Use of a Patient and Observer Scar Assessment Scale to Evaluate the V-Y Advancement Flap for Reconstruction of Medial Cheek Defects
Bibliographic record
Abstract
BACKGROUND: The V-Y advancement flap (VYF) is not commonly used to reconstruct defects located on the medial cheek. The quantitative assessment of VYF for this indication has not been reported. In evaluation of surgical scarring, the Patient and Observer Scar Assessment Scale (POSAS) has been validated for use in burn and breast surgery scars, but its usefulness in dermatologic surgery has not been determined. OBJECTIVE: To present our experience with the use of the POSAS to assess the success of VYF reconstruction for surgical defects on the medial cheek. METHODS AND MATERIALS: Fourteen patients with medium to large (>5 cm(2) ) medial cheek Mohs defects reconstructed using VYF were assessed. Final cosmetic and functional results were analyzed after a follow-up of 6 months to 2 years (mean follow-up 21 months) using the POSAS. RESULTS: Observers using the POSAS gave a mean score for VYF reconstructions of 9.1 ± 2.3 (5 represents normal skin, 50 represents worst imaginable scar). Patients using the POSAS gave a mean score for VYF reconstructions of 10 ± 4 (6 representing normal skin, 60 representing worst imaginable scar). CONCLUSION: VYF reconstruction of medium to large defects of the medial cheek is a useful option. The POSAS may be a helpful tool for evaluating reconstructive results in dermatologic surgery.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".