Improving esthetic outcome of facial scars by fat grafting
Bibliographic record
Abstract
ObjectiveThe aim of this study was to evaluate the effects of different techniques of fat grafting on improving the esthetic outcome of facial scars.BackgroundControl of facial scarring is one of the most difficult challenges in surgical practice, and represents a difficult therapeutic problem facing plastic surgeons to achieve good results. To date, no gold standard exists for the treatment of scar tissue. Autologous fat grafting has been introduced as a promising treatment option for scar tissue-related symptoms. However, the scientific evidence for its effectiveness remains unclear.Patients and methodsThis study was conducted on 30 patients with obvious facial scars. Patients' age ranged from 8 to 48 years. Patients were selected randomly to be treated with fat grafting. The abdomen and thigh were the most commonly chosen donor sites. Fat was processed to be injected at the dermohypodermal junction (microfat grafting) or intradermal injection (nanofat grafting) was used.ResultsFat grafting proved to have a significant role in scar remodeling. This was measured clinically by the Vancouver Scar Scale. Regarding patient satisfaction with cosmetic appearance, 15 cases were evaluated as excellent, eight cases were evaluated as good, and five cases were evaluated as fair.ConclusionAutologous fat grafting has a significant role in facial scar remodeling and provides a beneficial effect on facial scar tissue and scar-related conditions with not only esthetic results but also functional results. Significant improvement in scar appearance, skin characteristics, and restoration of volume and three-dimensional contour is reported.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".