Risk of Stroke and Recurrence After AF Ablation in Patients With an Initial Event‐Free Period of 12 Months
Bibliographic record
Abstract
Stroke and Recurrence After AF Ablation Introduction Because of the unclear prognostic effects of ablation of atrial fibrillation (AF), oral anticoagulation (OAC) is often continued after ablation even in asymptomatic patients. We sought to determine the frequency of stroke and AF recurrence in patients on and off therapeutic OAC 1 year after a successful AF ablation. Methods and Results Patients that underwent AF ablation and were free of AF 12 months after ablation were selected from our AF database. During follow‐up (FU), patients were screened for recurrence of AF, changes in OAC or antiarrhythmic medication, and the occurrence of stroke or transient ischemic attack (TIA). A total of 398 patients (median age 60.7 years [50.8, 66.8], 25% female) were investigated. The median duration of FU was 529 (373, 111,3.5) days. OAC was discontinued in 276 patients (69.3%). During FU, 4 patients (1%) suffered from stroke and 55 patients (13.8%) experienced a recurrence of AF. Persistent AF was significantly associated with a greater chance of AF recurrence (49.1% vs. 26.8%; P = 0.001). Neither CHADS 2 nor CHA2DS2‐VASc‐Score nor recurrence of AF were significantly different in patients with or without stroke. There was a trend toward a higher percentage of coronary artery disease among patients that experienced stroke (50% vs. 10%; P = 0.057). Conclusion The overall risk of stroke and AF recurrence is low in patients with a recurrence free interval of at least 12 months after AF ablation. Of note, recurrence of AF was not associated with a higher risk of stroke in our study population.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".