Comparison of efficacy of intralesional 5-fluorouracil plus triamcinolone acetonide versus intralesional triamcinolone acetonide in the treatment of keloids
Bibliographic record
Abstract
Objective To compare efficacy of intralesional 5-fluorouracil (5-FU) plus triamcinolone acetonide (TCA) versus intralesional TCA alone in the treatment of keloids. Methods The study included 100 patients with keloids. Patients were divided into two groups. Randomization was done through lottery method. For each 1 cm area, group A was given intralesional 5-FU 50 mg/ml (0.9ml) plus TCA 40mg/ml (0.1ml) after every 4 weeks and group B was given intralesional TCA 40mg/ml (0.1ml) after every 4 weeks for total period of 12 weeks. Administration of the drugs was continued till the keloid flattened or for a maximum period of 12 weeks. Follow-up was done every 4 weeks for total period of 12 weeks after the administration of last injection. Decrease in total score using Vancouver Scar Scale was calculated. Results After the completion of study mean reduction in Vancouver Scar Score was -71.18 ± 8.69 in the intralesional 5-FU plus TCA group as compared to -50.80 ± 8.59 in the intralesional TCA group (p=0.001). 5-FU + TCA was efficacious in 98% of cases (group A) and TCA alone in 62% of cases (group B). No serious adverse effects were noticed in either group. Conclusion Intralesional 5-FU plus TCA is significantly better than intralesional TCA alone in the treatment of keloids.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".