<i>Malassezia</i> specific IgE in head and neck dermatitis of eczema: A systematic review & meta‐analysis
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Bibliographic record
Abstract
Head and neck atopic dermatitis (HNAD) is a subtype of atopic dermatitis (AD), a common inflammatory skin condition with a distinctive clinical appearance. Malassezia spp., a predominant skin yeast, is considered to exacerbate HNAD. In this study, we investigate the prevalence of Malassezia-specific IgE among HNAD patients. A comprehensive search was performed for observational studies analysing the association between Malassezia-specific IgE and HNAD. This study was performed according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses 2020 checklist and quality was assessed via the Newcastle-Ottawa Quality Assessment Scale (NOS). Fourteen observational studies (840 patients) were included in the analysis. 58% of HNAD patients were male (95% CI: 45.2-69.7). Overall prevalence of Malassezia-specific IgE among HNAD patients was 79.3% (95% CI: 57.5-91.5). Prevalence of Malassezia-specific IgE among HNAD patients varied significantly between geographical regions (p = 0.0441), with 88% in non-Asian regions (95% CI: 61.06-97.17) and 54.73% in Asian regions (95% CI: 34.36-73.63). Malassezia-specific IgE prevalence among HNAD patients varied significantly among studies of higher and lower NOS quality score (p = 0.0386), with 95.42% in studies with NOS ≥7 (95% CI: 63.54-99.60) and 58.05% in studies with NOS <7 (95% CI: 41.44-73.01). Malassezia-specific IgE prevalence among HNAD patients did not vary significantly between more and less predominant Malassezia species (p = 0.1048). Malassezia spp. plays a crucial role in the pathogenesis of HNAD, and IgE anti-Malassezia antibodies appeared to be a common marker for HNAD. Understanding the pathophysiology of Malassezia in HNAD can help develop more targeted therapeutic approaches in managing AD.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it