Low-Molecular-Weight Heparin vs Heparin in the Treatment of Patients With Pulmonary Embolism
Bibliographic record
Abstract
BACKGROUND: Pulmonary embolism (PE) occurs in 50% or more of patients with proximal deep-vein thrombosis. Low-molecular-weight heparin treatment is effective and safe in patients with deep vein thrombosis and may also be so in patients with PE. Recent rigorous clinical trials have established objective criteria for determining a high probability of PE by perfusion lung scanning. OBJECTIVE: To compare low-molecular-weight heparin with intravenous heparin for the treatment of patients with objectively documented PE and underlying proximal deep vein thrombosis. METHODS: In a multicenter, double-blind, randomized trial, we compared fixed-dose subcutaneous low-molecular-weight heparin (tinzaparin sodium) given once daily with dose-adjusted intravenous heparin given by continuous infusion using objective documentation of clinical outcomes. Pulmonary embolism at study entry was documented by the presence of high-probability lung scan findings. RESULTS: Of 200 patients with high-probability lung scan findings at study entry, none of the 97 who received low-molecular-weight heparin had new episodes of venous thromboembolism compared with 7 (6.8%) of 103 patients who received intravenous heparin (95% confidence interval for the difference, 1.9%-11.7%; P = .01). Major bleeding associated with initial therapy occurred in 1 patient (1.0%) who was given low-molecular-weight heparin and in 2 patients (1.9%) given intravenous heparin (95% confidence interval for the difference, -2.4% to 4.3%). CONCLUSIONS: Low-molecular-weight heparin administered once daily subcutaneously was no less effective and probably more effective than use of dose-adjusted intravenous unfractionated heparin for preventing recurrent venous thromboembolism in patients with PE and associated proximal deep vein thrombosis. Our findings extend the use of low-molecular-weight heparin without anticoagulant monitoring to patients with submassive PE.
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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".