Allergy to dust mites may contribute to early onset and severity of alopecia areata
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: A higher risk of allergic diseases such as rhinitis, asthma and atopic eczema (atopic dermatitis) has been reported for patients with alopecia areata (AA) compared with the general population, but the significance of this is still largely unclear. AIM: To determine whether serum total or specific IgE play a role in the onset and severity of AA. METHODS: We tested 461 serum samples from 351 patients with AA and 110 healthy controls (HC) for total IgE (tIgE) and specific IgE (sIgE) by ImmunoCAP-100 or in vitro test (IVT). RESULTS: The absolute value of tIgE was higher in patients with AA than in normal controls (P < 0.001), although the prevalence of raised tIgE (> 120 IU/mL) detected in patients with AA (29.3%) was similar to that of HC (21.8%). Prevalences of raised sIgE against various allergens detected by ImmunoCAP-100 showed that Dermatophagoides pteronyssinus (Der p; 31.1%) and Dermatophagoides farinae (Der f; 29.0%) were the most common allergens. Similar results were found by IVT, with the most common response being against Der p/Der f (29.0%). However, the prevalences of tIgE and sIgE against dust mites (Der p and Der f) in patients with early-onset AA and severe AA were significantly higher than those with late-onset AA and mild AA (P = 0.02, P = 0.02 vs. P = 0.03 and P = 0.001, respectively). Notably, the increases in tIgE and sIgE were independent of atopy history. CONCLUSIONS: Allergy to dust mites may have an effect on the immune response in AA, and may contribute to its early onset and severity in patients of Chinese origin.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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