Fractional Carbon Dioxide Laser Resurfacing in Combination With Potent Topical Corticosteroids for Hypertrophic Burn Scars in the Pediatric Age Group: An Open Label Study
Bibliographic record
Abstract
BACKGROUND: Lasers and potent topical corticosteroids are used as therapeutic options in hypertrophic burn scars. OBJECTIVE: To assess the therapeutic effect of fractional CO2 laser resurfacing in combination with potent topical corticosteroids on hypertrophic burn scars in pediatric age group. METHODS: Ten children (5-12 years) with postburn hypertrophic scars were treated with 3 to 5 sessions of fractional CO2 laser resurfacing at 1-month intervals, and triamcinolone suspension was applied immediately after each laser session. Patients were also instructed to apply clobetasol propionate gel for 1 week after each laser session. Response to treatment was assessed using Vancouver Scar Scale (VSS) and Physician Global Assessment (PGA). Tolerability for the procedure and adverse effects were also assessed. RESULTS: Laser sessions were well tolerated under the effect of topical or local anesthesia. At the time of final assessment, there was mean reduction of 4.2 (range: 2.8-7) in VSS. Reduction of VSS by ≥4 points was observed in 8 of 10 cases, whereas PGA revealed excellent response in 6 of 10 cases. No significant adverse effects were reported by any patient. CONCLUSION: Fractional CO2 laser resurfacing in combination with potent topical steroids leads to significant therapeutic benefits in children with postburn hypertrophic scars.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".