Burn scar regeneration with the “SUFA” (Subcision and Fat Grafting) technique. A prospective clinical study
Bibliographic record
Abstract
BACKGROUND: Treatment of burn scars with traditional surgical techniques is challenging due to recurrent contractures. Fat grafting has been previously used in small clinical series and results are often biased by lack of scientific validating methods. Fat grafting in clinical practice is often evaluated for its filler properties and rarely scientifically validated for its potential in dermal regeneration. Animal studies have shown dermal regeneration with new deposition and reorientation of the collagen fiber. Our study aims to apply the validity of in vitro studies to clinical practice. METHODS: Our study prospectively evaluated outcomes in 12 patients treated with the "SUFA" technique (Subcision and Fat Grafting) for debilitating contracted burns scars limiting range of motion. Results were evaluated clinically with the Vancouver scale and by range of motion at 1, 3, 6 and 12 months. Dermal regeneration was evaluated by looking at dermis thickening using high definition ultrasound and scar remodeling looking at reorientation and new deposition of collagen fibers with hematoxylin-eosin histology and monoclonal antibodies against collagen type 1 and 3. RESULTS: <0.05). Fat reabsorption occurred with a mean of 40%. Thickening of dermis and redistribution and reorientation of the collagen fibers within the dermis was also demonstrated. CONCLUSIONS: Our results present the first clinical scientific evidence of dermal regeneration in fat grafting. Using monoclonal antibodies and high definition ultrasounds, we demonstrate the first evidence of dermis regeneration in a clinical scenario.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".