Cost Comparison of Catheter Ablation and Medical Therapy in Atrial Fibrillation
Bibliographic record
Abstract
INTRODUCTION: There is emerging evidence for clinical superiority of catheter ablation over rate and rhythm control strategies in paroxysmal atrial fibrillation (PAF). The objective of this study was to compare costs related to medical therapy versus catheter ablation for PAF in Ontario (Canada). METHODS: Costs related to medical therapy in the analysis included the cost of anticoagulation, rate and rhythm control medications, noninvasive testing, physician follow-up visits, and hospital admissions, as well as the cost of complications related to this management strategy. Costs related to catheter ablation were assumed to include the cost of the ablation tools (electroanatomic mapping or intracardiac echocardiography-guided pulmonary vein ablation), hospital and physician billings, and costs related to periprocedural medical care and complications. Costs related to these various elements were obtained from the Canadian Registry of Atrial Fibrillation (CARAF), government fee schedules, and published data. Sensitivity analyses looking at a range of initial success rates (50-75%) and late attrition rates (1-5%), prevalence of congestive heart failure (CHF) (20-60%), as well as discounting varying from 3% to 5% per year were performed. RESULTS: The cost of catheter ablation ranged from $16,278 to $21,294, with an annual cost of $1,597 to $2,132. The annual cost of medical therapy ranged from $4,176 to $5,060. Costs of ongoing medical therapy and catheter ablation for PAF equalized at 3.2-8.4 years of follow-up. CONCLUSION: Catheter ablation is a fiscally sensible alternative to medical therapy in PAF with cost equivalence after 4 years.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".