Causes of Death in Canadian Forces Members Deployed to Afghanistan and Implications on Tactical Combat Casualty Care Provision
Bibliographic record
Abstract
BACKGROUND: As part of its contribution to the Global War on Terror and North Atlantic Treaty Organization's International Security Assistance Force, the Canadian Forces deployed to Kandahar, Afghanistan, in 2006. We have studied the causes of deaths sustained by the Canadian Forces during the first 28 months of this mission. The purpose of this study was to identify potential areas for improving battlefield trauma care. METHODS: We analyzed autopsy reports of Canadian soldiers killed in Afghanistan between January 2006 and April 2008. Demographic characteristics, injury data, location of death within the chain of evacuation, and cause of death were determined. We also determined whether the death was potentially preventable using both explicit review and implicit review by a panel of trauma surgeons. RESULTS: During the study period, 73 Canadian Forces members died in Afghanistan. Their mean age was 29 (+/-7) years and 98% were male. The predominant mechanism of injury was explosive blast, resulting in 81% of overall deaths during the study period. Gunshot wounds and nonblast-related motor vehicle collisions were the second and third leading mechanisms of injury causing death. The mean Injury Severity Score was 57 (+/-24) for the 63 study patients analyzed. The most common cause of death was hemorrhage (38%), followed by neurologic injury (33%) and blast injuries (16%). Three deaths were deemed potentially preventable on explicit review, but implicit review only categorized two deaths as being potentially preventable. CONCLUSIONS: The majority of combat-related deaths occurred in the field (92%). Very few deaths were potentially preventable with current Tactical Combat Casualty interventions. Our panel review identified several interventions that are not currently part of Tactical Combat Casualty that may prevent future battlefield deaths.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".