A pharmacoeconomic evaluation of the myocardial ischemia reduction with aggressive cholesterol lowering (MIRACL) study in Canada.
Bibliographic record
Abstract
OBJECTIVE: To determine a 16-week total healthcare cost and the cost-effectiveness of short-term, lipid-lowering therapy with atorvastatin 80 mg following acute coronary syndrome (ACS) in Canada. METHODS: The expected costs per patient on atorvastatin 80 mg per day and placebo were compared using clinical outcome data from the MIRACL study and cost data from the Ontario Case Costing Project and the Ontario Schedule of Benefits. The cost per event avoided was also assessed. The clinical outcomes measured included: death, cardiac arrest, non-fatal myocardial infarction (MI), fatal MI, angina pectoris, stroke, congestive heart failure, and surgical or percutaneous coronary revascularizations. All direct medical costs from the perspective of the Canadian health care system were taken into account. RESULTS: The total expected cost per patient was 2,590 dollars in the placebo group and 2,639 dollars in the atorvastatin group. The incremental cost of atorvastatin treatment (49.26 dollars per patient) corresponded to a cost of 1,285 dollars per event avoided. The cost savings obtained through the reduction in events offset 86% of the cost of atorvastatin treatment. Budget impact analysis revealed that increased rates of atorvastatin usage following ACS were associated with large numbers of events avoided at a small additional cost when projected to the Canadian population. CONCLUSIONS: In Canada, the clinical benefits of intensive short-term atorvastatin treatment administered within 96 hours after ACS were associated with a favorable cost-effectiveness ratio. The incremental cost of atorvastatin is mostly offset by savings due to the reduction in events in patients treated with atorvastatin.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".