Low-Molecular-Weight Heparin Versus Unfractionated Heparin for Prophylaxis of Venous Thromboembolism in Medicine Patients—A Pharmacoeconomic Analysis
Bibliographic record
Abstract
BACKGROUND: Prevention of in-hospital venous thromboembolism (VTE) is identified internationally as a priority to improve patient safety. Advocated alternatives include low-dose unfractionated heparin (UFH) or low-molecular-weight heparin (LMWH). Although LMWHs are as effective as UFH, less frequent administration and potentially safer adverse effect profile associated with LMWHs might off-set greater drug acquisition costs. The objective of this study was to determine the most cost-effective thromboprophylaxis strategy for hospitalized medicine patients and specific subgroups in Canada. METHODS: A decision-analytic model assessed costs and outcomes of LMWH compared to UFH for thromboprophylaxis in at-risk hospitalized medicine patients from an institutional perspective. The outcome of interest was the incremental cost-effectiveness ratio (ICER) for preventing deep vein thrombosis (DVT) and combined untoward events (pulmonary embolism [PE], major bleed, and death). The time horizon of the model was the hospital stay. RESULTS: In the base-case analysis, LMWH thromboprophylaxis resulted in higher costs ($7.40), but 3.6 and 1.1 fewer DVT and untoward events per 1000 patients, respectively, with associated ICERs of $2042 and $6832. Results remained predominantly stable when alternative assumptions were evaluated in the sensitivity analysis. Low-molecular-weight heparin had the most favorable economic profile in patients with a history of DVT. In the probabilistic sensitivity analysis, in 33% of simulations LMWH was less costly and more effective, whereas the reverse was true for UFH only in 13% of simulations. CONCLUSIONS: Low-molecular-weight heparin administration is a cost-effective alternative for thromboprophylaxis strategy in Canadian hospitalized medicine patients.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".