A multicenter review of deep venous thrombosis prophylaxis practice patterns for blunt hepatic trauma
Bibliographic record
Abstract
BACKGROUND: Non-operative management of blunt hepatic trauma is successful in the majority of hemodynamically stable patients. Due to the risk of recurrent hemorrhage, pharmacologic deep venous thrombosis (DVT) prophylaxis is often delayed. The optimal timing of prophylaxis is unclear. A multi-centre, retrospective review of patients with blunt hepatic injuries presenting between 2000 and 2004 was performed. All patients had an ISS >/= 12 and a CT scan confirming hepatic trauma. Patients were categorized into: (1) early DVT prophylaxis (</= 48 hrs of admission), (2) delayed prophylaxis (>48 hrs), and (3) no prophylaxis. METHODS AND RESULTS: Thirty-seven (25%) and 45 (42%) patients received early and delayed DVT prophylaxis respectively. The remainder (32%) received none. Mean hepatic injury grades were lower in the early prophylaxis group (II) compared to the delayed and no prophylaxis cohorts (III)(p = 0.002). The number of patients requiring post-admission blood transfusions was highest in the delayed group (44%) compared to the early (26%) and no prophylaxis (6%) groups (p = 0.03). No patient in the early prophylaxis cohort developed a DVT or required delayed angiographic or operative intervention. Two patients in the delayed group failed non-operative management. Eight (18%) patients in the delayed group developed a clinically significant DVT; 1 (2%) progressed to a PE. CONCLUSION: Practice patterns indicate that chemical DVT prophylaxis initiated within 48 hours of admission may be safe in patients with significant blunt hepatic trauma. Delays in prevention result in venothromboembolic events, but not in fewer blood transfusions or a decreased need for subsequent angiographic or operative therapies.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".