Airway Management in Pan Facial Fracture: An Outcome Analysis of Elective Tracheostomy and Submental Endotracheal Intubation
Bibliographic record
Abstract
Background and Aims. Pan facial fractures are complex and often requiring complex airway management. Elective tracheostomy (ET) and submental endotracheal intubation (SEI) are the two major techniques for airway management. The aim of this article is to compare the management outcome between these techniques. Methods. This study was done in a tertiary care hospital from Jan 2019 to Dec 2019. Data were retrieved for all patients from hospital admission-discharge reports, operation room records, follow-up notes, and clinical photograph records which was recorded prospectively after ethical clearance. Total 38 patients were included in the study after the exclusion criteria into two groups: submental endotracheal intubation (SEI) and elective tracheostomy (ET). Demographic data, intraoperative time (IOT), length of hospital stay (LOHS), postoperative pain score at three and seven days, and Vancouver Scar Score (VSS) at 4 and 12 weeks was compared between the two groups. Results. SEI consisted of 23 patients (60%) while ET had 15 (40%) patients. The mean age was 32.77±8.24 years in the SEI and 29.36±7.32 years in the ET. The IOT in SEI was 15.36±1.53 min and 24.60±1.40 min in the ET which was statistically significant (p = 0.00001). The LOHS was 11±3.87 days in SEI and 25.2±3.88 days in ET (p = 0.0001). The mean VSS at 4 and 12 weeks for SEI were moderate and mild respectively and for the ET was moderate and mild respectively. Both were statistically significant with a p = 0.003 and p = 0.006. Conclusion. Submental intubation is a safe airway management technique in pan facial fracture. It provides the surgeon with an excellent operative field for achieving the proper dental occlusion. Both short- and long-term outcomes are better compared to the alternative airway method of elective tracheostomy.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".