Combination of Cultured Epidermal Autograft and Meshed Skin Graft Enables Full-thickness Excision of Giant Congenital Nevus
Bibliographic record
Abstract
Giant congenital melanocytic nevus (GCMN) is a skin condition characterized by an abnormally dark, noncancerous skin patch. Two main issues with GCMN are aesthetics and malignant transformation. Various methods of treatment are reported, but each method has its own disadvantages, such as risk of recurrence or restriction in the treatable area. We report three cases of GCMN treated with full-thickness excision and immediately covered with cultured epidermal autograft (CEA) combined with split-thickness skin graft (STSG). This is a single-center, single-arm, retrospective report of three cases. The nevus was excised at full skin thickness. Meshed STSG taken from scalp was grafted to the defect, and CEA was grafted over simultaneously. Two weeks later, CEA was applied again as a booster. The same procedures were performed until all nevi were excised. In all cases, nearly complete epithelialization was achieved at several weeks after operation. The reconstructed skin was elastic, and there was no persistent joint contracture. Vancouver Scar Scale score was 4-8. Mesh-like appearance was observed. A hypertrophic scar appeared in the area without meshed STSG. An intractable keloid was observed in one patient. No recurrence of the nevus was observed during the follow-up period. The donor site scar on the scalp was well hidden by the hair. Our method enables full-thickness resection and reconstruction of a wider area in a single operation while improving the take rate of CEA, with reasonable degree of scarring compared with conventional methods.
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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 | 0.001 |
| 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) | 0.000 | 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".