Comparative efficacy and clinical outcomes of compound betamethasone and triamcinolone acetonide on IL-6 and IL-17 in keloid treatment.
Bibliographic record
Abstract
Purpose: To determine the efficacy and clinical outcomes of compound betamethasone and triamcinolone acetonide on interleukin-6 (IL-6) and interleukin-17 (IL-17) in keloid management. Methods: This study was a retrospective analysis of 118 keloid patients treated at The First Affiliated Hospital of Hebei North University, Zhangjiakou, China from January 2020 to December 2022. Patients were randomly divided into Group A (comprising 62 patients who received compound betamethasone) and Group B (comprising 56 patients who received triamcinolone acetonide). Treatment efficacy after 6 months using the Vancouver Scar Scale (VSS), changes in IL-6 and IL-17 levels, and incidence of treatment-related adverse reactions were compared in both groups. Results: Group A demonstrated significantly higher overall response rate compared to Group B (p < 0.05). Both groups showed significant reductions in IL-6 and IL-17 levels after treatment (p < 0.05). However, Group A showed significantly lower IL-6 and IL-17 (p < 0.05) and significantly higher VSS scores t Group B (p < 0.05). Incidence of adverse reactions was comparable between the groups (p > 0.05). Conclusion: Compound betamethasone shows superior efficacy in reducing IL-6 and IL-17 levels and improves scar appearance in keloid patients comparable to triamcinolone acetonide. Prospective studies with larger sample sizes to evaluate the efficacy of various treatments or combination therapies should be conducted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".