Cervical Spine Injury in Association with Craniomaxillofacial Fractures
Bibliographic record
Abstract
BACKGROUND: The incidence of cervical spine injuries associated with facial fractures varies from study to study. There is general agreement that immediate management of cervical spine injuries is mandatory to prevent further neurologic injury. Nevertheless, disagreement exists as to the actual incidence of cervical spinal trauma in conjunction with various facial fracture patterns. The purpose of this study was to review the incidence of cervical spine injury associated with various types of facial fractures presenting to St. Michael's Hospital Regional Trauma Center, Toronto, Ontario, Canada. METHODS: The authors conducted a retrospective chart review of craniomaxillofacial fracture patients presenting to St. Michael's Hospital from January 1, 1994, to December 31, 2003, inclusive. RESULTS: The data from this 10-year time span revealed a total of 124 patients with cervical spine injuries drawn from a cohort of 3356 patients with craniomaxillofacial fractures. The overall incidence of cervical spine injury was 3.69 percent. Of these patients, 928 had isolated upper third facial or skull fractures, whereas isolated middle third facial fractures were seen in 716 patients and isolated lower third facial fractures were present in 798 patients. Combined facial fracture patterns, involving two or more facial thirds, accounted for the greatest number of cervical spine injuries, occurring in 8.86 percent (n = 914). CONCLUSIONS: The relationship between cervical spinal injuries and craniomaxillofacial trauma has been better defined as it relates to a regional trauma registry. The implications as related to the trauma assessment, diagnosis, and treatment of these injuries are reviewed.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".