Age-related trends in severe injury hospitalization in Canada
Bibliographic record
Abstract
BACKGROUND: We performed a population-based evaluation of age-related trends in severe injury hospitalization across Canada. METHODS: We identified hospitalizations following severe injury (Injury Severity Score [ISS] > 15) between 2002 and 2009 using the Canadian National Trauma Registry. Age-standardized severe injury hospitalization rates were calculated using the direct method referencing the 2006 Canadian population. The annual percent change in hospitalization rates were estimated using negative binomial regression. RESULTS: During the 8-year period, hospitalization rates for severe injury rose by 22% among individuals 65 years or older, compared with 10% among individuals younger than 65 years. Fall-related injuries accounted for 46% of all severe injury hospitalizations and increased by an average of 3% annually, with a twofold higher annual rate of increase among the elderly. Case-fatality rates declined by 10%, with the decline more than threefold higher among younger patients. CONCLUSION: Elderly patients accounted for an increasing proportion of hospitalizations, highlighting important opportunities for injury prevention among this age group. Case-fatality rates, while declining among younger patients, remained stable in the elderly population, suggesting the need for better strategies to manage the complex care needs of these patients. LEVEL OF EVIDENCE: Epidemiologic study, level III.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".