Comparing the effects of conventional method, pulse dye laser and erbium laser for the treatment of hypertrophic scars in Iranian patients
Bibliographic record
Abstract
BACKGROUND: Hypertrophic scar is an elevated scar with ugly appearance that isn’t acceptable even in reconstructive surgery. Unfortunately, there is no standard and effective treatment for it. Conventional treatments such as corticosteroid injection and garment usage have limited effectiveness. In recent year, laser is suggested for reduction of the volume and height of these scars. But in different studies, different results from very effective to ineffective were reported for this type of treatment. METHODS: This study was a single blind randomized clinical trial that was done on three groups. In each group, 40 patients with hypertrophic scar were included. In group one PDL, group 2 Erbium laser and in group 3 corticosteroid were used. Scar improvement was assessed by the amount of decrease in Vancouver burn scar (VBS) score; the higher the decrease, the better the improvement. RESULTS: Although the mean VBS score significantly decreased in all three groups after treatment, the decrease in mean VBS score in group 3 was significantly lower than the decrease in mean VBS scores of groups 1 and 2 (P values were 0.037 and 0.041, respectively). CONCLUSIONS: Some types of laser such as PDL and erbium can improve elevation and vascularity of hypertrophic scar. These types of treatment can use in hypertrophic scar management when vascularity and elevation of scar are unfavorable. KEY WORDS: PDL, hypertrophic scar, erbium laser, conventional treatment.
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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 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".