Impact of atrial antitachycardia pacing and atrial pace prevention therapies on atrial fibrillation burden over long-term follow-up
Bibliographic record
Abstract
AIMS: Selective atrial pacing algorithms have been developed for prevention of atrial tachycardia/atrial fibrillation (AT/AF). Although short-term studies have shown modest to minimal incremental benefit of these algorithms compared with conventional dual-chamber (DDD/R) pacing for prevention of AT/AF, the long-term effects of these algorithms are unknown. Accordingly, we compared atrial antitachycardia pacing (ATP) therapy and combined atrial ATP and atrial pace prevention (ATP + Prevention) algorithms to conventional DDD/R pacing for prevention of AT/AF over long-term follow-up. METHODS AND RESULTS: Seventy-one patients with AT/AF following pacemaker insertion were randomized to DDD/R pacing, DDD/R plus ATP pacing, or DDD/R plus ATP and prevention pacing and followed for 3 years. Atrial tachycardia/AF burden and an AF symptom scale were compared over time between groups. Atrial tachycardia/AF burden remained stable over 3 years in the DDD/R and ATP + Prevention groups. Atrial tachycardia/AF burden increased significantly over time in the ATP group. Patients not on class I or III antiarrhythmic drug therapy were more likely to experience an increase in AT/AF burden over time. CONCLUSION: Atrial ATP and atrial ATP in combination with atrial pace prevention algorithms do not suppress AT/AF over long-term follow-up compared with DDD/R pacing.
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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 | 0.001 |
| 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".