Patch Testing To a Textile Dye Mix by the International Contact Dermatitis Research Group
Bibliographic record
Abstract
BACKGROUND: Disperse dyes are well-known contact sensitizers not included in the majority of commercially available baseline series. OBJECTIVE: To investigate the outcome of patch testing to a textile dye mix (TDM) consisting of 8 disperse dyes. METHODS: Two thousand four hundred ninety-three consecutive dermatitis patients in 9 dermatology clinics were patch tested with a TDM 6.6%, consisting of Disperse (D) Blue 35, D Yellow 3, D Orange 1 and 3, D Red 1 and 17, all 1.0% each, and D Blue 106 and D Blue 124, each 0.3%. 90 reacted positively to the TDM. About 92.2% of the patients allergic to the TDM were also tested with the 8 separate dyes. RESULTS: Contact allergy to TDM was found in 3.6% (1.3-18.2) Simultaneous reactivity to p-phenylenediamine was found in 61.1% of the TDM-positive patients. Contact allergy to TDM and not to other p-amino-substituted sensitizers was diagnosed in 1.2%. The most frequent dye allergen in the TDM-positive patients was D Orange 3. CONCLUSIONS: Over 30% of the TDM allergic patients had been missed if only the international baseline series was tested. Contact allergy to TDM could explain or contribute to dermatitis in over 20% of the patients. Textile dye mix should be considered for inclusion into the international baseline series.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".