Management of Aesthetical and Functional Complications after Total Parotidectomy. First Long-Term Experiences with Dermal Matrix Surgimend ® in Patient Affected by Malignant Parotid Tumors
Bibliographic record
Abstract
Background: This is an observational cohort study on patients affected by malignant parotid tumors treated with total parotidectomy. The aim of our work is to analyze and compare the effects and complications after parotidectomy, using or not SurgiMend ®. Methods: 40 patients were retrospectively enrolled between September 2014 and June 2020. Basing on the placement of SurgiMend ® for parotid lodge reconstruction, the samples were divided into two groups. Thus, the incidence rate of complications after the surgical procedure was analyzed between the two groups. Results: = 0.05) revealed a significant difference of Vancouver Scar Scale (VSS) between the two groups, representation as vascularity and pigmentation improvement, changing scar color, scar height reduction, and increased pliability. Conclusion: Although many techniques are available to fill the parotidectomy defect, improve facial contour and prevent Frey's syndrome, the use of SurgiMend ® matrix is one of most effective and reliable method to address these complications, with the advantage of decreased operative time due to not require an additional surgical donor site.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".