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Record W2269192614 · doi:10.1097/bcr.0000000000000383

Prospective Evaluation of Fractional CO2 Laser Treatment of Mature Burn Scars

2016· article· en· W2269192614 on OpenAlexaboutno aff
Sigrid A Blome-Eberwein, Christina Gogal, Michael J. Weiss, Deborah Boorse, P Pagella

Bibliographic record

VenueJournal of Burn Care & Research · 2016
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsScarsMedicineErythemaSurgeryProspective cohort study

Abstract

fetched live from OpenAlex

The authors conducted a prospective study of fractional CO2 laser treatment of mature burn scars, comparing objective and subjective scar measurements evaluating at least one treatment and one control scar on the same patient pre- and post treatments. After institutional review board approval, burn survivors with mature blatant burn scars were invited to enter the study. A series of three fractional CO2 laser treatments was performed in an office setting, using topical anesthetic cream, at 40 to 90 mJ, 100 to 150 spots per cm(2). Subjective and objective measurements of scar physiology and appearance were performed before and at least 1 month after the treatment series on both the treated and the control scar. A total of 80 scars, 48 treatment and 32 control scars, were included in the study. Treatment pain score averaged at 4.7/10 during and at 2.4/10 5 minutes after the treatment. All treated scars showed improvement. Objectively measured thickness, sensation, erythema, and pigmentation improved significantly in the treated scars (P = .001, .001, .004, and .001). Elasticity improved, but without statistical significance. Vancouver scar scale assessments by an independent observer improved from 8 to 6; patient self-reported pain and pruritus remained unchanged in both groups. Fractional CO2 laser treatment is a promising entity in the treatment of burn scars. Our study results show significant differences in objective measurements between the treated scars and the untreated control scars over the same time period. In scar treatment studies, the patient/observer and Vancouver scar scales may not be sensitive enough to detect outcome differences.

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)0.002
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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
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)0.0010.000

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 head0.099
GPT teacher head0.460
Teacher spread0.361 · 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 designNon-randomized trial
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

Citations74
Published2016
Admission routes1
Has abstractyes

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