Traumatic spinal injuries in children at a single level 1 pediatric trauma centre: report of a 23-year experience
Bibliographic record
Abstract
BACKGROUND: With a reported incidence of up to 10% compared to all spinal trauma, spinal injuries in children are less common than in adults. Children can have spine fractures with or without myelopathy, or spinal cord injuries without radiological abnormalities (SCIWORA). METHODS: We retrospectively reviewed the cases of children with spinal injuries treated at a level 1 pediatric trauma centre between 1990 and 2013. RESULTS: A total of 275 children were treated during the study period. The mean age at admission was 12 ± 4.5 years, and the male:female ratio was 1.4:1. Spinal injuries were more common in children of ages 12-16 years, with most injuries among ages 15-16 years. The top 3 mechanisms of spinal injury were motor vehicle-related trauma (53%), sports (28%) and falls (13%). Myelopathy occurred in 12% and SCIWORA occurred in 6%. The most common spine levels injured were L2-sacrum, followed by O-C2. Associated injuries, including head injuries (29%), and fractures/dislocations (27%) occurred in 55% of children. Overall mortality was 3%. Surgical intervention was required in 14%. CONCLUSION: The creation of a pediatric spinal injury database using this 23-year retrospective review helped identify important clinical concepts; we found that active adolescent boys had the highest risk of spine injury, that noncontiguous spine injuries occured at a rate higher than reported previously and that nonaccidental spine injuries in children are underreported. Our findings also emphasize the importance of maintaining a higher index of suspicion with trauma patients with multiple injuries and of conducting detailed clinical and radiographic examinations of the entire spine in children with a known spinal injury.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".