Ventricular Pacing or Dual-Chamber Pacing for Sinus-Node Dysfunction
Bibliographic record
Abstract
BACKGROUND: Dual-chamber (atrioventricular) and single-chamber (ventricular) pacing are alternative treatment approaches for sinus-node dysfunction that causes clinically significant bradycardia. However, it is unknown which type of pacing results in the better outcome. METHODS: We randomly assigned a total of 2010 patients with sinus-node dysfunction to dual-chamber pacing (1014 patients) or ventricular pacing (996 patients) and followed them for a median of 33.1 months. The primary end point was death from any cause or nonfatal stroke. Secondary end points included the composite of death, stroke, or hospitalization for heart failure; atrial fibrillation; heart-failure score; the pacemaker syndrome; and the quality of life. RESULTS: The incidence of the primary end point did not differ significantly between the dual-chamber group (21.5 percent) and the ventricular-paced group (23.0 percent, P=0.48). In patients assigned to dual-chamber pacing, the risk of atrial fibrillation was lower (hazard ratio, 0.79; 95 percent confidence interval, 0.66 to 0.94; P=0.008), and heart-failure scores were better (P<0.001). The differences in the rates of hospitalization for heart failure and of death, stroke, or hospitalization for heart failure were not significant in unadjusted analyses but became marginally significant in adjusted analyses. Dual-chamber pacing resulted in a small but measurable increase in the quality of life, as compared with ventricular pacing. CONCLUSIONS: In sinus-node dysfunction, dual-chamber pacing does not improve stroke-free survival, as compared with ventricular pacing. However, dual-chamber pacing reduces the risk of atrial fibrillation, reduces signs and symptoms of heart failure, and slightly improves the quality of life. Overall, dual-chamber pacing offers significant improvement as compared with ventricular pacing.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.003 | 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".