Epidemiology of traumatic brain injury in children receiving intensive care in the UK
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIMS: To describe the epidemiology of children with traumatic brain injury (TBI) admitted to paediatric intensive care units (PICUs) in the UK. METHODS: Prospective collection of clinical and demographic information from paediatric and adult intensive care units in the UK and Eire between February 2001 and August 2003. RESULTS: The UK prevalence rate for children (0-14 years) admitted to intensive care with TBI between February 2001 and August 2003 was 5.6 per 100,000 population per year (95% Poisson exact confidence intervals 5.17 to 6.05). Children admitted to PICUs with TBI were more deprived than the population as a whole (mean Townsend score for TBI admissions 1.19 v 0). The commonest mechanism of injury was a pedestrian accident (36%), most often occurring in children over 10. There was a significant summer peak in admissions in children under 10 years. Time of injury peaked in the late afternoon and early evening, a pattern that remained constant across the days of the week. Injuries involving motor vehicles have the highest mortality rates (23% of vehicle occupants, 12% of pedestrians) compared with cyclists (8%) and falls (3%). In two thirds of admissions (65%) TBI was an isolated injury. CONCLUSIONS: TBI in children requiring intensive care is more common in those from poorer backgrounds who have been involved in accidents as pedestrians. The summer peak in injury occurrence for 0-10 year olds and late afternoon timing give clear targets for community based injury prevention.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it