Abstract 15554: Three-Year Incidence of Pacemaker Implantation in Patients With Atrial Fibrillation and Sinus Node Dysfunction Receiving Ablation versus Antiarrhythmic Drugs
Bibliographic record
Abstract
Introduction: Around one in five patients with atrial fibrillation (AF) has a diagnosis of sinus node dysfunction (SND). Hypothesis: There will be lower incidence of pacemaker implantation (PPM) among patients with AF and SND who undergo catheter ablation (CA) compared to anti-arrhythmic drugs (AAD). Methods: Data were collected from 2014-2022 utilizing Optum Clinformatics database, an administrative claims database for commercially insured and Medicare Advantage beneficiaries in the United States. Adult patients with concomitant AF and SND, and prior history of taking at least one AAD were identified and classified into CA or AAD cohort based for subsequent treatment. Patients were excluded if they had a prior history of PPM, implantable cardiac defibrillator, catheter or surgical ablation, AV nodal ablation, valvular procedure, left atrial appendage occlusion, or high grade/complete heart block. Inverse probability treatment weighting technique was applied to balance sociodemographic and clinical comorbid characteristics between the cohorts. Weighted Cox regression model was used to evaluate the differential risk of incident PPM. Sub-analyses were performed by AF type (paroxysmal and persistent AF). Results: There were 1,206 patients in AAD cohort and 1,624 patients in CA cohort. Incidence rate (per 1,000 person-year) of PPM was 55.8 (95% CI 47.1-64.5) for CA cohort and 117.8 (95% CI 101.7-133.9) for AAD cohort and the 3-year cumulative incidence of PPM was 23.1% (95% CI 20.0%-26.2%) and 13.8% (95% CI 11.6%-15.9%), respectively. Weighted Cox regression model indicated that CA had 43% lower risk of incident PPM compared to AADs (hazard ratio [HR] 0.57; 95% CI 0.46-0.71). Those with paroxysmal AF (HR 0.48; 95% CI 0.34-0.69) had lower need for PPM compared to persistent AF (HR 0.57; 95% CI 0.40-0.81). Conclusions: Patients with AF and SND treated with CA were observed to have significantly lower risk of incident pacemaker implantation compared to those who had AAD.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".