Efficacy of Silicone Gel versus Silicone Gel Sheet in Hypertrophic Scar Prevention of Deep Hand Burn Patients with Skin Graft: A Prospective Randomized Controlled Trial and Systematic Review
Bibliographic record
Abstract
BACKGROUND: Burn injuries are burdensome to the public health system. Hypertrophic scars are the most common undesirable sequelae associated with burn scar contracture, resulting in reduced hand function. This study compared 2 different forms of silicone combined with pressure garment (PG) to determine the efficacy in hypertrophic scar prevention in hand burns. METHODS: A systematic review was also performed, including only randomized control trials with silicone materials in burned patients. A prospective intraindividual randomized controlled trial was conducted to compare the efficacy of 3 treatment groups: silicone gel and silicone gel sheet combined with PG versus PG alone. RESULTS: 0.05). Scar stiffness improved at 8- and 12-weeks follow-up in both silicone gel and silicone gel sheet combined with PG; however, there was no significant difference between silicone groups. Scar thickness significantly improved at 2, 4, and 8 weeks in the silicone gel group compared with PG. Scar irregularity significantly improved at 2, 4, 8, 16, and 20 weeks in both silicone combined PG groups compared with PG alone. CONCLUSIONS: Silicone gel and silicone gel sheet combined with PG were more effective than PG alone in some aspects of the Patient and Observer Scar Assessment Score. However, there was no significant difference between the silicone gel and silicone gel sheet on the Vancouver Scar Scale.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".