Incidence of Delayed Intracranial Hemorrhage in Children After Uncomplicated Minor Head Injuries
Bibliographic record
Abstract
OBJECTIVES: This study sought to determine the incidence of delayed diagnosis of intracranial hemorrhage in the general population and the proportion of children who presented to emergency departments (EDs) with uncomplicated minor head injuries who received delayed diagnoses of intracranial hemorrhage. METHODS: This was an 8-year, retrospective, cohort study of children <14 years of age who presented to EDs in the Calgary Health Region between April 1992 and March 2000. Cases of uncomplicated minor head injuries and delayed diagnosis of intracranial hemorrhage (intracranial hemorrhage not apparent until > or =6 hours after injury) were identified. RESULTS: An estimated 17,962 children (95% confidence interval [CI]: 17,412-18,511 children) with uncomplicated minor head injuries were evaluated at Calgary Health Region EDs. Two and 8 children were identified as having delayed diagnoses of intracranial hemorrhage with and without delayed deterioration in level of consciousness (Glasgow Coma Scale scores of <15), respectively. The proportions of children with uncomplicated minor head injuries with delayed diagnoses of intracranial hemorrhage with and without deterioration in level of consciousness were approximately 0.00% (0 of 17,962 children [upper limit of 95% CI: 0.02%]) and 0.03% (5 of 17,962 children [95% CI: 0.01%-0.07%]), respectively. On the basis of population data for the Calgary Health Region, the incidences of delayed diagnosis of intracranial hemorrhage with and without deterioration in level of consciousness were 0.14 and 0.57 cases per 100,000 children per year, respectively. CONCLUSIONS: The occurrence of delayed diagnosis of intracranial hemorrhage among children who present with uncomplicated minor head injuries is rare.
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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".