635 Compression Garments with Silicone Improve Hypertrophic Scars Compared to Compression Garments Alone: A Retrospective Study
Bibliographic record
Abstract
Abstract Introduction The management of hypertrophic scars is one of the major challenges facing healthcare providers in the treatment of burn patients. Two of the mainstay noninvasive clinical practices for hypertrophic scars is the utilization of pressure garments and garments with Silicone gel sheeting. Here, we present a comparison of the effectiveness of compression garments alone and garments with silicone in the treatment of a large pediatric patient population with hypertrophic scars. Methods A retrospective study was performed to compare the effectiveness of compression garments with silicone versus compression garments without silicone in the treatment of pediatric hypertrophic scars. Included in this study were patients who received at least 12 months of follow-up treatment with silicone or non-silicone compression garments between 2013 and 2018. Modified Vancouver Scar Scale (VSS) scores were analyzed 1, 3, 6, 9, and 12 months post-injury/surgery for each scar. Descriptive statistics and t tests were used to summarize and compare the total VSS scores between the two groups. In addition, descriptive and ANOVA statistics were performed to compare the effectiveness of silicone compression treatment for scars located on different regions of the body. Results In total, the compression garment with silicone group included 99 scars of 70 different patients and the non-silicone group included 28 scars of 19 different patients. Before-after total VSS scores for silicone group decreased from 4.11 (SD, 1.522) to 1.47 (SD, 1.268) compared to a decrease from 3.27 (SD, 1.117) to 1.80 (SD, 1.380) for compression group after 12 months of treatment (P< 0.05). ANOVA analysis revealed no statistically significant difference between silicone’s effectiveness on scars located in different regions of the body based on total VSS score after 12 months of treatment (F(4, 99)=1.47, p< 0.05). Conclusions Compression garments with silicone are more effective in treating hypertrophic scars than garments without silicone. The effectiveness of silicone is independent of the scar location assuming sufficient contact and coverage. Applicability of Research to Practice This retrospective study supports the use Silicone compression garments for hypertrophic scars in pediatric patients and is completely applicable to medical practice.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".