A danish healthcare-focused economic evaluation of first-line cryoballoon ablation versus antiarrhythmic drug therapy for the treatment of paroxysmal atrial fibrillation
Bibliographic record
Abstract
INTRODUCTION: Three randomised controlled trials (RCTs) have demonstrated that first-line cryoballoon pulmonary vein isolation decreases atrial tachycardia in patients with symptomatic paroxysmal atrial fibrillation (PAF) compared with antiarrhythmic drugs (AADs). The aim of this study was to develop a cost-effectiveness model (CEM) for first-line cryoablation compared with first-line AADs for the treatment of PAF. The model used a Danish healthcare perspective. METHODS: Individual patient-level data from the Cryo-FIRST, STOP AF and EARLY-AF RCTs were used to parameterise the CEM. The model structure consisted of a hybrid decision tree (one-year time horizon) and a Markov model (40-year time horizon, with a three-month cycle length). Health-related quality of life was expressed in quality-adjusted life years (QALYs). Costs and benefits were discounted at 3% per year. Model outcomes were produced using probabilistic sensitivity analysis. RESULTS: First-line cryoablation is dominant, meaning it results in lower costs (-€2,663) and more QALYs (0.18) when compared to first-line AADs. First-line cryoablation also has a 99.96% probability of being cost-effective, at a cost-effectiveness threshold of €23,200 per QALY gained. Regardless of initial treatment, patients were expected to receive ∼ 1.2 ablation procedures over a lifetime horizon. CONCLUSION: First-line cryoablation is both more effective and less costly (i.e. dominant), when compared with AADs for patients with symptomatic PAF in a Danish healthcare system.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".