Combination of 1064 nm Long-Pulsed and Q-Switched Nd:YAG Laser for Facial Hypertrophic Scar and Hyperpigmentation Following Burn Injury
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Bibliographic record
Abstract
Abstract: Burn injury is a common type of trauma which causes significant morbidity and mortality. Wound healing following burns can be complicated by the formation of hypertrophic scars and the occurrence of post-inflammatory hyperpigmentation (PIH). Neodymium:yttrium aluminum garnet (Nd:YAG) laser might become one of the treatments of choice for hypertrophic scars and PIH. We report a case of post-burn hypertrophic scars and hyperpigmentation in a 20-year-old man. The patient was consulted from the Department of Plastic Surgery and Reconstruction after scar revision. He was treated with 1064 nm long-pulsed Nd:YAG laser therapy, spot size 6 mm, fluence 55 J/cm 2 , pulse duration 3 millisecond (ms), for three sessions with one month interval, followed by 1064 nm Q-switched (QS) Nd:YAG, spot size 4 mm, fluence 2.5 J/cm 2 , frequency 2 Hz for two sessions with one month interval. Clinical improvement was observed after five sessions, characterized by scar thinning as assessed using Vancouver scar scale and increased skin tone brightness also reduced redness assessed using a spectrophotometer with no significant side effects. The management of post-burn facial scars and hyperpigmentation remains a challenge. Aside from surgery, the treatment strategy for hypertrophic scar is laser, one of which is the long-pulsed Nd:YAG laser which reduces the production of collagen. In hyperpigmented lesions, QS Nd:YAG laser destructs the melanosome. Combination of 1064 nm long-pulsed and QS Nd:YAG laser therapy provide significant improvement. These therapeutic strategies can be considered as a treatment option for post-burn hypertrophic scars and hyperpigmentation. Keywords: hypertrophic scars, Nd:YAG laser, post-inflammatory hyperpigmentation
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it