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Record W4387104157 · doi:10.25289/ml.23.024

Treatment of an ear keloid refractory to intralesional triamcinolone injection monotherapy with fractional CO<sub>2</sub> laser and triamcinolone combination therapy: a case report

2023· article· en· W4387104157 on OpenAlexaboutno aff
Young Gue Koh, Hye Sung Han, Kwang Ho Yoo, Sun Young Choi

Bibliographic record

VenueMedical Lasers · 2023
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsTriamcinolone acetonideRefractory (planetary science)KeloidMedicineCombination therapyDermatologySurgeryInternal medicineMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Keloid is a benign fibroproliferative disorder characterized by excessive collagen production during abnormal wound healing in keloid-prone individuals.Therefore, the treatment of keloid aims to reduce inflammation and reorganize collagen bundles.Intralesional corticosteroid injection, particularly triamcinolone, is a common first-line treatment, but injections can be difficult in very firm lesions.This case report presents a refractory ear keloid treated with a combination therapy of fractional ablative CO 2 laser and intralesional triamcinolone injection.The patient had a persistent keloid mass in her left ear despite previous intralesional corticosteroid injections.The ear keloid was treated with the combination therapy of fractional CO 2 laser and triamcinolone injection.The keloid size was reduced by more than 50%, and the Vancouver Scar Scale score improved.Combined fractional CO 2 laser and triamcinolone injections may have a synergistic effect on drug delivery in addition to each keloid improvement.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0050.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.036
GPT teacher head0.342
Teacher spread0.306 · 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 designCase report
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

Citations0
Published2023
Admission routes1
Has abstractyes

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