Occupational outcomes following mild traumatic brain injury in Canadian military personnel deployed in support of the mission in Afghanistan: a retrospective cohort study
Bibliographic record
Abstract
OBJECTIVE: Deployment-related mild traumatic brain injury (MTBI) occurs in a significant number of military personnel but its long-term impacts are unclear. This study explores the impact of deployment-related MTBI on continued fitness-for-duty, with the ultimate intent of identifying potential targets for intervention to attenuate its effects. PARTICIPANTS: Consisted of 16 193 Canadian Armed Forces (CAF) personnel who deployed in support of the mission in Afghanistan and completed an enhanced postdeployment screening (EPDS) questionnaire over the period January 2009-July 2012. PRIMARY OUTCOME: The primary outcome was development of permanent medical unfitness defined as a 'career-limiting medical condition' (CL-MC). The secondary outcome was the diagnostic categories recorded for each individual at the time a CL-MC was established. DESIGN: This study used a retrospective cohort design. Linked administrative and health data provided the primary outcome and the diagnoses responsible for it. Survival analysis was used to estimate the risk of a CL-MC and Cox regression provided adjusted HRs (aHRs) for the association between a CL-MC and MTBI, accounting for key covariates and confounders. Diagnostic categories associated with CL-MCs were identified. RESULTS: Over a median follow-up period of 3.42 years, 6.57% of the study population developed a CL-MC. MTBI was independently associated with CL-MCs (aHR=1.65, 95% CI 1.35 to 2.03). Mental disorders and musculoskeletal conditions were the primary diagnoses associated with CL-MCs (identified as the primary diagnosis in 55.4% and 25.9%, respectively), and a neurological condition was only documented in 5.8% of those with MTBI who developed a CL-MC CONCLUSIONS: Deployment-related MTBI was associated with adverse occupational outcome but mental disorders and musculoskeletal conditions primarily drove subsequent medical unfitness. These findings support a diagnostic and treatment approach focusing on these comorbidities as the most promising strategy to minimise the burden of disability in MTBI-exposed military personnel.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".