A comparison of single-lead atrial pacing with dual-chamber pacing in sick sinus syndrome
Bibliographic record
Abstract
AIMS: In patients with sick sinus syndrome, bradycardia can be treated with a single-lead pacemaker or a dual-chamber pacemaker. Previous trials have revealed that pacing modes preserving atrio-ventricular synchrony are superior to single-lead ventricular pacing, but it remains unclear if there is any difference between single-lead atrial pacing (AAIR) and dual-chamber pacing (DDDR). METHODS AND RESULTS: We randomly assigned 1415 patients referred for first pacemaker implantation to AAIR (n = 707) or DDDR (n = 708) pacing and followed them for a mean of 5.4 ± 2.6 years. The primary outcome was death from any cause. Secondary outcomes included paroxysmal and chronic atrial fibrillation, stroke, heart failure, and need for pacemaker reoperation. In the AAIR group, 209 patients (29.6%) died during follow-up vs. 193 patients (27.3%) in the DDDR group, hazard ratio (HR) 1.06, 95% confidence interval (CI) 0.88-1.29, P = 0.53. Paroxysmal atrial fibrillation was observed in 201 patients (28.4%) in the AAIR group vs. 163 patients (23.0%) in the DDDR group, HR 1.27, 95% CI 1.03-1.56, P = 0.024. A total of 240 patients underwent one or more pacemaker reoperations during follow-up, 156 (22.1%) in the AAIR group vs. 84 (11.9%) in the DDDR group (HR 1.99, 95% CI 1.53-2.59, P < 0.001). The incidence of chronic atrial fibrillation, stroke, and heart failure did not differ between treatment groups. CONCLUSION: In patients with sick sinus syndrome, there is no statistically significant difference in death from any cause between AAIR pacing and DDDR pacing. AAIR pacing is associated with a higher incidence of paroxysmal atrial fibrillation and a two-fold increased risk of pacemaker reoperation. These findings support the routine use of DDDR pacing in these patients. CLINICAL TRIAL REGISTRATION: URL http://www.clinicaltrials.gov. Unique identifier: NCT00236158.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".