Venous thromboembolism prophylaxis and the impact of a thrombosis service at a Canadian level 1 trauma centre
Bibliographic record
Abstract
Background: Venous thromboembolism (VTE) is a common and serious complication seen in patients with trauma. Guidelines recommend the routine use of pharmacologic prophylaxis; however, compliance rates vary widely. The aim of this study was to describe the clinical practice related to VTE prophylaxis in the first 24 hours after injury at our level 1 Canadian trauma centre and the impact of a thrombosis consultation service. Methods: We performed a retrospective review of the health records of adult patients with trauma admitted between Jan. 1, 2012, and June 30, 2013. The rate of VTE was ascertained. The use of an initial prophylactic regimen, potential contraindications to prophylaxis and involvement of the thrombosis service were determined. Results: A total of 633 patients were included, 459 men and 174 women with a mean age of 47.4 years. The mean Injury Severity Score was 15.8. The overall VTE rate was 2.8%. A total of 514 patients (81.2%) received VTE prophylaxis, mechanical in 302 (47.7%) and pharmacologic in 231 (36.5%) (19 patients received both types). The thrombosis service was involved in the care of 164 patients (25.9%). Patients seen by the thrombosis service were more likely to receive VTE prophylaxis than those not seen by the service (145 [88.4%] v. 369 [78.7%], p < 0.01). Conclusion: Compliance with VTE prophylaxis administration was suboptimal, and opportunities for improvement exist. The involvement of a thrombosis consultation service appears to improve compliance with VTE prophylaxis, and augmented use of this service may improve clinical outcomes.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".