Immediate, Optimal Reconstruction of Facial Lentigo Maligna and Melanoma following Total Peripheral Margin Control
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Peripheral margin control of lentigo maligna and melanoma on the head and neck can be problematic. Frozen sections are unreliable, and conventional histopathology cannot examine the entire margin. Customary treatment involves wide excision and dressing care or skin graft coverage until histopathologic evaluation is complete, as reexcision is frequently required because of positive margins. Wound contraction, donor-site morbidity, and additional procedures before reconstruction are inherent disadvantages to this approach. METHODS: After excisional biopsy of facial lentigo maligna and thin (<1 mm) lentigo maligna melanoma, peripheral margin control was performed in the office by means of excision of 2-mm-wide linear strips of skin, 5 to 10 mm from the biopsy site, combined with simple wound closure. Total margins were evaluated by means of permanent sections. Repeated margin excision was performed until clear. Definitive excision of the lesion was then performed and, with confidence of negative peripheral margins, the optimal reconstructive option was pursued immediately. RESULTS: Fifty-one lesions underwent "square" peripheral margin control, with lentigo maligna melanoma present in nine lesions (average Breslow depth, 0.65 mm). Margins required for clearance of lentigo maligna and lentigo maligna melanoma averaged 1.0 and 1.3 cm, respectively. No recurrences were identified with long-term follow-up. Reconstruction using the optimal procedure was performed immediately in all cases. CONCLUSIONS: Use of the square technique in the management of lentigo maligna and lentigo maligna melanoma improves the certainty of peripheral margin control before definitive excision. Immediate reconstruction can be performed, thereby avoiding temporizing procedures or open wounds and providing for optimal aesthetic and functional results.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it