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Record W3150115669 · doi:10.1093/jbcr/irab032.286

636 Subcutaneous Contracture Band Release in Burn Scars

2021· article· en· W3150115669 on OpenAlexaboutno aff
Sigrid A Blome-Eberwein, Lisa LePage, Sophia Starner

Bibliographic record

VenueJournal of Burn Care & Research · 2021
Typearticle
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineScarsContractureSurgeryDemographicsAxillaInternal medicine

Abstract

fetched live from OpenAlex

Abstract Introduction Contracture scars post-burn injury often develop in areas near joints and can restrict movement as well as cause cosmetic deformities.1,2 The goal of subcutaneous scar release is to maximize mobility and minimize the need for invasive procedures which can require more recovery time and cause less aesthetically pleasing outcomes, although this new minimally invasive technique may also be used in conjunction with invasive procedures or after more invasive reconstructions to yield the best functional and cosmetic outcome. Methods Retrospective data from May 2016 to July 2019 were collected and analyzed for 28 patients ranging from ages 6 to 68 years old that were diagnosed with a subcutaneous contracture in one or more areas of their body. The data recorded included demographics, procedure specifics and outcomes, patients’ assessments, and areas of which the procedure was most frequently done on. Results Of the data available, range of motion per site improved by 19.1 degrees. Average pain scores reported directly after the procedure were relatively low at 1.5 on a 10-point scale. Vancouver Scar Scale scores decreased by 0.6 from pre-operatively (10.7) to post-operatively (10.1). The most frequently occurring areas that subcutaneous scar release was done on was the neck (15), axilla (7), and shoulder (7). Overall, 83% of patients reported being very satisfied or satisfied with the outcome of their procedure. Conclusions Subcutaneous scar release improves burn patients’ range of mobility with less residual scarring and less recovery time than standard of care treatments for scar contractures.

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)0.000
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.040
GPT teacher head0.384
Teacher spread0.344 · 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
Published2021
Admission routes1
Has abstractyes

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