Economic impact of enoxaparin versus unfractionated heparin for venous thromboembolism prophylaxis in patients with acute ischemic stroke: A hospital perspective of the PREVAIL trial
Bibliographic record
Abstract
BACKGROUND: The PREVAIL (Prevention of VTE [venous thromboembolism] after acute ischemic stroke with LMWH [low-molecular-weight heparin] and UFH [unfractionated heparin]) study demonstrated a 43% VTE risk reduction with enoxaparin versus UFH in patients with acute ischemic stroke (AIS). A 1% rate of symptomatic intracranial and major extracranial hemorrhage was observed in both groups. OBJECTIVE: To determine the economic impact, from a hospital perspective, of enoxaparin versus UFH for VTE prophylaxis after AIS. DESIGN: A decision-analytic model was constructed and hospital-based costs analyzed using clinical information from PREVAIL. Total hospital costs were calculated based on mean costs in the Premier™ database and from wholesalers acquisition data. Costs were also compared in patients with severe stroke (National Institutes of Health Stroke Scale [NIHSS] score ≥14) and less severe stroke (NIHSS score <14). RESULTS: The average cost per patient due to VTE or bleeding events was lower with enoxaparin versus UFH ($422 vs $662, respectively; net savings $240). The average anticoagulant cost, including drug-administration cost per patient, was lower with UFH versus enoxaparin ($259 vs $360, respectively; net savings $101). However, when both clinical events and drug-acquisition costs were considered, the total hospital cost was lower with enoxaparin versus UFH ($782 vs $922, respectively; savings $140). Hospital cost-savings were greatest ($287) in patients with NIHSS scores ≥14. CONCLUSIONS: The higher drug cost of enoxaparin was offset by the reduction in clinical events as compared to the use of UFH for VTE prophylaxis after an AIS, particularly in patients with severe stroke.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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".