Comparing the Efficacy of Triamcinolone Acetonide Versus Bleomycin in Hypertrophic Scars in Burn Patients: A Clinical Trial
Bibliographic record
Abstract
Background: Treatment of hypertrophic burn scars is challenging. Intralesional injection of corticosteroids has been the first line of treatment. Triamcinolone Acetonide (TA) and Bleomycin (BLE) are standard therapeutic options. We conducted a comparative study to measure the effects of BLE and TA on hypertrophic burn scars. Methods: In this clinical trial, we enrolled 25 patients with hypertrophic burn scars in this study. In each patient, two adjacent affected areas on the body were randomly selected for intralesional injection of TA and BLE. The size of the burn scars was between 10 and 40 cm2 (square centimeter). The injections were repeated at intervals of four weeks for three periods. Follow-up of patients continued until the end of the fourth month of treatment. We used the Vancouver Scar Scale and Patient and Observer Scar Assessment Scale system to compare the recovery of each lesion. Means, standard deviation, and p-values comparing the treatment of lesions with BLE and TA using two different scales were reported. Independent samples t-test and paired sample t-test were used to find out a statistically significant difference between BLE and TA treated lesions. Results: = 0.023). The proportion of individuals who had no side effects after taking BLE and TA was much higher than those who experienced skin pain or hypopigmentation. Conclusion: Intralesional BLE injection is more effective than TA in treating hypertrophic scars. Further studies with larger sample sizes are needed to approve these results.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".