Clinical and epidemiological aspects and modern approaches to the treatment of pityriasis versicolor
Bibliographic record
Abstract
Pityriasis versicolor (tinea versicolor) lichen (PVL) is a fungal infection of the stratum corneum of the epidermis caused by the yeast-like fungus Malassezia (Pityrosporum), which is part of the normal microbiome of the skin. Malassezia yeast has a conditionally pathogenic potential, penetrating into the stratum corneum and causing the appearance of multicolored spots on the skin. Malassezia fungi are involved in the pathogenesis of head and neck dermatitis, seborrheic dermatitis and folliculitis. PVL occurs in both tropical and temperate climates and affects both sexes equally. There are no systematic data on the prevalence of this disease in the world, but it is known that in tropical climates, PVL is more common (up to 40% in Brazil) than in temperate zones (<1% in Sweden). In Russia, there are also no general epidemiological data on the prevalence of PVL in the available literature. In the Krasnodar Territory in 2022-2024, among patients who turned to a dermatovenerologist for skin peeling accompanied by itching, 28% were diagnosed with PVL. The disease is considered non-contagious and is treated with topical antifungal drugs. In severe cases, the use of systemic antimycotics is indicated, which reduces the duration of the treatment and prevents relapses of the disease. The review provides data on the pathogenesis and prevalence of the disease, as well as modern approaches to PVL therapy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".