Comparison of intralesional verapamil with intralesional triamcinolone in the treatment of hypertrophic scars and keloids
Bibliographic record
Abstract
BACKGROUND: The calcium channel blocker, verapamil stimulates procollagenase synthesis in keloids and hypertrophic scars. AIM: To study the effect of verapamil in the treatment of hypertrophic scars and keloids and to evaluate the effect of verapamil on the rate of reduction of hypertrophic scars and keloids in comparison with triamcinolone. METHODS: The study was a randomized, single blind, parallel group study in which 54 patients were allocated to to receive either verapamil or triamcinolone. Drugs were administered intralesionally in both groups. Improvement of the scar was measured using modified Vancouver scale and by using a centimeter scale serially till the scar flattened. RESULTS: There was a reduction in vascularity, pliability, height and width of the scar with both the drugs after 3 weeks of treatment. These changes were present at one year of follow-up after stopping treatment. Scar pigmentation was not changed desirably by either drug. Length of the scars was also not altered significantly by either drug. The rate of reduction in vascularity, pliability, height and width of the scar with triamcinolone was faster than with verapamil. Adverse drug reactions were more with triamcinolone than with verapamil. CONCLUSION: Intralesional verapamil may be a suitable alternative to triamcinolone in the treatment of hypertrophic scars and 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".