Within-Patient, Evaluator-Blinded, Randomized Controlled Clinical Trial to Assess the Efficacy of Gel Sheets in the Treatment of Hypertrophic Scar in Adult Burn Survivors
Bibliographic record
Abstract
Gel sheets have been used to treat hypertrophic scars (HSc) since the 1980s, though evidence for their efficacy-especially for burn-related HSc-is limited. This study conducted a randomized, evaluator-blinded trial to assess gel sheets on established burn HSc compared to intra-individual patient-matched control scars receiving usual care. Thirty-six adult burn survivors with 2 similar scars (based on ultrasound thickness > 2.034 mm and erythema index > 300) were enrolled. One scar per person was randomly assigned to receive gel sheets plus usual care, while the other received usual care only, over a 3-month period. Objective measures (thickness, elasticity, erythema, transepidermal water loss [TEWL], and melanin) were taken at baseline, monthly, and 1-month posttreatment. Itch and pain were self-reported, and adherence tracked monthly. An analysis of covariance (ANCOVA) after 3 months of treatment, and at 1-month posttreatment follow-up, controlling for pretreatment values, showed no significant difference between groups for thickness, elasticity, erythema, TEWL, melanin or itch intensity. However, ANCOVA revealed a significant increase in elasticity in the treated scars when only participants who wore the gel sheet over 16 h a day were analyzed. Comparisons of pretreatment to 3 months of all participants, using paired t-tests, showed a significant decrease in thickness and TEWL, and an increase in elasticity in both groups, but no significant change in erythema or melanin of either site. In conclusion, scar thickness, elasticity, and TEWL improved over time in both groups, but there was no significant between-group difference. However, gel sheets may enhance elasticity if worn over 16 h daily.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".