A Decision Analysis of Percutaneous Left Atrial Appendage Occlusion Relative to Novel and Traditional Oral Anticoagulation for Stroke Prevention in Patients with New-Onset Atrial Fibrillation
Bibliographic record
Abstract
BACKGROUND: Percutaneous left atrial appendage occlusion (LAAO) is a nonpharmacologic approach for stroke prevention in nonvalvular atrial fibrillation (NVAF). No direct comparisons to novel oral anticoagulants (OACs) exists, limiting decision making on the optimal strategy for stroke prevention in NVAF patients. Addressing this gap in knowledge is timely given the recent debate by the US Food and Drug Administration regarding the effectiveness of LAAO. OBJECTIVE: To assess the cost-effectiveness of LAAO and novel OACs relative to warfarin in patients with new-onset NVAF without contraindications to OAC. DESIGN: A cost-utility analysis using a patient-level Markov micro-simulation decision analytic model was undertaken to determine the lifetime costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratio (ICER) of LAAO and all novel OACs relative to warfarin. Effectiveness and utility data were obtained from the published literature and cost from the Ontario Drug Benefits Formulary and Case Costing Initiative. RESULTS: Warfarin had the lowest discounted QALY (5.13 QALYs), followed by dabigatran (5.18 QALYs), rivaroxaban and LAAO (5.21 QALYs), and apixaban (5.25 QALYs). The average discounted lifetime costs were $15 776 for warfarin, $18 280 for rivaroxaban, $19 156 for apixaban, $20 794 for dabigatran, and $21 789 for LAAO. Apixaban dominated dabigatran and LAAO and demonstrated extended dominance over rivaroxaban. The ICER for apixaban relative to warfarin was $28 167/QALY. Apixaban was preferred in 40.2% of simulations at a willingness-to-pay threshold of $50 000/QALY. LIMITATIONS: Assumptions regarding clinical and methodological differences between published studies of each therapy were minimized. CONCLUSIONS: Apixaban is the most cost-effective therapy for stroke prevention in patients with new-onset NVAF without contraindications to OAC. Uncertainty around this conclusion exists, highlighting the need for further research.
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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 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".