Treatment of Hypertrophic Scars Using a Long-Pulsed Dye Laser With Cryogen-Spray Cooling
Bibliographic record
Abstract
Hypertrophic scars are common and cause functional and psychologic morbidity. The conventional pulsed dye laser (585 nm) has been shown previously to be effective in the treatment of a variety of traumatic and surgical scars, with improvement in scar texture, color, and pliability, with minimal side effects. This prospective study was performed to determine the effectiveness of the long-pulsed dye laser (595 nm) with cryogen-spray cooling device in the treatment of hypertrophic scars. Fifteen Asian patients with 22 hypertrophic scars were treated by the long-pulsed dye laser (595 nm) with cryogen-spray cooling device. In 5 patients, the scar area was divided into halves, one half of which was treated with the laser, whereas the other half was not treated and was used as a negative control. All patients received 2 treatments at 4-week intervals, and evaluations were done by photographic and clinical assessment and histologic evaluation before the treatment and 1 month after the last laser treatment. Treatment outcome was graded by a blind observer using the Vancouver General Hospital (VGH) Burn Scar Assessment Scale. Symptoms such as pain, pruritus, and burning of the scar improved significantly. VGH scores improved in all treated sites, and there was a significant difference between the baseline and posttreatment scores, corresponding to an improvement of 51.4 +/- 14.7% (P < 0.01). Compared with the baseline, the mean percentage of scar flattening and erythema elimination was 40.7 +/- 20.7 and 65.3 +/- 25.5%, respectively (P < 0.01). The long-pulsed dye laser (595-nm) equipped with cryogen spray cooling device is an effective treatment of hypertrophic scars and can improve scar pliability and texture and decrease scar erythema and associated symptoms.
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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".