Cost-effectiveness of rivaroxaban versus enoxaparin for the prevention of postsurgical venous thromboembolism in Canada
Bibliographic record
Abstract
This study aimed to evaluate the cost-effectiveness of prophylaxis with rivaroxaban vs. enoxaparin in the prevention of venous thromboembolism (VTE) after total hip replacement (THR) and total knee replacement (TKR) from the perspective of the Canadian healthcare system. A model was developed that included both acute VTE (represented as a decision tree) and long-term complications (represented as a Markov process with one-year cycles). Transition probabilities were derived from phase III clinical trials comparing rivaroxaban with enoxaparin and published literature. Costs were derived from the Ontario Case Costing Initiative and publicly available sources. Utilities were derived from published literature. The model reported VTE event rates, quality-adjusted life expectancy and direct medical costs over a five-year horizon. Costs are reported in 2007 Canadian Dollars (C$). When rivaroxaban and enoxaparin are compared in patients undergoing THR, rivaroxaban dominates enoxaparin. That is, rivaroxaban is associated with improved health outcomes as measured by increased quality-adjusted life years (QALYs; 0.0006) and fewer symptomatic VTE events (0.0061), and also with lower cost (savings of C$300) per patient. Similarly, rivaroxaban dominates enoxaparin in patients undergoing TKR, achieving a gain of 0.0018 QALYs, a reduction of 0.0192 symptomatic venous thromboembolic events and savings of C$129 per patient. Rivaroxaban is a cost-effective alternative to enoxaparin for VTE prophylaxis in patients undergoing THR and TKR. Over a five-year horizon, rivaroxaban dominated enoxaparin in the prevention of VTE events in patients undergoing THR and TKR, providing more quality-of-life benefit at a lower cost.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".