Effective Treatment of Keloids with Three-Dose Moderate-Strength Intralesional Triamcinolone Acetonide (TAC) Regimen
Bibliographic record
Abstract
Background: The most devastating consequence of any injury is scar formation. Among all the surgical specialties, plastic surgery faces the worst dilemma as patients expect it to be the scar-less surgery.Objectives: This study aims to set an effective dose of triamcinolone acetonide intralesional injection to achieve successful results in the treatment of keloids.Methods: A prospective interventional study was conducted in the Department of Plastic Surgery, Shaikh Zayed Hospital Lahore for 2 years. Triamcinolone acetonide was injected intralesional at a dose of 4mg/cm2 every 4th week. The improvement in scar appearance, pain, and itch were measured using Vancouver Scar Scale (VSS), Visual Analog Scale (VAS), and the St Andrew's itch egg scale, respectively up to 12 months of therapy.Results: Among the 40 patients, 12 were males and 28 were females. The mean age of patients was 32.8 years and the most common sites were the chest, earlobes, and back. There was a substantial progressive improvement in VSS and VAS scores over one year. A significant reduction in pruritus was also observed in the patients. No recurrence was noted at the end of 12 months.Conclusions: A moderate-strength dose of 4mg/cm2 as a single intralesional injection of triamcinolone acetonide every four weeks is effective in decreasing the size of keloids and relieving the symptoms such as pain and itching.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".