Patch Testing with Methyldibromoglutaronitrile in a Localized Population in the United States
Bibliographic record
Abstract
BACKGROUND: in Europe, methyldibromoglutaronitrile (MDGN) was banned because of excessive rates of contact allergy. However, it is unclear whether the concentrations used for testing MDGN are optimal, as different groups have used varying concentrations with quite different rates of positive reactions. OBJECTIVES: to report patch-test results with MDGN in a localized US population, to compare these results with those of other studies, and to evaluate any association between contact allergy to MDGN and atopic dermatitis. METHODS: a retrospective analysis of 1,753 patients tested with various concentrations of MDGN was conducted. RESULTS: Four percent (4.0%) of patients had positive reactions to MDGN, of which 1.2% were ++/+++ reactions and 2.8% were + reactions. Among patients with ++/+++ reactions, 9.5% had a reaction of definite relevance; of patients with + reactions, only 2.0% had a reaction of definite relevance. Irritant reactions were had by 3.2% of patients; none of these were relevant. The North American Contact Dermatitis Group had a positive reaction rate of 6.2%; European groups had rates of 1.6 to 5.0%. No significant association was found between atopic dermatitis and positive patch-test reactions to MDGN. CONCLUSION: owing to the number of irritant reactions observed, we suspect that many reactions to MDGN are falsely positive, underscoring the importance of careful interpretation of reactions less than or equal to +.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".