Comparison of Intralesional Triamcinolone Acetonide Alone with Intralesional Triamcinolone Acetonide-5-Fluorouracil Combination Injection in Keloid: A Case Report
Bibliographic record
Abstract
Keloids are abnormal cutaneous wound healing responses extending beyond the borders of the initial wound, usually appearing pink-purplish to hyperpigmented nodules or plaques with a hard consistency, irregular shape, uneven border, and smooth shiny surface. Most often occur on the chest, shoulder, upper arms, earlobes, and cheeks. This case report aims to compare a case of keloid treated with intralesional triamcinolone acetonide (TAC) alone with intralesional triamcinolone acetonide-5-fluorouracil (TAC + 5-FU) combination injection. A 21-year-old Minahasa male complains of growing pruritic scars in the back area and right and left upper arms since five years ago. Physical examination of the right and left upper arms revealed multiple hyperpigmented nodules and plaques, irregularly shaped, smooth, and shiny surfaces with defined borders and varying sizes. A clinical diagnosis of keloid was made. Treatment was initiated with weekly intralesional TAC alone on the left upper arm vs. intralesional TAC + 5-FU combination injection on the right upper arm. The evaluation was made based on the clinical and modified Vancouver scar scale. One of the most commonly used therapeutic options for keloid is TAC. However, the combination of TAC + 5-FU may be opted for due to its mechanism through the corticosteroid mechanism of action in conjunction with the antimetabolite activity of 5-FU. The combination may yield a more effective and faster outcome with fewer side effects. Intralesional combination TAC + 5-FU injection may be a therapeutic option for keloid with minimal side effects.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".