Neuropathology of Fatal Falls in Southwestern Ontario
Bibliographic record
Abstract
BACKGROUND: Fall from height is common in all age groups. In 2020 alone, over 6000 people in Canada died from fall-related injuries. Most of the published literature investigating fall-related injuries are often focused on fracture patterns, survival and recovery. Fatal falls are not well studied. The objective of this study is to characterize the demographics and craniocerebral and vertebrospinal injury patterns related to fatal falls within Southwestern Ontario. METHODS: A retrospective case review was conducted at the Department of Pathology, London Health Sciences Centre, for deaths attributed to falls from 2000 to 2020. Only cases with complete autopsy and detailed neuropathology reports were included. Demographic data, comorbidity profiles and craniocerebral and vertebrospinal injuries, along with scene details, were collected and analyzed. RESULTS: 45 cases were included, with a male sex predominance and a mean age of 60.3 ± 18.1 years. The most common head injuries were hematoma, cerebral contusions and skull base fractures. Falls from stairs were the most common. Low fall (<3 m) was associated with subfalcine herniation and was more commonly seen in older individuals (>65 years). Younger individuals were more prone to falls from a high height (>3 m), with frontotemporal lobe contusions as the most common finding. DISCUSSION: This study provides a detailed depiction of craniocerebral and vertebrospinal injury patterns of the fatal falls in Southwestern Ontario. Our findings show low falls are a more common cause of fatalities in individuals 65 years and older, and age is a significant predictor of frontal contusions and subdural hematomas.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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".