The Correlation Between Time to Skin Grafting and Hypertrophic Scarring Following an Acute Contact Burn in a Porcine Model
Bibliographic record
Abstract
One sequelae of burn injury remains the development of hypertrophic scarring. This appears more likely when the healing has been prolonged. Early excision of deep dermal burns and subsequent split skin grafting (SSG) may provide a more favorable result. The optimal timing of grafting for deeper dermal burns remains controversial. This study sought to establish evidence for the optimal grafting time using a porcine model. Five Large White female pigs were exposed to four contact burn injuries for duration of 20 seconds at 92°C. Each site was randomized to a treatment arm: dressing only as the control, SSG day 3, SSG day 14, and SSG day 21. Burn wound biopsies were obtained at days 0, 3, 14, 21, and 99 after the burn injury, together with microbiological swabs. Digital photographs were taken to assess scarring using the Vancouver scar scale. All biopsies were subject to histological and immunohistochemical analysis. Vancouver scar scale scores and histopathological analysis indicated that areas grafted on day 3 had the least fibrosis and scarring (P = 0.031). There was a strong correlation between the histological evaluation of the degree of fibrosis and α-smooth muscle actin levels (r = .60, P = .014). A greater degree of fibrosis was observed in the presence of infection (P = .028). Sites grafted on day 3 consistently exhibited the best clinical and histological scar outcome. The increased fibrosis observed in delayed grafting may have been be related to progression of burn depth and infection. These results suggest that early grafting of deep dermal burns may be preferential.
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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 | 0.002 | 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 | 0.001 |
| 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".