Cardiovascular Outcomes With Atrial-Based Pacing Compared With Ventricular Pacing
Bibliographic record
Abstract
BACKGROUND: Several randomized trials have compared atrial-based (dual-chamber or atrial) pacing with ventricular pacing in patients with bradycardia. No trial has shown a mortality reduction, and only 1 small trial suggested a reduction in stroke. The goal of this review was to determine whether atrial-based pacing prevents major cardiovascular events. METHODS AND RESULTS: A systematic review was performed of publications since 1980. For inclusion, trials had to compare an atrial-based with a ventricular-based pacing mode; use a randomized, controlled, parallel design; and have data on mortality, stroke, heart failure, or atrial fibrillation. Individual patient data were obtained from 5 of the 8 identified studies, representing 95% of patients in the 8 trials, and a total of 35 000 patient-years of follow-up. There was no significant heterogeneity among the results of the individual trials. There was no significant reduction in mortality (hazard ratio [HR], 0.95; 95% confidence interval [CI], 0.87 to 1.03; P=0.19) or heart failure (HR, 0.89; 95% CI, 0.77 to 1.03; P=0.15) with atrial-based pacing. There was a significant reduction in atrial fibrillation (HR, 0.80; 95% CI, 0.72 to 0.89; P=0.00003) and a reduction in stroke that was of borderline significance (HR, 0.81; 95% CI, 0.67 to 0.99; P=0.035). There was no convincing evidence that any patient subgroup received special benefit from atrial-based pacing. CONCLUSIONS: Compared with ventricular pacing, the use of atrial-based pacing does not improve survival or reduce heart failure or cardiovascular death. However, atrial-based pacing reduces the incidence of atrial fibrillation and may modestly reduce stroke.
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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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".