The Use of Pressure and Silicone in Hypertrophic Scar Management in Burns Patients: A Pilot Randomized Controlled Trial
Bibliographic record
Abstract
This pilot study investigates whether pressure and silicone therapy used simultaneously are more effective in treating multiple characteristics of hypertrophic scars than pressure alone. A pilot randomized controlled trial was conducted. Twenty-two participants with hypertrophic burn scars were randomized to receive Jobskin pressure garments and Mepiform silicone sheeting or Jobskin pressure garments alone. The Vancouver Scar Scale (VSS) was used to measure multiple scar characteristics at baseline, week 12, and week 24. No statistically significant difference was found in the rate of change of the VSS scores between the pressure therapy (PT) group and the pressure therapy and silicone group at week 12 or week 24; however, the mean scores of both groups reduced over 24 weeks. There were no statistically significant changes in the VSS subscores (scar height, vascularity, pliability, and pigmentation) from baseline to week 12 or week 24. A statistically significant relationship was observed between the VSS score and TBSA burned (<30%) in the PT group at baseline (P<.05), over 12 weeks (P<.05), and over 24 weeks (P<.05). Given the limitations of this study, especially the small sample size, further research is necessary before any firm conclusions can be drawn on this therapy approach. However, this pilot study has discussed the recurring issues in the research regarding these controversial treatments and has yielded potential for further investigation in a fully powered randomized controlled trial.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".