Skin Grafting Compared with Conservative Treatment in Patients with Deep Second-Degree Burn Wounds of the Trunk and Buttocks
Bibliographic record
Abstract
BACKGROUND: Burns are among the most common causes of injury and result in long-term morbidity, psychological complications, and reduced quality of life. We aimed to evaluate and compare the results of skin grafting versus nonsurgical treatment in patients with deep second-degree burn wounds of the back and posterior trunk. METHODS: This is a descriptive-analytical cross-sectional study of patients with trunk and buttock burns admitted to Burn Hospital in Shiraz, Iran from 2017 to 2019. The skin surface with burns and the final repaired tissue was measured. The Vancouver Scar Score (VSS) and pigmentation, vascularity, thickness, and pliability were assessed. VSS, pigmentation, vascularity, thickness and pliability were considered as outcomes. RESULTS: <0.001). CONCLUSION: The mean VSS was significantly higher in patients with grade 2 deep burns who received skin grafting than in patients without skin grafting. Due to the lack of donor sites and the need to prioritize skin grafts in burn patients with high total body surface area, it is better to perform skin grafts on the posterior trunk and buttocks in areas with deep grade 2 burns as a last priority and treat this wound with conservative therapy.
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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 | 0.001 |
| 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 | 0.000 |
| 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".