Clinical features and the outcomes evaluation of hypertrophic scar treatment with triamcinolone injection at Can Tho University of Medicine and Pharmacy Hospital
Bibliographic record
Abstract
Background: Excessive scarring has both cosmetic and psychological repercussions. Intra- scar injection, for example, makes a significant contribution to enhancing treatment efficiency. Objectives: To describe the morphological features, categorize, and assessing the effects of Triamcinolone injection therapy of hypertrophic scars. Materials and methods: A cross-sectional descriptive study of 80 patients with hypertrophic scars treated with triamcinolone intralesional injection at Can Tho University of Medicine and Pharmacy Hospital from 5/2018 to 5/2021. Results: There were 80 patients in all, with a male/female ratio of 1/1.05 and a median age of 15-35. There were 129 scars in all, with scar age >1 year accounting for 83%, keloid scars accounting for 64%, and hypertrophic scars accounting for the remaining 36 percent. Scars are most commonly seen on the trunk, accounting for 53.5 percent of all scars, particularly on the anterior chest wall. When the source of scars was discovered, trauma and acne accounted for 24% and 23%, respectively, while the rest were predominantly spontaneous scars, accounting for 49%. Scarring and discomfort of mild to moderate severity were common clinical symptoms; scars larger than 5cm in size had more symptoms than scars smaller than 5cm. Prior to the therapy, the mean Vancouver Score Scale-VSS was 6.55±2.13. After 24 weeks of the therapy, 96.7% of patients had entirely improved itching symptoms, 75% had completely improved pain, and 25% still had minimal pain. After therapy, the mean Vancouver Score Scale-VSS was 2.55±1.81 (p<0.05). At week 24, 3.75% of patients experienced skin shrinkage, 3.75% experienced depigmentation, and 13.75% experienced vasodilation. Conclusion: Triamcinolone intralesional injection should be utilized as a first-line therapy for hypertrophic scarring.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".