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Record W4381594415 · doi:10.1093/jbcr/irad045.166

571 Effectiveness of Compression Garments with Silicone versus Compression Garments Alone on Hypertrophic Scar

2023· article· en· W4381594415 on OpenAlexaboutno aff
Karen Robertson, David Wang, Khoa Tran, Ejun Yun, Katelyn Stevens, Brett Hartman

Bibliographic record

VenueJournal of Burn Care & Research · 2023
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
FundersSchool of Medicine, Indiana University
KeywordsMedicineSiliconeVascularityScarsSurgeryHypertrophic scarHypertrophic scars

Abstract

fetched live from OpenAlex

Abstract Introduction Only a few studies have looked at the effects of custom compression garments with silicone sheeting sewn into the garments versus garments alone on scar management. This retrospective study hypothesizes that garments with silicone will improve the Modified Vancouver Scar Scale (mVSS) total scores and sub-scores of pliability, vascularity and height of hypertrophic scars(HTS) when compared to garments alone. Methods This is a retrospective study of patients that were autografted or required >21 days to heal and placed in compression garments with or without silicone between 2013 and 2020. Charts were reviewed and mVSS scores from 91 patients with 191 scar locations (134 silicone/57 non-silicone) were collected at 1,3,6,9,12 months. Descriptive statistics were used to describe the sample characteristics. The mean mVSS score and mean sub-scores for pliability, height and vascularity were computed at 1,3,6,9,12 months and reported for the silicone and non-silicone groups. Results When comparing the two groups at 9-months (with 45% of initial scars scored), the silicone group had a greater decrease in numerical value and overall % change from 1 to 9-months as compared to the non-silicone group in all areas. The results at 12-months (with 30% of initial scars scored) demonstrated the non-silicone group had a greater decrease in numerical value and % change in height and overall score. Pliability had a 25% improvement in silicone group compared to 16% change in non-silicone group. Vascularity % change was similar with a 47% change in non-silicone group and 46% change in silicone group. The scars in silicone group that were analyzed at 12-months were consistently scored higher across prior months. Conclusions Silicone group demonstrated improved %change in all categories at 9-months and in pliability %change at 12-months despite the decreased sample size. Pliability is improved with the use of silicone garments. Although the 12-month %change in mean for height, vascularity and total score did not show improvement over non-silicone, this reflects the return patients having significant scarring throughout treatment and needing continued interventions. These returning patients had scars in the non-silicone group as well that were also rated resulting in the disparity in the groups. The patients in the silicone group with improved scars did not continue follow-up at 12-months. Further research with focus on 9-18 month follow-up mVSS scores is warranted. Applicability of Research to Practice Effectiveness of adding silicone to garments in scar treatment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.097
GPT teacher head0.433
Teacher spread0.336 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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