A population-based study of potential brain injuries requiring emergency care.
Bibliographic record
Abstract
BACKGROUND: Brain injury is an important health concern, yet there are few population-based analyses on which to base prevention initiatives. This study aimed, first, to calculate rates of potential brain injury within a defined Canadian population and, second, to describe the external causes, natures and disposition from the emergency department of these injuries. METHODS: We studied all cases of blunt head injury that resulted in a visit to an emergency department for all residents of Greater Kingston during 1998. We used data from the Canadian Hospitals Injury Reporting and Prevention Program (CHIRPP) and augmented this by examining all records of emergency or inpatient care received at all hospitals in the area. RESULTS: In 202 (27%) of 760 cases of head injury, there was potential for brain injury. Annual rates of potential brain injury were 16 and 7 per 10,000 population for males and females respectively. CT was performed on 114 (56%) of 202 cases, of which 60 (53%) demonstrated an intracranial pathology, with 11 (10%) showing a diffuse axonal injury pattern on the initial scan. Falls from heights accounted for 14 (47%) of 30 injuries observed in children aged 0-9 years. Individuals aged 10-44 years sustained 32 (63%) of 51 motor vehicle injuries, 15 (88%) of 17 bicycle injuries, 22 (100%) of 22 sports injuries and 8 (89%) of 9 fight-related injuries. Falls accounted for 15 (71%) of 21 injuries among adults aged 65 years or more. INTERPRETATION: The results indicate the relative importance of several external causes of injury. The findings from our geographically distinct population are useful in establishing rational priorities for the prevention of brain injury.
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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".