Surgical treatment of nasal non-melanoma skin cancer in elderly patients using dermal substitute
Bibliographic record
Abstract
Conclusions: The nose is often involved by non-melanoma skin cancer (NMSC) and the increase in the incidence of such tumors, the morbidity and treatment-related costs represent a significant burden to healthcare systems. A bioresorbable dermal substitute (Hyalomatrix®) has been used for immediate dermal coverage and nose restoration after excision of infiltrating nasal NMSCs in elderly ASA III patients. Further studies on dermal substitutes are needed to improve benefit to patients.Objective: Surgical treatment of nasal non-melanoma skin cancer (NMSC) in elderly patients.Materials and methods: Ten elderly ASA III patients with nasal defects after resection of infiltrating NMSC were reconstructed in a two-stage strategy. The surgical protocol targeted an initial wide tumor excision and apposition of a dermal induction template (Hyalomatrix®) and successive full thickness skin autograft. Results were documented by photography, visual analog scale for patient satisfaction, and Vancouver scar scale for evaluation of final graft characteristics.Results: All patients were tumor-free during the 2 years follow-up. The procedure achieved acceptable nose reshaping and graft scarring evolution. Patient satisfaction was good-to-high.
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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".