Severe Traumatic Brain Injury in a Large Canadian Health Region
Bibliographic record
Abstract
Background: Although severe traumatic brain injury (sTBI) is a devastating condition with tremendous public health implications, the epidemiology of this disease has not previously been described in Canada. We sought to define the incidence, risk factors and outcome of patients suffering sTBI in a large Canadian region. Methods: A population-based surveillance cohort design was utilized to identify all Calgary Heath Region residents who were victims of trauma with an injury severity score ³12. Subsequent application of a specific sTBI case definition defined the final cohort. Results: The annual incidence of sTBI was 11.4 per 100,000 population. The incidence of sTBI was significantly higher for males as compared to females [17.1 vs. 5.9 per 100,000; relative risk (RR) = 2.91, 95% confidence interval; 2.17, 3.94; p<0.0001]. There was a striking increase in the annual age specific population incidence of sTBI observed among those older than 74 years of age. The relative risk among the highest risk group of elderly (>85 years) males as compared to the lowest risk female group (50-64 years) was 19.78 (95% CI; 6.27, 62.3; p<0.0001). One hundred and eight patients died prior to hospital discharge for a mortality rate of 5.1 per 100,000 per year. Conclusion: Severe traumatic brain injury is common among residents of the Calgary Health Region and is associated with a high mortality rate. Males and the elderly are at the highest risk for acquiring sTBI and may represent target groups for preventive efforts. Conclusion: Les lÉsions cÉrÉbrales par traumatisme crânien sÉvère sont frÉquentes parmi les rÉsidents de la rÉgion sanitaire de Calgary et sont associÉes à une mortalitÉ ÉlevÉe. Les hommes et les personnes âgÉes sont les groupes les plus à risque et constituent des groupes cibles pour les interventions à visÉe prÉventive.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".