Epidemiology of Maxillofacial Injuries at Trauma Hospitals in Ontario, Canada, Between 1992 and 1997
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to review the epidemiology of maxillofacial skeletal injuries in severely injured patients admitted to trauma hospitals in Ontario, Canada, with an Injury Severity Score > 12. METHODS: The Ontario Trauma Registry was accessed to examine the epidemiology of maxillofacial skeletal injuries in severely injured patients treated at 12 trauma hospitals in the province of Ontario, Canada, between 1992 and 1997. Data were collected prospectively, and a descriptive analysis was performed to determine the pattern of maxillofacial injuries, including patient age, sex distribution, etiology of injury, time of injury, and injury profile. RESULTS: There were 2,969 patients that met the inclusion criteria. The median age was 25 years, and men were injured at a 3:1 ratio over women. Most severely injured patients with maxillofacial fractures were injured as a result of motor vehicle collision (70%), with only 33% of the patients restrained with a seat-belt. The temporal distribution of injuries showed that most injuries occurred during evening hours, on weekends, and in the summer. The largest number of fractures was found in the maxilla and orbital bones. The Injury Severity Score of the patients in this study ranged from 13 to 75, with a median of 25. The injury most commonly associated with maxillofacial fractures was injury to the head and neck area. Of patients with injury to the head and neck, most had an altered level of consciousness or injuries to the skull, brain, or cranial vessels. CONCLUSION: Many severely injured patients have maxillofacial injuries. Long-term collection of epidemiologic data regarding maxillofacial fractures is important for the evaluation of existing preventative measures and useful in the development of new methods of injury prevention. Furthermore, insight into the epidemiology of facial fractures and concomitant injuries is an integral component in evaluating the quality of patient care, developing optimal treatment regimens, and making decisions regarding appropriate resource and manpower allocations.
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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 | 0.000 |
| 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) | 0.003 | 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