Neck injuries in young pediatric homicide victims
Bibliographic record
Abstract
OBJECT: In this study, the authors estimate the prevalence of injuries to the soft tissue of the neck, cervical vertebrae, and cervical spinal cord among victims of abusive head trauma to better understand these injuries and their relationship to other pathophysiological findings commonly found in children with fatal abusive head trauma. METHODS: The population included all homicide victims 2 years of age and younger from the city of Philadelphia, Pennyslvania, who underwent a comprehensive postmortem examination at the Office of the Medical Examiner between 1995 and 2003. A retrospective review of all available postmortem records was performed, and data regarding numerous pathological findings, as well as the patient's clinical history and demographic information, were abstracted. Data were described using means and standard deviations for continuous variables, and frequency and ranges for categorical variables. Chi-square analyses were used to test for the association of neck injuries with different types of brain injury. RESULTS: The sample included 52 children, 41 (79%) of whom died of abusive head trauma. Of these, 29 (71%) had primary cervical cord injuries: in 21 there were parenchymal injuries, in 24 meningeal hemorrhages, and in 16, nerve root avulsion/dorsal root ganglion hemorrhage were evident. Six children with abusive head trauma had no evidence of an impact to the head, and all 6 had primary cervical spinal cord injury (SCI). No child had a spinal fracture. Six of 29 children (21%) with primary cervical SCIs had soft-tissue (ligamentous or muscular) injuries to the neck, and 14 (48%) had brainstem injuries. There was a significant association of primary cervical SCI with cerebral edema (p = 0.036) but not with hypoxia-ischemia, infarction, or herniation. CONCLUSIONS: Cervical SCI is a frequent but not universal finding in young children with fatal abusive head trauma. In the present study, parenchymal and/or root injury usually occurred without evidence of muscular or ligamentous damage, or of bone dislocation or fracture. Moreover, associated brainstem injuries were not always seen. Although there was a significant association of primary cervical cord injury with cerebral edema, there was no direct relationship to brainstem herniation, hypoxia-ischemia, or infarction. This suggests that cervical spinal trauma is only 1 factor in the pathogenesis of these lesions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".