Pulsed dye laser versus long-pulsed Nd:YAG laser in the treatment of hypertrophic scars and keloid: A comparative randomized split-scar trial
Bibliographic record
Abstract
INTRODUCTION: Keloids and hypertrophic scars are benign fibrous growths that occur after trauma or wounding of the skin and present a major therapeutic problem. OBJECTIVE: The purpose of this study is to evaluate and compare the effectiveness of pulsed dye laser (PDL) versus Nd:YAG laser in hypertrophic scar and keloid. METHODS: Twenty patients with hypertrophic scars and keloid were included in this prospective, randomized, split-scar study. Half of each scar was randomized to treatment with a 595-nm PDL and the contralateral half with the 1064-nm Nd:YAG. Each patient received 6 laser treatment sessions at 1-month intervals. The scars were evaluated at baseline and one month after the last laser session using the Vancouver scar scale (VSS). RESULTS: One month after the last laser treatment, final total VSS analysis of treated sites by PDL and long-pulsed Nd:YAG laser revealed significant improvements (p < 0.001), whereas the average percentage of improvement in the total VSS was 55.14% for PDL and 65.44% for Nd:YAG laser. However, there were no statistically significant differences between PDL- and long-pulsed Nd:YAG laser-treated sites for total VSS (p = 0.074). LIMITATIONS: This was a single-center non-controlled trial, which included a small number of patients and subjective outcome measures. CONCLUSION: PDL and long-pulsed Nd:YAG laser treatments for keloid and hypertrophic scar provide significant improvement with insignificant difference between both modalities.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".