Anticoagulation in atrial fibrillation and implantable cardioverter defibrillator implantation in arrhythmogenic right ventricular cardiomyopathy: need for improving patient selection
Bibliographic record
Abstract
Articles in this series highlight and summarize key papers from the last year.The issue continues with a focus on arrhythmias, which opens with the Fast Track Congress manuscript 'Atrial fibrillation progression after cryoablation vs. radiofrequency ablation: the CIRCA-DOSE trial' by Jason Andrade from the University of British Columbia in Vancouver, Canada, and colleagues. 3][6][7][8][9] Persistent forms of AF are associated with increased rates of thrombo-embolism, heart failure, and death.Catheter ablation modifies the pathogenic mechanism of AF progression.A total of 346 patients with drug-refractory paroxysmal AF were enrolled and randomly assigned to contact force-guided RF ablation (CF-RF ablation), 4-min cryoballoon ablation (CRYO-4), or 2-min cryoballoon ablation (CRYO-2).Implantable cardiac monitors placed at study entry were used for follow-up.The main outcome was the first episode of persistent atrial tachyarrhythmia.Secondary outcomes included atrial tachyarrhythmia recurrence and arrhythmia burden on the implantable monitor.At a median of 944 days, none of 115 patients randomly assigned to CF-RF, 8 of 115 patients assigned to CRYO-4, and 5 of 116 patients assigned to CRYO-2 experienced an episode of persistent atrial tachyarrhythmia (P = .03).A documented recurrence of any atrial tachyarrhythmia ≥30 s occurred in 56, 54, and 63% of patients, respectively; P = .65.Compared with that of the pre-ablation monitoring period, AF burden was reduced by a median of 99.5% with CF-RF, 99.9% with CRYO-4, and 99.1% with CRYO-2 (Figure 1).The authors conclude that catheter ablation of paroxysmal AF using radiofrequency energy is associated with fewer patients developing persistent AF on follow-up as compared with cryoablation.The contribution is accompanied
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".