Built environment safety: epidemiology of head and brain injury and fractures from stair falls in Canada
Bibliographic record
Abstract
Background Falls are overtaking traffic injuries as the leading cause of not only injury hospitalisation, but also death. Stairs are of special interest for prevention by design, being subject to building codes. Objectives To assess importance and determinants of stair as causes of death and hospitalisation in Canada and a major rural-small urban region in the British Columbia interior. Methods National and provincial mortality and hospitalisation databases were used to compare determinants and trends of external cause W10 with other falls, grouping nature of injury codes for W10 by head and brain trauma and limb fractures. Results In Canada, stair-related deaths averaged 280/year and 0.9/100 000 person years in 32 000 000 population during 2000–2008, accounting for 63% of inter-level fall deaths, 25% of known and 13% of all fall causes. There were about 10 000 stair-related hospitalisations/year, 36 : 1 hospitalisations:deaths. The British Columbia Interior Health Region had 2586 hospitalisations, 3.5/1000 person years in 750 000 population during 2002–2010; 54% were females, with 46% females and 54% males <65 years-old. Head injuries represented 12% of hospitalisations, extremity fractures most others. Males 5–64-years-old accounted for most severe head injuries, including subdural and epidural haematomas. Stairs were the leading specified cause of head injury, exceeding road crashes. Significance Stairs are a key built-environment issue, especially for homes. With victims younger than for most falls, disability can be prolonged. Building codes should provide automatic passive protection for all ages by mandating step geometry including deeper treads and short uniform risers, graspable handrails, and high vertical barriers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".