Evaluation of fractional carbon dioxide laser in the treatment of hypertrophic scars
Bibliographic record
Abstract
Background Scars affect millions of patients and can significantly influence the physical and psychological functions of patients. Hypertrophic scars are raised nodules or plaques that develop as a result of an excessive collagen deposition during the wound healing process. There are several medical and surgical treatments available. Fractional carbon dioxide (CO 2 ) laser is currently emerging as a minimally invasive therapeutic alternative. Aim The aim was to evaluate the effect of fractional CO 2 laser in the treatment of hypertrophic scars. Patients and methods This study included 11 patients with hypertrophic scars (skin type III–IV), and their age ranged from 5 to 25 years old, with a mean of 18.27±7.43 years. Each patient received four sessions of treatment with 1-month interval. Final evaluation was performed 1 month after the last session by the opinion of three dermatologists blinded to the study protocol. The Vancouver scar scale and patient satisfaction before and after treatment were assessed. Skin biopsies were obtained before and 1 month after treatment for light microscopic studies. Results All patients showed clinical improvement. There was a statistically significant difference in the Vancouver scar scale between before and after treatment, where P =0.003. Response to treatment was excellent in 18.2%, good in 27.3%, fair in 36.4%, and poor improvement in 18.2% of patients according to dermatologists’ assessments. Overall, 27.3% of patients were highly satisfied, 54.5% were satisfied, and 18.2% were slightly satisfied. Patients tolerated the procedure well with minimal adverse effects. Conclusion Fractional CO 2 can be an effective modality in the treatment of hypertrophic scars, without serious adverse events.
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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) | 0.000 | 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".