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Record W4395449974 · doi:10.1016/j.burns.2024.04.010

Impact of laser treatment on hypertrophic burn scars in pediatric burn patients

2024· article· en· W4395449974 on OpenAlexaboutno aff
Katherine Bergus, Taylor Iske, Renata Fabia, Dana Schwartz, Rajan K. Thakkar

Bibliographic record

VenueBurns · 2024
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePediatric burnHypertrophic scarsScarsSevere burnDermatologySurgery

Abstract

fetched live from OpenAlex

Paediatric patients with hypertrophic burn scars benefit from laser treatment, but this treatment's effectiveness on burn wounds stratified by specific body region and prior burn wound therapy has not been fully evaluated. We performed a single center retrospective study of pediatric burn patients, treated with fractional CO2, with or without pulse dye, laser between 2018-2022. We identified 99 patients treated with 332 laser sessions. Median age at the time of burn injury was 4.0 years (IQR 1.7, 10.0) and 7.1 years (IQR 3.6, 12.2) at the time of first laser treatment. In the acute setting, 55.2 % were treated with dermal substrate followed by autografting, 29.6 % were treated with dermal substrate alone, and 9.1 % underwent autografting alone. Most body regions showed improvement in modified Vancouver Scar Scale (mVSS) score with laser treatment. mVSS scores improved significantly with treatment to the anterior trunk (-1.18, p = 0.01), arms (-1.14, p = 0.003), and legs (-1.17, p = 0.015). Averaging all body regions, the mVSS components of pigmentation (-0.34, p < 0.001) and vascularity (-0.47, p < 0.001), as well as total score (-0.81, p < 0.001) improved significantly. Knowing the variable effectiveness of laser treatment in pediatric burn scars is useful in counseling patients and families pre-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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.015
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.029
GPT teacher head0.341
Teacher spread0.312 · 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 teacher head, 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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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