Fixed-Dose, Weight-Adjusted, Unfractionated Heparin (UFH) Given Subcutaneously (sc) without Laboratory Monitoring for Acute Treatment of Venous Thromboembolism (VTE): Randomized Comparison with Low-Molecular-Weight-Heparin (LMWH).
Bibliographic record
Abstract
Abstract Background: Treatment of VTE with UFH is usually by intravenous (iv) infusion with adjustment of dose in response to the activated partial thromboplastin time (APTT). However, (1) there is no evidence that adjusting UFH in response to APTT results reduces recurrent VTE or bleeding if patients are receiving an appropriate dose of UFH, and (2) sc UFH might be preferable to iv UFH. We hypothesized that UFH is as effective and safe as LMWH when each is administered sc in weight-adjusted, fixed-doses. Methods: We performed a multicentre, randomized, open-label, trial that compared fixed-dose UFH (first dose 333 u/kg sc, then 250 u/kg sc twice-daily) with fixed-dose LMWH (100 u/kg sc twice-daily) for initial treatment of acute VTE. Patients were followed for 3 months during which they received warfarin (target INR 2.0–3.0). Outcomes were adjudicated by a blinded committee. Results: 703 patients who presented with acute DVT (81%) or PE (19%) were enrolled and received study drug (68% entirely as outpatients). Of the 352 LMWH patients, 74% received dalteparin and 26% received enoxaparin. Recurrent VTE occurred in 13 (3.8%) UFH and 12 (3.4%) LMWH patients in the 3 months (difference of 0.3%; 95% CI, −2.6 to 3.3%). Major bleeding occurred in 4 (1.1%) UFH and 5 (1.4%) LMWH patients in the first 10 days (difference of −0.3%; 95% CI, −2.3 to 1.7%), and a total of 6 (1.7%) UFH and 12 (3.4%) LMWH patients at 3 months. 18 (5.2%) UFH and 22 (6.3%) LMWH patients died. Conclusion: Fixed-dose sc UFH is as effective and as safe as fixed-dose sc LMWH for treatment of acute VTE. Our findings: (1) support the use of fixed-dose sc UFH as a convenient and inexpensive alternative to LMWH; and (2) question the need for APTT monitoring of UFH therapy.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".