Heart Rate Variability and Procedural Outcome in Catheter Ablation for Atrial Fibrillation
Bibliographic record
Abstract
INTRODUCTION: In patients with normal hearts, increased vagal tone is associated with onset of paroxysmal atrial fibrillation (AF). Vagal denervation of the atria renders AF less inducible. Circumferential pulmonary vein isolation (CPVI) is effective for treating paroxysmal and persistent AF, and has been shown to impact heart rate variability (HRV) indices, in turn, reflecting vagal denervation. We examined the impact of CPVI on HRV indices, and evaluated the relationship between vagal modification and AF recurrence. METHODS: Electrocardiogram recordings were collected from 83 consecutive patients (63 male, 20 female, age 56.9 ± 9.3 years) undergoing CPVI for paroxysmal (n = 56) or persistent (n = 27) AF. Recordings were obtained over 10 minutes preprocedure, and at intervals up to 12 months. Antiarrhythmic medications were suspended prior to CPVI, and were resumed for 3 months following. Success was defined as no recurrence of atrial arrhythmia lasting longer than 30 seconds. RESULTS: In patients with successful procedures (n = 56, 42 paroxysmal, 14 persistent), HRV indices were significantly altered, with respect to preprocedure levels, over a sustained period. However, patients with recurrence (n = 27, 14 paroxysmal, 13 persistent) demonstrated similar HRV to their preprocedure levels over the follow-up period. CONCLUSION: Our results suggest that patients experiencing recurrence after a single CPVI have HRV attenuated by the procedure only intermittently, whereas patients with one successful CPVI experience a sustained change. A short-term HRV recording is a convenient and potentially important marker for recurrence of atrial arrhythmia in a population undergoing CPVI.
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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 | 0.003 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".