Patch Testing With Textile Allergens: The Mayo Clinic Experience
Bibliographic record
Abstract
BACKGROUND: Recognition of allergic contact dermatitis attributed to textile dyes and resins is steadily increasing. OBJECTIVE: This study aims to review the results of patch testing with a textile series at our institution and to compare with previously published reports. METHODS: We performed a retrospective review of results in patients who underwent patch testing using a series of textile dyes and resins from January 1, 2000, through September 30, 2011. RESULTS: A total of 671 patients (mean age, 56.5 years; female, 65.9%) were patch tested with the textile series (42 dyes and resins). These patients were also generally tested with the standard patch test series (n = 620). Of the patients, 219 (32.6%) demonstrated allergic reaction to 1 or more textile dyes and resins, and 71 (10.6%) manifested irritant reactions. The most frequent allergens were disperse blue 106 1% (8.3%), disperse blue 124 1% (8.0%), and melamine formaldehyde 7% (8.0%). Of patients tested with the standard series, 36 (5.8%) showed a positive reaction to the traditional textile screening allergen p-phenylenediamine 1%. CONCLUSIONS: Supplementing the standard series with the textile series increased detection of textile allergies. In patients suspected of textile allergy, addition of the textile series is necessary for appropriate diagnosis.
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 | 0.001 | 0.001 |
| 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".