Pacemaker Mode Selection:
Bibliographic record
Abstract
The evidence base for pacing, specifically with regards to outcome-based randomized trials, is only beginning to emerge. At present, the guidelines for pacing in sinus node dysfunction (SND), atrioventricular block (AVB), and vasovagal syncope are largely based on observational, not randomized studies. The findings from observational studies that physiological pacing was associated with reduced mortality, fewer strokes, less heart failure, and less AF when compared with ventricular pacing, were not uniformly supported by the early randomized trials of a relatively small sample size. Thus, it has become increasingly clear that large scale randomized trials are necessary to measure reliably the benefit, if any, of progressively more expensive and complex pacemakers. To provide reliable answers to these important questions, three large multicenter randomized trials in Canada, the United Kingdom, and the United States have been designed and conducted. The present review analyzed the results of completed randomized trials on pacemaker mode selection. To date, > 6,000 patients requiring permanent pacing to prevent bradycardia have been randomized; among these, dual chamber pacing did not prevent stroke or improve survival when compared with ventricular pacing. However, dual chamber pacing led to a moderate reduction of incident and chronic AF, reduced symptoms of heart failure in patients with SND, prevented pacemaker syndrome, and modestly improved quality-of-life. Further, a 5-10% reduction in mortality by atrial-based pacing cannot be excluded based on the results of the analyzed trials. The availability of data from ongoing randomized trials and their meta analysis should complete the totality of evidence during the next several years.
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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 | 0.009 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".