Clinical and economic impact of first-line or drug-naïve catheter ablation and delayed second-line catheter ablation for atrial fibrillation using a patient-level simulation model
Bibliographic record
Abstract
AIMS: To determine the clinical and economic implications of first-line or drug-naïve catheter ablation compared to antiarrhythmic drugs (AADs), or shorter AADs-to-Ablation time (AAT) in atrial fibrillation (AF) patients in France and Italy, using a patient level-simulation model. MATERIALS AND METHODS: A patient-level simulation model was used to simulate clinical pathways for AF patients using published data and expert opinion. The probabilities of adverse events (AEs) were dependent on treatment and/or disease status. Analysis 1 compared scenarios of treating 0%, 25%, 50%, 75% or 100% of patients with first-line ablation and the remainder with AADs. In Analysis 2, scenarios compared the impact of delaying transition to second-line ablation by 1 or 2 years. RESULTS: Over 10 years, increasing first-line ablation from 0% to 100% (versus AAD treatment) decreased stroke by 12%, HF hospitalization by 29%, and cardioversions by 45% in both countries. As the rate of first-line ablation increased from 0% to 100%, the overall 10-year per-patient costs increased from €13,034 to €14,450 in Italy and from €11,944 to €16,942 in France. For both countries, the scenario with no delay in second-line ablation had fewer AEs compared to the scenarios where ablation was delayed after AAD failure. Increasing rates of first-line or drug-naïve catheter ablation, and shorter AAT, resulted in higher cumulative controlled patient years on rhythm control therapy. LIMITATIONS: The model includes assumptions based on the best available clinical data, which may differ from real-world results, however, sensitivity analyses were included to combat parameter ambiguity. Additionally, the model represents a payer perspective and does not include societal costs, providing a conservative approach. CONCLUSION: Increased first-line or drug-naïve catheter ablation, and shorter AAT, could increase the proportion of patients with controlled AF and reduce AEs, offsetting the small investment required in total AF costs over 10 years in Italy and France.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".