Functional and Aesthetic Outcome of Reconstructive Surgery for Contracted Neck Scars
Bibliographic record
Abstract
Background: Contracted scars of the neck involving the anterior cervical zone constitute a unique group of challenges compared with post-burn complications in other parts of the body. Many techniques have been advocated for reconstructing neck contractures.Purpose: To determine and recommend the ideal skin cover for neck contracture release defects with regard to both functional and cosmetic outcomes.Methods: A prospective and retrospective cohort study included 20 patients with various degrees of contracted scars of the neck. After releasing contracture band and resection of the unfavorable scarred tissue, remaining defects were surgically reconstructed using multiple Z-Plasties, STSGs, FTSGs and supraclavicular artery island flap with or without prior usage of a tissue expander.Results: Excision and flap group have a higher significant functional outcome than excision with graft and Multiple Z-Plasty groups (p= 0.031). Also, excision and flap have a lower non-significant Vancouver scar scale than other reconstruction methods without significant differences between groups. Excision and flap group have higher Patient Satisfaction score than Excision and graft and Multiple Z-Plasty groups without significant differences between groups.Conclusion: Local and regional flaps especially the supraclavicular artery island flap provide a predictable reconstruction option not only with better color and texture match but also achieves a superior functional outcome.Approval from the Research Ethics Committee in Benha Faculty of Medicine was granted and a fully informed written consents were taken from all patients regarding surgical procedure, photographing, possible complications and follow-up period.Keywords: Post-burn contracture – Contracted neck scar – Neck contracture reconstruction – Supraclavicular flap – Tissue expansion.
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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 | 0.001 |
| 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) | 0.002 | 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".