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Record W4400655286 · doi:10.1097/gox.0000000000005966

Role of Triamcinolone Acetonide in the Maturation of Scars

2024· article· en· W4400655286 on OpenAlexaboutno aff
Ranjit Bhosale, R Dawar, Raj Kumar Manas

Bibliographic record

VenuePlastic & Reconstructive Surgery Global Open · 2024
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsTriamcinolone acetonideScarsMedicineFibrous jointSuture lineSurgery

Abstract

fetched live from OpenAlex

Background: Surgeons have tried various measures to achieve a minimum and aesthetically appealing scars after wound healing at surgical sites. Various regimens have been recommended to minimize scars both intraoperatively and postoperatively. Our study aims to assess the outcome of the injection of triamcinolone acetonide used intraoperatively on a normal surgical suture line. Methods: This is a prospective, observational study of 21 patients (divided into test and control groups with a single scar at the same site) treated with or without injection of triamcinolone acetonide, and outcomes were assessed using Vancouver Scar Scale and Stony Brook Scar Evaluation Scale. Results: > 0.05) between the median of vascularity, pigmentation, and total score on the Vancouver Scar Scale, whereas there was significant difference between height, color, and overall appearance according to the Stony Brook Scar Evaluation Scale between the test and the control group. We could not find a significant difference in outcome with varying, increasing doses of triamcinolone acetonide. Conclusion: A low dose of triamcinolone acetonide is an effective drug that tends to improve the outcome of a scar in terms of vascularity, pigmentation, height, and overall appearance of the postoperative surgical scar and helps in the maturation of a normal scar.

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 score0.290
Threshold uncertainty score0.242

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.035
GPT teacher head0.334
Teacher spread0.299 · 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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