Cost-effectiveness of cryoballoon ablation for the management of paroxysmal atrial fibrillation
Bibliographic record
Abstract
AIMS: Cryoballoon ablation is an established treatment option for the management of patients with atrial fibrillation. We sought to evaluate the cost-effectiveness of cryoablation, compared with second-line anti-arrhythmic drug (AAD) therapy in patients with paroxysmal atrial fibrillation (PAF), from a UK payer perspective. METHODS AND RESULTS: We developed a state-transition (Markov) model to calculate the total costs and quality-adjusted life-years (QALYs) associated with cryoablation and AAD therapy in patients with PAF. A 5-year horizon was used for the base-case. Data from a recent study of cryoballoon ablation in patients with PAF were used to model short-term health outcomes and costs, together with longer term external evidence to populate subsequent time periods. Total discounted costs were £21 162 and £17 627 for the cryoballoon ablation and AAD arms, respectively. Total QALYs of 3.565 and 3.404 therefore led to an incremental cost-effectiveness ratio of £21 957 per QALY gained. Sensitivity analysis suggested that the key drivers of the results were the model time horizon, the costs of follow-up care in patients with recurrent AF, and the costs of the ablation procedure. CONCLUSION: Cryoballoon ablation provides increased quality-adjusted life expectancy compared with AAD at reasonable additional cost, representing good value for money in patients with PAF.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".