Atopy and Sensitization to Allergens Known to Cause Systemic Contact Dermatitis
Bibliographic record
Abstract
BACKGROUND: Atopic dermatitis (AD) associated with respiratory atopy may represent a form of systemic contact dermatitis (SCD), whereby AD flares after ingestion or inhalation of allergens. OBJECTIVE: The aim of the study was to compare the prevalence of positive patch tests to allergens known to cause SCD in AD patients with and without respiratory atopy. METHODS: This is a retrospective study of patients with AD patch tested to 23 allergens known to cause SCD. Positive patch tests were compared between AD patients with and without respiratory atopy, stratified by age and wet or dry work occupation. CONCLUSIONS: Children and adolescents, but not adults, with AD and respiratory atopy were more likely than age-matched AD patients without respiratory atopy to have positive patch tests to these allergens (odds ratio, 2.33; 95% confidence interval, 1.13-4.79). Moreover, AD patients with respiratory atopy and engaging in wet work, but not dry work, occupations were more likely than AD patients without respiratory atopy to have positive patch tests to allergens known to cause SCD (odds ratio, 1.47; 95% confidence interval, 1.05-2.06). Thus, respiratory atopy and wet work are associated with sensitization to allergens known to cause SCD in patients with AD, and patch testing may be valuable in identifying systemic triggers of dermatitis in these patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".