonary veins in 12-20% of cases. The role of addressing these triggers during catheter ablations has not been well defined. Therefore, the aim of this review is to summarize the effect of ablation of nonpulmonary vein triggers in addition to pulmonary vein isolation across the spectrum of atrial fibrillation in patients receiving catheter ablation. RECENT FINDINGS: In paroxysmal atrial fibrillation, an inducible nonpulmonary vein trigger is an independent predictor of recurrence. These triggers are inducible by adenosine and isoproterenol infusion. Nonpulmonary vein triggers cause a significant proportion of atrial fibrillation recurrence seen during repeat procedure and addressing them decreases such recurrence. Targeting inducible nonpulmonary vein triggers also decreases recurrence in persistent atrial fibrillation and was associated with a 25-30% relative reduction in arrhythmia recurrence compared with pulmonary vein isolation alone. In persistent atrial fibrillation, the addition of left atrial appendage isolation was associated with 55% reduction in arrhythmia recurrence. There was no benefit to the empirical ablation of the superior vena cava and the addition of extensive linear lines. There was insufficient evidence to assess the effects of empirical ablation of the coronary sinus, crista terminalis, left atrial posterior wall and the vein of Marshall on arrhythmia recurrence. SUMMARY: Evidence suggests that the presence of an inducible nonpulmonary vein trigger is a strong predictor of arrhythmia recurrence. Efforts to detect and ablate nonpulmonary vein triggers are warranted. Further studies are required to fully identify the role nonpulmonary vein trigger ablation.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".