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The efficacy of intralesional triamcinolone acetonide (20mg/ml) in the treatment of keloid

2018· article· en· W2792079960 on OpenAlexaboutno aff
Adit M. Garg, Yogesh M. Shah, Alok Garg, Shazia Zaidi, Kshitij Saxena, Khushboo Gupta, B. Ramya

Bibliographic record

VenueInternational Surgery Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineKeloidTriamcinolone acetonideHypopigmentationAdverse effectDermatologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Background: Management of keloid is difficult as well as challenging. Intralesional triamcinolone acetonide (TAC) injections have remained a gold standard in non-surgical management of keloid. TAC is generally used in the concentration of 40mg/ml, which causes adverse effects such as local dermal atrophy and hypopigmentation. Aim was to study efficacy and adverse effects of TAC in treatment of keloid, in a lesser concentration of 20mg/ml.Methods: An open label study was conducted from November 2015 to May 2017 on 25 subjects of either gender, in the age group 11-55 years, at a medical college hospital. Intralesional injection TAC 20 was administered in the keloid at an interval of 3 weeks, for a total of 6 sessions, over a period of 18 weeks. Vancouver scar scale (VSS) was used to assess the improvement and SPSS 21 for statistical analysis.Results: Mean age of keloid subjects was 30.72 years and median duration of keloid was 8 months. The mean VSS score before treatment was 8.36 which reduced to 3.20 after treatment. Mean percentage change in VSS score was 62.79%, which was very highly significant (p <0.001). Physician’s assessment was ‘Very Good’ in 52.0% and ‘Excellent’ in 5 (20%). Adverse effect of atrophy was seen in 3 (12%), hypopigmentation in 11 (44%) and telangiectasia in 4 (16%).Conclusions: Intralesional injection triamcinolone acetonide 20mg/ml gives very good to excellent improvement in the majority of patients of keloid. Local adverse effects seen were hypopigmentation, atrophy and telengiectasia.

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)0.001
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 score0.294
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.062
GPT teacher head0.373
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

Citations15
Published2018
Admission routes1
Has abstractyes

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