The Efficacy of a Silicone Sheet in Postoperative Scar Management
Bibliographic record
Abstract
OBJECTIVE: Silicone gel sheeting has been introduced to prevent scarring, but objective evidence for its usefulness in scar healing is limited. Therefore, the authors' objective was to examine the effectiveness of silicone gel sheeting by randomly applying it to only unilateral scars from a bilateral hallux valgus surgery with symmetrical closure. DESIGN: In a prospective randomized, blinded, intraindividual comparison study, the silicone gel sheeting was applied to 1 foot of a hallux valgus incision scar (an experiment group) for 12 weeks upon removal of the stitches, whereas the symmetrical scar from the other foot was left untreated (a control group). The scars were evaluated at 4 and 12 weeks after the silicon sheet application. The Vancouver Scar Scale was used to measure the vascularity, pigmentation, pliability, height, and length of the scars. Adverse effects were also evaluated, and they included pain, itchiness, rash, erythema, and skin softening. RESULTS: At weeks 4 and 12, the experiment group scored significantly better on the Vancouver Scar Scale in all items, except length (P < .05 for all except the length of scar), compared with the control group. In all items, adverse effects of the experiment group were significantly lower than those of the control group at week 12, suggesting that direct attachment of the silicone sheet does not cause adverse effects (P < .05). CONCLUSIONS: To the authors' knowledge, this is one of the first models to minimize bias related to scar evaluation by using symmetrical scars. The early silicone sheet application did show a significant improvement in prevention of postoperative scarring.
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".