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Record W4311286477 · doi:10.1177/20595131221137768

The objective evaluation of triamcinolone acetonide efficacy in keloids management using Antera3D® imaging system

2022· article· en· W4311286477 on OpenAlexaboutno aff
Fedele Lembo, Liberato Roberto Cecchino, Domenico Parisi, Aurelio Portincasa

Bibliographic record

VenueScars Burns & Healing · 2022
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsTriamcinolone acetonideKeloidMedicineScarsPathologicalCorticosteroidWilcoxon signed-rank testSurgeryDermatologyInternal medicineMann–Whitney U test

Abstract

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Background: Keloids are pathological scars characterized by nodular fibrous tissue that extends beyond the border of initial damage. These lesions do not spontaneously regress and can cause cosmetic disfigurements and functional disabilities. IntraLesional Injection of Triamcinolone Acetonide (ILITA), alone or in combination with other therapy, is one of the first-line treatment modalities. In this study the authors evaluated the objective efficacy of ILITA treatment in keloids management using this new imaging system. Materials and Methods: 37 patients with 45 keloid scars were treated with intralesional injection of triamcinolone acetonide (TAC) 20 mg/ml at an interval of three weeks. Antera3D® camera took the images and dates of the treated area in each patient, before the treatment (T0) and at three weeks after the last injection (T1). The system processed the levels of color, elevations, melanin and hemoglobin expression. All the scars were also evaluated, at the same times, by validated Vancouver Scar Scale (VSS). Comparison of the variables was performed using a Wilcoxon signed-rank test with a p < 0.05. Results: At T0, mean VSS score was 8.67 ± 1.35 which reduced to 3.62 ± 1.72 at final follow up. Antera3D® scores were statistically significant differences in color (8.14 ± 2.41 vs 9.54 ± 1.81), protrusion (381.3 ± 15.6 vs 198.6 ± 21.3), melanin (0.53 ± 0.02 vs 0.62 ± 0.2) and hemoglobin (1.26 ± 0.41 vs 2.21 ± 0.41) expression levels after the treatment. Conclusions: In our clinical trial, the data results demonstrated that ILITA seems to be effective in reducing keloid dimensions and symptoms such as itching and pain, even if the treatment has local minimal adverse effects such as pain, telangiectasias and atrophy. Lay Summary: Keloids are pathological scars characterized by nodular fibrous tissue that extends beyond the border of initial damage. Large keloids can cause cosmetic disfigurements and functional disabilities that affect quality of life. In literature, several treatment approaches have been described but, to date, no single method is considered superior. The International Advisory Panel on Scar Management recommended the use of intralesional steroid injections for keloids treatment. The efficacy of treatment may be evaluated with subjective scale; as no one can guarantee an objective evaluation. To eliminate the observer and/or patient factors, and to obtain a reliable, consistent, feasible, valid and objective evaluation a skin analysis camera system called Antera3D® (Miravex, Dublin, Ireland) can be used.In this study the authors evaluated the objective efficacy of triamcinolone acetonide treatment in keloids management using this imaging system. In this series, for Antera3D® scores there were statistically significant differences in color, protrusion, melanin and hemoglobin expression levels before and after treatment. The device directly shows the treatment changes, measured objectively and accurately, without bias of traditional evaluation scoring scale.Antera3D® system guarantees an objective evaluation of effectiveness of scar treatment enabling clinicians to modulate the therapy according to the scores registered.

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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.058
GPT teacher head0.386
Teacher spread0.329 · 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".

Quick stats

Citations3
Published2022
Admission routes1
Has abstractyes

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