IgE-Mediated Sensitization to <i>Malassezia</i> in Atopic Dermatitis: More Common in Male Patients and in Head and Neck Type
Bibliographic record
Abstract
BACKGROUND: Atopic dermatitis (AD) is a common chronic inflammatory skin disease. Malassezia, the predominant skin microbiota fungus, is considered to exacerbate AD, especially in a subset of patients with head and neck type AD (HNAD). In the present study, the relationship between AD and sensitization to Malassezia antigens was investigated. METHODS: We assessed 173 patients with AD. The severity of eczema was determined with Eczema Area and Severity Index (EASI); the type of AD, namely, head and neck type, was reported as well. The total serum IgE and specific IgE to Malassezia were determined and correlated with clinical picture of AD, sex, age, and the EASI. RESULTS: Total IgE was elevated in 77.7% of patients. Specific IgE to Malassezia was positive (≥0.35 kU/L) in 49.1% of patients. Men were significantly more often sensitized to Malassezia antigen (58% of men vs 42% of women; P value, 0.04). Concurrently, 58% of patients with HNAD versus 42% non-HNAD patients had higher levels of specific IgE to Malassezia, this difference being nearly significant (P value, 0.06). Patients with atopy were also more frequently sensitized to Malassezia. No significant relationship between EASI and the level of total IgE or specific IgE to Malassezia was observed. CONCLUSIONS: In our population, IgE-mediated sensitization was found in up to 49% of all patients with AD, most common in men and in head and neck type.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".