Shoe Allergens: A Retrospective Analysis of Cross-sectional Data From the North American Contact Dermatitis Group, 2005–2018
Bibliographic record
Abstract
BACKGROUND: Shoe contact allergy can be difficult to diagnose and manage. OBJECTIVE: The aim of the study was to characterize demographics, clinical characteristics, patch test results, and occupational data for the North American Contact Dermatitis Group patients with shoe contact allergy. METHODS: This is a retrospective study of 33,661 patients, patch tested from 2005 to 2018, with a shoe source, foot as 1 of 3 sites of dermatitis, and final primary diagnosis of allergic contact dermatitis. RESULTS: Three hundred fifty-two patients met the inclusion criteria. They were more likely to be male (odds ratio = 3.36, confidence interval = 2.71-4.17) and less likely to be older than 40 years (odds ratio = 0.49, confidence interval = 0.40-0.61) compared with others with positive patch test reactions. The most common relevant North American Contact Dermatitis Group screening allergens were potassium dichromate (29.8%), p-tert-butylphenol formaldehyde resin (20.1%), thiuram mix (13.3%), mixed dialkyl thioureas (12.6%), and carba mix (12%). A total of 29.8% (105/352) had positive patch test reactions to supplemental allergens, and 12.2% (43/352) only had reactions to supplemental allergens. CONCLUSIONS: Shoe contact allergy was more common in younger and male patients. Potassium dichromate and p-tert-butylphenol formaldehyde resin were the top shoe allergens. Testing supplemental allergens, personal care products, and shoe components should be part of a comprehensive evaluation of suspected shoe contact allergy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".