Wet Wipe Allergens: Retrospective Analysis From the North American Contact Dermatitis Group 2011–2014
Bibliographic record
Abstract
BACKGROUND: Although there are several case reports of wet wipe-associated contact dermatitis, the prevalence of wipes as a source of allergic contact dermatitis in larger populations and the responsible allergens are largely unknown. OBJECTIVE: The aim of the study was to determine the prevalence of wet wipes as a source of contact allergy and the most commonly associated allergens in a North American tertiary referral patch test population. METHODS: Data collected from 2011 to 2014 by the North American Contact Dermatitis Group was used to conduct a retrospective cross-sectional analysis of patient demographics and patch test results associated with the triple-digit source code for "wet wipe." RESULTS: Of the 9037 patients patch tested during the study period, 79 (0.9%) had a positive patch test reaction to an allergen identified with a wet wipe source. The most commonly associated allergens were preservatives, including the following: methylisothiazolinone (MI) (59.0%), methylchloroisothiazolinone (MCI)/MI (35.6%), bronopol (2-bromo-2-nitropropane-1,3-diol) (27.4%), and iodopropynyl butylcarbamate (12.3%). Fragrance (combined) represented 12.3%. Anal/genital dermatitis was 15 times more likely (P < 0.0001) in those with wet wipe allergy. More than 92% of patients with wipe-associated contact allergy had their contact allergens detected by the North American Contact Dermatitis Group screening series. CONCLUSIONS: Wet wipes are an important source of contact allergy. Preservatives are the main allergens, especially isothiazolinones.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".