Open Reduction and Internal Fixation of Mandibular Fractures in a Nonhospital Surgical Facility: Retrospective Chart Review.
Bibliographic record
Abstract
BACKGROUND: Many patients with mandibular fracture need treatment with open reduction and internal fixation (ORIF). These patients are typically treated in hospital, as either inpatients or day surgery patients. However, it is possible to perform these surgeries in a nonhospital surgical facility (NHSF). In this study, we review the outcomes of ORIF surgery for mandibular fracture performed in an NHSF. METHODS: A retrospective chart analysis was conducted for all patients with mandibular fracture who were referred, between 2019 and 2024, to an NHSF in Edmonton, Alberta, Canada, for ORIF. Data were collected for patient- and injury-related variables, including cause of trauma; fracture location; time from injury and diagnosis to ORIF; time in the operating room and post-anesthesia care unit (PACU); complication rates for nausea, vomiting, pain or bleeding in the PACU; rates of same-day discharge, hardware failure, non-union and infection; and length of postoperative follow-up. A cost analysis was also conducted. RESULTS: A total of 69 patients with mandibular fracture who underwent ORIF as day surgery in an NHSF met the inclusion criteria. The mean times from injury to ORIF and from fracture diagnosis to ORIF were 6.0 and 2.5 days, respectively. The mean times spent in the operating and recovery rooms were 61.6 and 62.2 minutes, respectively. All of the patients were discharged home, and no patients experienced surgical or anesthesia complications requiring transfer to a hospital. The cost analysis showed that performance of ORIF was more cost-effective in an NHSF than in hospital. CONCLUSION: These preliminary data are the first in Canada suggesting that for selected cases of mandibular fracture, ORIF in an NHSF is efficient, safe and cost-effective, provided stringent patient selection criteria and postoperative protocols for discharge are followed.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".