Economic Impact of Enoxaparin After Acute Ischemic Stroke Based on PREVAIL
Bibliographic record
Abstract
The efficacy and safety of low-molecular-weight heparins (LMWHs) versus unfractionated heparin (UFH) has been demonstrated for the prevention of venous thromboembolism (VTE) after acute ischemic stroke. Few data exist regarding the economic impact of LMWHs versus UFH in this population. A decision-analytic model was constructed using clinical information from the Prevention of VTE after Acute Ischemic stroke with LMWH Enoxaparin (PREVAIL) study, and drug costs and mean Centers for Medicare & Medicaid Services event costs. When considering the total cost of events and drugs, enoxaparin was associated with cost-savings of $895 per patient compared with UFH ($2018 vs $2913). Findings were retained within the univariate and multivariate analyses. From a payer perspective, enoxaparin was cost-effective compared with UFH in patients with acute ischemic stroke. The difference was driven by the lower clinical event rates with enoxaparin. Use of enoxaparin may help to reduce the clinical and economic burden of VTE.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 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".