Patch Testing With Tocopherol and Tocopherol Acetate: The North American Contact Dermatitis Group Experience, 2001 to 2016
Bibliographic record
Abstract
BACKGROUND: Vitamin E (tocopherol) a naturally occurring mixture of antioxidants commonly used in topical skin care products, may cause allergic contact dermatitis. OBJECTIVE: The aim of this study was to characterize positive patch test reactions to tocopherol and tocopherol acetate. METHODS: This is a retrospective analysis of North American Contact Dermatitis Group patch test data to tocopherols (dl-α-tocopherol 100% and/or dl-α-tocopherol acetate 100%) from 2001 to 2016. RESULTS: Of the 38,699 patients patch tested to tocopherol and/or tocopherol acetate, 349 (0.9%) had positive reactions; of these, 87.6% were currently relevant. Most (51.4%) were weak (+) and/or not related to occupation (99.1%). Compared with tocopherol-negative patients, tocopherol-positive individuals were more likely to be female (72.5% vs 67.2%, P = 0.0355), have a final primary diagnosis of allergic contact dermatitis (74.2% vs 52.6%, P < 0.0001), and have dermatitis in a scattered generalized distribution (23.8% vs 18.2%, P = 0.0072); they were also less likely to have hand involvement (16.6% vs 22.3%, P = 0.0064). The most common source of tocopherol was personal care products, especially moisturizers. CONCLUSIONS: Positive patch test reactions to tocopherols were relatively rare given their widespread use. When positive, current clinical relevance was high. Tocopherol-positive patients were more likely to be female and presented with dermatitis on the face or in a scattered generalized pattern.
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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 | 0.001 |
| 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".