Re-Evaluating the Field Tourniquet for the Canadian Forces
Bibliographic record
Abstract
OBJECTIVE: To determine the best field tourniquet for Medical Technician (Med Tech) use in the Canadian Forces (CF). METHODS: We conducted a prospective controlled trial, comparing the efficacy and ease of applicability of 3 types of commercially available windlass tourniquets in 4 tactical situations on simulated patients. The primary outcome was time to tourniquet application with secondary outcomes including effectiveness and Med Tech satisfaction. RESULTS: The overall finding of this study indicates that the Combat Application Tourniquet (C-A-T) was applied the fastest in each scenario and was also significantly the most effective in occluding distal blood flow. The survey results show that the 3 tourniquet types are similar in many of the measures of ease of learning and application, with the C-A-T scoring highest in self-application and the Special Operations Forces Tactical Tourniquet Wide having the lowest scores for both durability and effectiveness. CONCLUSION: When tested on a group of CF Med Techs, the C-A-T remained the CF field tourniquet of choice, based on the assessed criteria. Although there is inherent bias in the approach of this study, it reflects the process required to determine if a new piece of kit is superior to what is already considered the standard to a trained and equipped military.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".