Predictors of atrial fibrillation in patients with dual-chamber pacemakers: insights from the Canadian study on spontaneous atrioventricular conduction preservation (CAN-SAVER)
Bibliographic record
Abstract
Controversies still exist whether algorithms aiming at minimizing unnecessary ventricular pacing help prevent the development of atrial fibrillation in dual-chamber pacemaker recipients. Methods: The CAN-SAVE R study is a Canadian multi-centre randomized study that compared the efficacy the SafeR™ mode with DDD pacing with a long AV delay in a large population of pts not presenting with permanent high degree AV Block (AVB) or permanent atrial fibrillation (AF). The primary objective was to compare % of VP and the impact on AF. Results: 373 patients from10 centres were included: 63% males, mean age= 71±10 years, LVEF= 50±5%, LAVol= 24±3mL. Pacing indications were Sinus Node dysfunction (SND) (47%), AV block (24%), SND + AV block (14%) and other (mainly syncope: 15%). After 3 years, 353 pts (95%) completed their follow-up. Overall, median %VP was 9.5% in the DDD group vs. 0.0% in the SafeR group. This difference in %VP did not affect AF burden (median 0.01% vs. 0.00% respectively). However, patients with previous history of AF, mitral valve disease, dilated left atrium and programmed to DDD mode (vs. SAFE-R™) were more likely to be in persistent AF at the end of 3-year follow-up (table). Predictors for being in permanent AF after 3 years of follow-up (odds ratio and 95% confidence intervals) Conclusions: CAN-SAVER failed to show benefits in terms of AF burden with a diminution of %VP from 9.5% (DDD with long AV delay) to 0.0% (SafeR™ mode). However, when evaluated in terms of risk to develop permanent AF, SafeR™ mode appears to provide some protection compared to DDD pacing with long AV delays.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".