Role of nanofat injection in treating post-traumatic scars
Bibliographic record
Abstract
Background: Scars are the common and unpleasing result that occur following injuries of different causes. They have a great impact on the affected subjects both physically and psychologically. Aim: The aim of this study was to evaluate the role of autologous nanofat injection in refining the esthetic appearance of post-traumatic scars, along with pathological correlation of the results. Patients and methods: Nineteen patients with post-traumatic scars were treated with a single session of nanofat injection. The results were assessed after 6 months from the session using Vancouver scar scale (VSS) in addition to pathological evaluation via image analyzing system. Results: The age ranged between 19 and 40 years old. Statistical significant improvement on the VSS was noted regarding the height and pigmentation of the treated scars. On histopathological evaluation, there was a high statistical significant increase regarding epidermal thickness, collagen fibers, elastic fibers, and vascularity. Conclusion: Nanofat injection is a potential efficient therapeutic modality for post-traumatic 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 | 0.000 |
| 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) | 0.001 | 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".