Double vest lipodermal flaps for depressed facial scars
Bibliographic record
Abstract
INTRODUCTION: Depressed tethered scar is a common problem that can cause emotional, social and behavioural problems, especially when it involves the exposed body parts. Several techniques have been described for treating these depressed scars, but none of these can fulfil the optimal results. AIM: Evaluating the aesthetic outcome of using a double vest lipodermal flaps for treating depressed facial scars. MATERIALS AND METHODS: The study included 25 patients with depressed facial scars who underwent scar revision. Their mean age was 31 years. Under local anaesthesia, the scarred area was de-epithelialised and double dart lipodermal flaps were used for revision. Visual analogue and Vancouver scar scales were used as subjective and objective parameters of evaluation, respectively. RESULTS: All the patients followed up for five to eight months. No complications were observed during the scar healing period. Patients satisfaction according to the visual analogue scale showed an average value of 8. The mean total scale according to the Vancouver scar scale was 2.6. CONCLUSION: The new technique of using double vest lipodermal flaps is simple and offers a promising alternative for revising depressed scars.
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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 | 0.000 |
| 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) | 0.003 | 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".