Beneficial effects of spraying low mineral content thermal spring water after fractional photothermolysis in patients with dermal melasma
Bibliographic record
Abstract
INTRODUCTION: Melasma is a common dermatological skin disease that can now be treated by fractional photothermolysis (fractional resurfacing). Past studies have shown that thermal spring water (TSW) spray can reduce local inflammatory symptoms after dermatological surgery, laser surgery or chemical peelings. The aim of this study was to evaluate the clinical efficacy and safety of spraying TSW post-fractional resurfacing treatment in patients with dermal melasma. METHODS: Twenty patients with bilateral dermal melasma were included in this split-face comparative study. Patients were treated by fractional resurfacing laser and then TSW was sprayed generously unilaterally. For the next 48 h, patients were instructed to spray thermal water at least six times a day on one side. Patient's self-assessment conducted 10 min and 2 days after TSW spraying (stinging, pain, skin dryness, swelling, and redness) and investigator's 48-h post-treatment evaluation (purpura, skin dryness, erythema, swelling, scars, hyper- or hypopigmentation) were recorded for the treated and control sides using visual analogue scales. RESULTS: Pain, dryness, and redness were significantly lower 10 min after spraying on the TSW-treated side in comparison with the untreated side, as assessed by the patients (P < 0.05). Two days after fractional resurfacing, dryness and redness were still improved on the TSW-treated side. The investigator's evaluation revealed that erythema, the only perceivable sign following irradiation, was significantly reduced by TSW spraying (P < 0.01). CONCLUSION: This split-face comparative study conducted in patients with dermal melasma showed that spraying TSW after fractional laser resurfacing significantly reduced short-term adverse effects associated with the procedure.
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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) | 0.002 | 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".