The Epidemiology of Hospitalized Head Injury in British Columbia, Canada
Bibliographic record
Abstract
OBJECTIVE: This descriptive study seeks to identify the incidence rates of head injuries in a large Canadian province, given incident cases for a ten year period. It describes cases in terms of age standardized rates, demographics, and health care utilization. METHODS: The analyses were done using descriptive statistics. Incidence rates were calculated using the direct method. The indicators of hospital resource utilization were: mean length of hospital stay, number of intensive care unit (ICU) stays, and mean length of stay in an ICU. RESULTS: In the ten year period, British Columbia saw 48,753 admissions due to an incident head injury. The most common head injury diagnosis was an "Intracranial" injury. The year with the highest total age standardized rate was 1991/92 (174.18/100,000). The mean length of hospital stay was 7.4 days. Ten percent had an ICU stay and the mean length of stay was 4.4 days (+/- 4.8). The diagnosis with the longest mean length of stay was a "Fractured Skull" while of the top five E-code categories; "Motor Vehicle Traffic" had the highest mean length of stay with 12.2 days. CONCLUSIONS: Our study provides a much needed analysis of the incidence of head injuries in British Columbia. These rates can be compared to other provinces using the 2001 Canadian population as the standardized population. Our results indicate that there are certain "at risk" groups that warrant attention, in particular, younger men with lower socioeconomic standing. Indicators of health care utilization presented in the study should generate policy discussions.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| 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".