P60. Presentation And Management of Ballistic Mandibular Fractures
Bibliographic record
Abstract
PURPOSE: Ballistic mandibular fractures can cause devastating injury. However, there is a lack of data regarding their management. Here, we examine the management and outcomes of patients with ballistic mandibular fractures. METHODS: A retrospective study was conducted reviewing patients with firearm-related mandibular injury presenting to a Level 1 Trauma Center from 2018-2023. RESULTS: 90 patients were included. The average age was 29.3 ± 13.2 years and 74 (82.2%) were male. 82 (91.1%) presented post-assault, 6 (6.7%) after self-inflicted injury, and 2 (2.2%) after accidental injury. Body fractures were the most common (40.0%) followed by ramus (25.6%) and angle (13.3%) fractures. 47 patients (52.2%) also had non-facial injuries. On presentation, 68 patients (75.6%) were intubated; 34 (37.8%) of them later required tracheostomy. 40 patients (44.4%) presented with significant bleeding; 14 (15.6%) were taken to the operating room and 8 (8.9%) were taken for embolization. 67 patients (74.4%) required surgical repair; 48 of them (71.6%) were repaired with internal fixation, 16 (23.9%) required bone grafts, 45 (67.2%) were placed in maxillomandibular fixation, and 3 (3.3%) required microvascular reconstruction. 14 patients (15.6%) had complications post-operatively; 2 (2.2%) had wound healing complications, 6 (6.7%) had infection, 3 (3.3%) had exposed hardware, 3 (3.3%) had malunion, and 1 (1.1%) had palatal fistula and carotid-cavernous fistula, respectively. 12 (13.3%) required surgery for complications. Neurologic complications led to mortality in 6 (6.7%) patients. CONCLUSION: Ballistic mandible fractures present a unique challenge. Our study is one of the few to examine management and complications of ballistic mandibular trauma.
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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".