Voltage-Guided Ablation for Atrial Fibrillation -- Current Insights and Future Directions
Bibliographic record
Abstract
The prevalence of atrial fibrillation (AF) is forecasted to increase manifold, emphasizing the need for efficacious treatments. Pulmonary vein isolation (PVI) to eliminate ectopic triggers is now established as a fundamental component of the invasive treatment of AF, however its efficacy in persistent AF remains suboptimal. The atrial myocardium undergoes adverse fibrotic remodeling as AF progresses, favoring arrhythmia initiation and maintenance. Reductions in left atrial bipolar voltage have been suggested to identify regions of such pathological remodeling, and represent novel targets for ablation to target the arrhythmogenic substrate. Early observational studies targeting these low voltage areas (LVA) have been encouraging, however results from more recent randomized trials are more mixed. Importantly, there is significant heterogeneity in the techniques for identifying LVAs and the strategies for ablation. In reality, the atrial arrhythmogenic substrate is multi-faceted rather than being limited to fibrosis and there remains uncertainty as to how accurately LVAs represent regions of fibrosis. Additionally, bipolar voltage is influenced by numerous physiological and biophysical factors. The present review summarizes the current evidence for LVA ablation in AF. We then analyze the components of the atrial arrhythmic substrate, its relationship to LVAs and the limitations in LVA assessment. Finally we discuss novel techniques for delineating the atrial substrate.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".