A national survey of thromboprophylaxis strategies in high risk trauma patients
Bibliographic record
Abstract
Purpose: The risk of venous thromboembolism (VTE) is very high in trauma patients, and VTE prophylaxis by means of pharmacological anticoagulation has become the standard of care in this patient population. Some patients are unable to receive pharmacological VTE prophylaxis and may be high risk for development of VTE. Contemporary use of mechanical prophylaxis with retrievable inferior vena cava filters (rIVCF) among Canadian trauma centers is unknown. The goal of our survey was to better understand current Canadian practices regarding rIVCF for VTE prophylaxis in this challenging patient population. Methods: An online survey based questionnaire was distributed to 16 Canadian Tertiary Care Trauma Center directors. This survey was hosted on the REDCap platform, and was analysed with REDCap software. Results: Response rate was 88%. Fifty percent of our surveyed centres see > 650 severe (ISS >12) trauma patients annually. All responders prefer low molecular weight heparin for VTE prophylaxis over other modalities. When pharmacological anticoagulation contraindicated, a pneumatic compression device was first line in 79%; rIVCF was first line in 21% of centres. Sixty-five percent of responders agree that the risk of rIVCF outweighs its benefit, however, 86% supported the need for future research in the Canadian trauma population, and 64% agree that sufficient clinical equipoise exists to support randomization for a prospective clinical trial. Conclusions: This survey based investigation of Canadian trauma directors has identified notable practice variation regarding rIVCF use for primary prophylaxis and underscores the need for further investigation of their use in high-risk trauma patients
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".