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Record W4411965236 · doi:10.29271/jcpsp.2025.07.922

Intralesional Triamcinolone Alone Vs. Combined Platelet-Rich Plasma for Keloid Treatment

2025· article· en· W4411965236 on OpenAlexaboutno aff
I Afridi, Shah Fiaz

Bibliographic record

VenueJournal of College of Physicians And Surgeons Pakistan · 2025
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsKeloidTriamcinolone acetonidePlatelet-rich plasmaMedicineDermatologyPlateletSurgeryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare the efficacy of intralesional triamcinolone acetonide alone versus its combination with platelet-rich plasma (PRP) in the treatment of keloids. STUDY DESIGN: Quasi-experimental study. Place and Duration of the Study: Department of Dermatology, MTI-Hayatabad Medical Complex, Peshawar, Pakistan, from March to September 2022. METHODOLOGY: Sixty patients with refractory keloids were enrolled and randomly assigned to two equal groups. Group A received intralesional triamcinolone acetonide (20 mg/mL) injections every three weeks for a total of four sessions. Group B received the same regimen of triamcinolone, supplemented with autologous PRP injections administered one week after each corticosteroid session. PRP was prepared using a two-step centrifugation technique and activated with calcium chloride before intralesional injection. Treatment response was assessed using the Vancouver scar scale (VSS) at 12 weeks. Data were analysed using SPSS version 23.0, with a p-value ≤0.05 considered statistically significant. RESULTS: Significant clinical improvement (≥50% VSS reduction) was observed in 86.7% of patients in Group B compared to 33.3% in Group A (p <0.001). CONCLUSION: Combining intralesional triamcinolone acetonide with PRP is significantly more effective than corticosteroid monotherapy in the treatment of keloids. KEY WORDS: Keloids, Intralesional triamcinolone acetonide, Platelet-rich plasma, Scar therapy.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.017
GPT teacher head0.320
Teacher spread0.303 · 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 designNot applicable
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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of College of Physicians And Surgeons PakistanSame topicDermatologic Treatments and ResearchFrench-language works237,207