Functional and Cosmetic Outcome of Full- Versus Split-Thickness Skin Grafts in Pediatric Palmar Surface Burns
Bibliographic record
Abstract
Palmar hand burns continue to be a common injury in the pediatric population, with long-term implications for function, hand rehabilitation, and psychosocial well-being in a growing child. Debate over the choice of full-thickness skin grafts (FTSG) and split skin grafts (SSG) for optimal subsequent functional and cosmetic outcomes continues. This study prospectively evaluated children who required skin grafting of palmar burns at our institution between January 2008 and December 2009. A clinical assessment of the grafted area and donor site using the Vancouver Scar Scale, together with assessment of sensation, hair growth, and the development of contracture was performed by an independent clinician. Thirty-four (16%) of 214 palm burns that presented to our institution during this period required grafting, of which 26 (77%) agreed to participate in this study. At a mean 13.5 months postsurgery, pliability was significantly enhanced in FTSG compared with SSG (P < .001). Although not statistically significant, vascularity and height of SSGs were preferred. There was no difference in sensation between the two types of graft or donor site outcomes, although hair growth was significantly (P = .002) more prominent in FTSG. There were an equal number of contractures in the two groups, with grafts of either type that extended from the palm onto the volar aspect of digits more commonly affected. These data suggest an improved outcome in children with deep palm burns after FTSG, although with the exception of scar pliability these differences were small.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".