Epidemiology of Traumatic Spinal Cord Injury in Canada
Bibliographic record
Abstract
STUDY DESIGN: Retrospective review. OBJECTIVE: To describe the incidence, clinical features, and treatment of traumatic spinal cord injury (SCI) treated at a Canadian tertiary care center. SUMMARY OF BACKGROUND DATA: Understanding the current epidemiology of acute traumatic SCI is essential for public resource allocation and primary prevention. Recent reports suggest that the mean age of patients with SCI may be increasing. METHODS: We retrospectively reviewed hospital records on all patients with traumatic SCI between January 1997 and June 2001 (n = 151). Variables assessed included age, gender, length of hospitalization, type and mechanism of injury, associated spinal fractures, neurologic deficit, and treatment. RESULTS: Annual age-adjusted incidence rates were 42.4 per million for adults aged 15-64 years, and 51.4 per million for those 65 years and older. Motor vehicle accidents accounted for 35% of SCI. Falls were responsible for 63% of SCI among patients older than 65 years and for 31% of injuries overall. Cervical SCI was most common, particularly in the elderly, and was associated with fracture in only 56% of cases. Thoracic and lumbar SCI were associated with spinal fractures in 100% and 85% of cases, respectively. In-hospital mortality was 8%. Mortality was significantly higher among the elderly. Treatment of thoracic and lumbar fractures associated with SCI was predominantly surgical, whereas cervical fractures were equally likely to be treated with external immobilization alone or with surgery. CONCLUSION: A large proportion of injuries was seen among older adults, predominantly as a result of falls. Prevention programs should expand their focus to include home safety and avoidance of falls in the elderly.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.002 | 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".