Effect of autologous nano fat graft on the healing of donor site of split thickness graft.
Bibliographic record
Abstract
Background:split-thickness grafts (STSGs) harvesting is a common technique to reconstruct absent skin and to re-establish the skin barrier in burn and skin defects. Donor site morbidity is not uncommon. Various materials and dressings had been used to improve healing of donor site. Fat grafting or its components had been used in promotion of healing in chronic and irradiated wounds indicating the possibility of improving healing. Aim of study: To evaluate the effect of adding nano fat grafts to donor sites of STSGs.Patients and methods:20 adult patients were included in this comparative self-controlled clinical trial from March 2020 to April 2021. These patients have raw areas of skin which needs STSG. STSG thickness was 0.12.5 inch leaving an area measuring 7*15cm(105cm2) at donor site. The donor site area in lower limb was used as a test area where it was divided into two equal areas, one area was covered by nano fat graft and Vaseline gauze (group A), the other acting as a control group was covered by Vaseline gauze only (group B). Group A was compared to group B as regard healing time from 10thday onward and quality of healing after one month using Vancouver scale (VSS). Tissue biopsy was taken at day 21 from both groups. Any Donor site complications were noted. ResultsComparing The rate of donor site healing in group A with group B, group A showed faster healing with a mean of (13.30 + 2.61) versus (16.05 + 2.43) days from the date of harvesting of STSG. Histologically the mean thickness of neo epithelium in group A was more than that of group B with a mean value of 255.04 + 15.27µm and 161.15 + 28.75 µm consecutively. group A showed better vascularity and pliability while no difference was detected as regard pigmentation and height. Infection occurred in donor site of one patient.Conclusions:Using topical nano fat graft and Vaseline gauze on the donor site of STSG improves healing time as well as vascularity and pliability in comparison to Vaseline gauze alone
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".