Evaluation of Minced Skin Grafts in the Treatment of Post Burn Leukoderma
Bibliographic record
Abstract
Background: Post burn leukoderma had been characterizedby chalk white depigmented areas of variable sizes and shapes.Re-pigmentation of the hypopigmented lesion is still a bigchallenge, current treatment modalities for post burn leukodermainclude non-surgical techniques and many surgicalinterventions.Objective: To evaluate the efficacy of minced skin graftin the treatment of post burn leukoderma.Material and Methods: Twenty Patients (18 female & 2males) with post burn leukoderma were included. Patients'age ranging from 10 to 50 years. The minimum leukodermasurface area was 0.5% whereas the maximum was 3%. Patientswere assessmed one year post operatively using VancouverScar Scale and Patient Observer Scar Assessment Scale(POSAS).Results: Vancouver scar scale results were; Good pigmentationwere obtained in 75%, Hyperpigmentation in 20% andPartial pigmentation was in 5%. For POSAS The overallpatient opinion scale was 1 (which denote best skin colour)in 80%, score 2 in 10%, score 3 in 5%, score 4 in 5% ofpatients.Conclusion: Minced skin graft can be used safely for thetreatment of post burn leukoderma. It is a simple reliabletechnique that can be easily integrated in our daily practice,no need for special instruments or laboratory preparations,gives a satisfactory result for patients with minimal donormorbidity.
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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) | 0.002 | 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".