Comparison of efficacy of intralesional vitamin D3 versus intralesional triamcinolone acetonide in keloid – A randomized double-blinded non-inferiority study
Bibliographic record
Abstract
Objectives: Keloids are often difficult to treat and have a high chance of recurrence. Multiple modalities of therapy have been tried with variable success rates. Intralesional triamcinolone acetonide (TA) remains the most common modality of treatment of keloids. We have conducted a randomized controlled trial comparing the efficacy of intralesional injection TA versus intralesional vitamin D3 (VD3) in keloids. Material and Methods: Group TA (n = 30) received an intralesional TA 40 mg/mL, and group vitamin D (VD) (n = 30) received intralesional VD3 (cholecalciferol) 60000 IU every 4 weekly till 12 weeks and all the patients were followed up for another 4 weeks. At each session, the scar size was assessed by the Vancouver Scar Scale (VSS), and the Visual Analog Scale assessed the pain. Results: The mean score of VSS was significantly decreased in both group TA (7.91 ± 1.5–4.9 ± 1.6, P < 0.001) and group VD (7.84 ± 0.8–5.0 ± 1.6, P < 0.001). The pain was severe in group VD compared to group TA. There was fluid discharge with severe itching and pain in one keloid site in the VD group. The keloids reduced faster in size in the TA group compared to the VD group. There was no significant difference in response to TA versus VD. Conclusion: Both intralesional triamcinolone and VD3 were found to be efficacious with triamcinolone achieving a faster effect. The pain was a limiting factor in the intralesional VD group.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".