527 Combination Treatment for Hypertrophic Burn Scars Utilizing Fractional Ablative and Continuous Wave CO2 Laser
Bibliographic record
Abstract
Abstract Introduction Hypertrophic scars remain a devastating consequence of severe burn wounds, producing anatomic deformities, as well as functional impairment. Fractional ablative CO2 laser treatment has shown scar - reducing effects. In this study, we compared the outcomes of combining two different CO 2 lasers or fractional ablative CO2 laser alone in treating hypertrophic burn scars. Methods Forty patients with hypertrophic burn scars were included in one of following two groups: fractional ablative CO2 laser combined with continuous wave CO2 laser (group 1) or fractional ablative CO2 laser alone (group 2). Three plastic surgeons rated the hypertrophic scars according to observer-rated Vancouver Scar Scale (VSS) before and after treatment (at least 6 months after the last laser) and by patient-completed questionnaires after treatment (at least 6 months after the last laser). Results Forty patients completed the laser treatment. Group 1 showed significant improvement in vascularity, pliability, and height than group 2 (p < 0.05) but not in pigmentation. Time-dependent analysis of total VSS scores suggested that group 1 experienced more improvement during a shorter treatment period than group 2 (p < 0.05). For patient-reported outcomes, group 1 showed significant improvement than group 2 in scar appearance, scar thickness, pain, and pruritus (p < 0.05). Conclusions Observer-reported VSS outcomes showed that combining laser treatment resulted in more improvement of vascularity, pliability, and height indices for hypertrophic burn scars. Patient-completed outcomes showed that combining laser therapy was considered more helpful for improving scar appearance, scar thickness, pain, and pruritus than fractional ablative laser alone. Furthermore, combination treatment appeared to produce more improvement in a shorter period of time. Applicability of Research to Practice The two lasers are widely used in scar treatment in South Korea, so yes this research can be applied to medical practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.003 | 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".