Very Low Ventricular Pacing Rates Can Be Achieved Safely in a Heterogeneous Pacemaker Population and Provide Clinical Benefits: The CANadian Multi-Centre Randomised Study–Spontaneous
Bibliographic record
Abstract
Background-—It is well recognized that right ventricular apical pacing can have deleterious effects on ventricular function. We performed a head-to-head comparison of the SafeR pacing algorithm versus DDD pacing with a long atrioventricular delay in a heterogeneous population of patients with dual-chamber pacemakers. Methods and Results-—In a multicenter prospective double-blinded randomized trial conducted at 10 centers in Canada, 373 patients, age 7111 years, with indications for dual chamber DC pacemakers were randomized 1:1 to SafeR or DDD pacing with a long atrioventricular delay (250 ms). The primary objective was twofold: (1) reduction in the proportion of ventricular paced beats at 1 year; and (2) impact on atrial fibrillation burden at 3 years, defined as the ratio between cumulative duration of mode-switches divided by follow-up time. Statistical significance of both co-primary end points was required for the trial to be considered positive. At 1 year of follow-up, the median proportion of ventricular-paced beats was 4.0 % with DDD versus 0 % with SafeR (P<0.001). At 3 years of follow-up, the atrial fibrillation burden was not significantly reduced with SafeR versus DDD (median 0.00%, interquartile range [0.00 % to 0.23%] versus median 0.01%, interquartile range [0.00 % to 0.44%], respectively, P=0.178]), despite a persistent reduction in the median proportion of ventricular-paced beats (10 % with DDD compared to 0 % with SafeR). Conclusions-—A ventricular-paced rate <1 % was safely achieved with SafeR in a population with a wide spectrum of indications for dual-chamber pacing. However, the lower percentage of ventricular pacing did not translate into a significant reduction in atrial
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".