Traumatic spinal cord injury in military personnel versus civilians: a propensity score-matched cohort study
Bibliographic record
Abstract
INTRODUCTION: Military personnel are exposed to mechanisms of bodily injuries that may differ from civilians. A retrospective cohort study (RCS) and a propensity score-matched cohort study (PSMCS) were undertaken to examine the potential differences in injury epidemiology, management and outcomes after spinal cord injury (SCI) between military personnel and civilians. METHODS: Using a Canadian multicentre SCI database, data of all individuals with sufficient data from October 2013 to January 2017 were included in the RCS (n=1043). In the PSMCS, a group of 50 military personnel with SCI was compared with a group of 50 civilians with SCI who were matched regarding sex, age, and level, severity and mechanism of SCI. RESULTS: In the RCS, military personnel with SCI (n=61) were significantly older and predominantl males when compared with civilians with SCI (n=982). However, the study groups were not statistically different with regards to their: level, severity and mechanisms of SCI; frequency of associated bodily injuries; and need for mechanical ventilation after SCI. In the PSMCS, the group of military individuals with SCI (n=50) was similar to the group of civilians with SCI (n=50) regarding pre-existing medical comorbidities, degree of motor impairment at admission, initial treatment for SCI and clinical and neurological outcomes after SCI. CONCLUSIONS: The results of these studies suggest that military SCI group has disproportionally older men at the time of injury compared with civilians with SCI. However, the military and civilian SCI groups had similar outcomes of alike initial treatment when both groups were matched regarding their demographic profile and injury characteristics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".