Clinical Predictors of Arrhythmia Recurrences Following Pulmonary Vein Antrum Isolation for Atrial Fibrillation: Predicting Arrhythmia Recurrence Post-PVAI
Bibliographic record
Abstract
INTRODUCTION: Pulmonary vein antrum isolation (PVAI) is an accepted treatment for atrial fibrillation (AF) refractory to medical therapy. The purpose of this study was to identify the patient, procedural, and follow-up factors associated with arrhythmia recurrences following PVAI. METHODS AND RESULTS: Clinical data were prospectively collected on all 385 consecutive patients who had 530 PVAI (age 58 ± 11 years, 63% paroxysmal AF-PAF, follow-up 2.8 ± 1.2 years) between February 2004 and March 2009. ECGs were recorded at each follow-up visit with Holter monitoring 1, 3, 6, and 12 months following PVAI and every 6 months thereafter. Recurrences < 3 months post-PVAI were defined as early, 3 months-1 year post-PVAI as late, and > 1 year post-PVAI as very late. Relationship between predictor variables and outcomes was modeled using Cox proportional hazards analysis. Late recurrences occurred in 42% with a lower rate among PAF versus non-PAF patients (39% vs 56%, P = 0.001). Of the 256 patients with ≥ 1-year follow-up, 121 (47%) had no arrhythmia off antiarrhythmic drugs (AADs) 1 year post-PVAI; 36 (30%) of these had a very late recurrence. In multivariate analysis, non-PAF, hypertension, and prior AAD failure predicted recurrence. When entered into the model, early recurrences remained the only predictor of late recurrences. CONCLUSION: Patients with non-PAF, hypertension, and prior failure of multiple AAD were more likely to experience arrhythmia recurrence post-PVAI. Early recurrences were the strongest predictor of late recurrences. Late and very late recurrences following PVAI were common and should be considered when planning long-term AF patient management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".