Erbium: YAG laser treatment efficacy and association with histologic features for giant congenital melanocytic nevi management
Bibliographic record
Abstract
BACKGROUND: Limited research exists on laser treatment of giant congenital melanocytic nevus (GCMN). OBJECTIVE: We sought to elucidate the efficacy of the Erbium: YAG laser on GCMN and the histologic factors associated with a positive clinical response. METHODS AND MATERIALS: Between 2019 and 2022, we enrolled 30 medium-to-giant CMN patients who underwent Er: YAG laser treatment. All patients received biopsies before and after laser treatments. Clinical efficacy outcomes were evaluated by the investigator's global assessment (IGA), 5-point scale of depigmentation, and Vancouver Scar Scale (VSS) scores at least 6 months after treatment. RESULTS: Of the 30 cases, 18 (60.0%) showed improvement (IGA score ≥3). Eight (26.7%) patients showed repigmentation. Eight (26.7%) patients developed hypertrophic scars. The average IGA, depigmentation, and VSS scores were 2.93, 3.57, and 3.20. The IGA score was higher (3.24 ± 1.18 vs. 2.22 ± 0.97, p = 0.031) and a lower repigmentation rate (14.3% vs. 55.6%, p = 0.032) was observed in the cases with Grenz zone. The IGA score was higher (3.33 ± 1.24 vs. 2.13 ± 0.89, p = 0.023) and the repigmentation rate was lower (11.1% vs. 50.0%, p = 0.034) also in the cases with the melanocytes nests with aggregation of melanin. Lesions with superficial ablation resulted in less hypertrophic scar formation than those with deep ablation (5.9% vs. 53.8%, p < 0.05). CONCLUSION: The Er: YAG laser demonstrated effective clinical results for GCMNs. The grenz zone and the melanocytes nests with aggregation of melanin are promising predictors of laser efficacy.
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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 | 0.000 |
| 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) | 0.000 | 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".