Fractional carbon dioxide laser treatment of hypertrophic scar clinical and histopathological evaluation
Bibliographic record
Abstract
Hypertrophic scar could be associated with several complications that interfere with patient daily activities, physical and psychological health and impact patient quality of life. Several therapeutics and maneuvers are used for treatment of hypertrophic scar with variable success and side effects. We aim to evaluate safety and efficacy of fractional carbon dioxide laser on treatment of hypertrophic scar both clinically and histopathologically. Hypertrophic scars in each patient of total thirty patients were subjected to random division with sealed envelope into two parts, part A treated with fractional carbon dioxide laser every month for 5 sessions, and part B lift without treatment for control. Hypertrophic scars in each patient were single or multiple, Single scar was more than 15 cm length. Clinical evaluation was done by two blinded dermatologists, using Vancouver Scar Scale (VSS) and Patient and Observer Scar Assessment Scale (POSAS) for each part before, 3 months and 6 months after treatment. Histopathological evaluation was done for each part before and 3 months after treatment by measuring epidermal thickness, collagen area percent, and elastin area percent. The upper significant clinical and histopathological improvement was shown in carbon dioxide laser treated parts than control parts without significant side effects for fractional carbon dioxide laser treatment. Treatment of hypertrophic scar with fractional carbon dioxide laser is beneficial and generally considered safe, with minimal risk of harm when performed with appropriate laser parameters for male and female patients with skin type III and IV, at different ages and different body regions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".