Use of small needle knife in autologous fat grafting for the treatment of depressed scar
Bibliographic record
Abstract
RATIONALE: Scars always related to functional limitations, cosmetic impairment, and social and emotional problems. Clinical improvements in scar characteristics after autologous fat grafting are well described. In this paper, we present an innovative approach to treat depressed scars. PATIENT CONCERNS: We presented a 29-year-old woman with multiple depressed scars in the left upper arm and near the elbow joint after trauma in childhood. DIAGNOSES: The patient was diagnosed as having multiple depressed scars accompanied with retraction and pain. INTERVENTIONS: We used small needle knife during fat grafting to treat the depressed scar. Vancouver Scar Scale was used to assess the effect. OUTCOMES: Aesthetic and functional improvements were observed. Resolution of pain and improvement in scar elasticity were objectively assessable. Improvement of both clinical evaluation and patient perception was obtained. LESSONS: Use of small needle knife during fat grafting is a good alternative for the treatment of 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 | 0.000 |
| 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 | 0.001 | 0.001 |
| 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".