Tracheostomy scar management by repositioning platysma muscle and applying an acellular dermal substitute
Bibliographic record
Abstract
BACKGROUND: A depressed tracheostomy scar can be esthetically unacceptable. We describe a new technique for managing tracheostomy scars using platysma muscle repositioning and the application of an acellular dermal substitute. METHODS: Seventeen patients with depressed tracheostomy scars were identified for scar management. The time between tracheostomy tube removal and scar management was 29 months. Before and after the surgery, the scar was rated using the Vancouver Scar Scale (VSS). RESULTS: After surgery, tracheal tug was eliminated in all patients and the appearance of the scar was much improved. The mean total VSS score improved from 8.265 to 2.324 (P < 0.0001). The follow-up period was 33.3 months. CONCLUSIONS: The management of tracheostomy scars by repositioning platysma muscle and applying an acellular dermal substitute is simple and efficient. The technique recovers the lost deep tissue volume, corrects tracheal skin tug, and enables tension-free skin closure to restore the normal contour of the neck.
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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 | 0.000 |
| 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) | 0.001 | 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".