Abstract 13385: Long Term Outcomes in Catheter Ablation of Atrial Fibrillation Compared to Medical Therapy
Bibliographic record
Abstract
Introduction: The long-term effects of catheter ablation (CA) compared to medical therapy on cardiovascular outcomes for atrial fibrillation (AF) remain undetermined. We examined the outcomes associated with CA compared to rate or rhythm control therapy in a population cohort with AF. Methods: Using Alberta administrative data, patients with AF as the primary diagnosis during hospitalization or emergency department/physician visit were included between 2008-2018. Based on therapy received, patients were assigned to CA, rate (digoxin, calcium channel or beta blocker) or rhythm control (amiodarone, sotalol, flecainide, propafenone, dronedarone). If treatment changed over time, the patient was censored in the prior treatment arm and assigned to the new arm. The association of treatment (included as time-varying covariate) with the primary composite outcome of death, hospitalization for heart failure or stroke was examined using multivariable Cox models after adjusting for age, sex, comorbidities and baseline medications. Secondary outcomes included cardiovascular hospitalizations, and individual components of the composite. Results: There were 2,149 (4.0%) patients treated with CA and 51,315 with medical treatment (rate : 41,948, (81.5%) rhythm: 9,367 (18.2%). During a median follow-up of 4.2 years, CA for AF was associated with a lower crude incidence of the composite outcome (rate per 100 person-years was 3.3 for CA, 9.5 for rate control, and 6.3 for rhythm control). In multivariate analysis, compared to CA, both rate (adjusted hazard ratio (aHR) 1.55, 95% confidence interval (CI), 1.44 to 1.68) and rhythm control (aHR 1.37; 95% CI 1.27 to 1.49) were associated with a higher risk of the primary composite outcome.(Figure) Secondary outcomes are shown in the Figure. Conclusions: Only a small percentage of patients with AF undergo CA. Patients selected for CA have a lower risk of long-term adverse outcomes compared to medical therapy in patients with AF.
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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 | 0.003 | 0.007 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".