Reepithelialization from Stem Cells of Hair Follicles of Dermal Graft of the Scalp in Acute Treatment of Third-Degree Burns
Bibliographic record
Abstract
BACKGROUND: The scalp, an excellent donor site for thin skin grafts, presents a limited surface but is rich in keratinocyte stem cells. The purpose of this study was to double scalp harvesting in one procedure and to evaluate the capacity of the dermal layer to spontaneously reepithelialize from hair follicle stem cells. METHODS: Two layers of 0.2-mm split-thickness skin graft, a dermoepidermal graft and a dermal graft, were harvested from scalp during the same procedure. Fifteen burn patients were included in this study. Healing of the scalp donor site and percentage of graft taken were evaluated. The Vancouver Scar Scale was used at 3 months and 1 year. Histologic studies were performed at day 0 and 3 months on grafts, and on the scalp at day 28. RESULTS: Nine patients were treated on the limbs with meshed dermal graft. Six were treated on the hands with unmeshed dermal graft. Graft take was good for both types of grafts. The mean time for scalp healing was 9.3 days. Histologic study confirmed that the second layer was a dermal graft with numerous annexes and that, at 3 months, the dermis had normal thickness but with rarer and smaller epidermal crests than dermal graft. The difference between the mean Vancouver Scar Scale score of dermal graft and dermoepidermal graft was not significant. CONCLUSION: The authors' study shows the efficacy of dermal graft from the scalp and good scalp healing. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, II.
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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".