Occupation-Related Contact Dermatitis in North American Health Care Workers Referred for Patch Testing: Cross-Sectional Data, 1998 to 2004
Bibliographic record
Abstract
BACKGROUND: Contact dermatoses are common in health care workers (HCWs). OBJECTIVES: To (1) estimate the prevalence of occupation-relevant allergic contact dermatitis (ACD) among health care workers patch-tested from 1998 to 2004 by the North American Contact Dermatitis Group (NACDG), (2) characterize responsible allergens among health care workers overall as well as in specific health care occupational subgroups, and (3) compare these results to those of nonhealth care workers. METHODS: Between 1998 and 2004, 15,896 patients were patch-tested by the NACDG. Occupation-related allergic patch-test results were analyzed among HCWs, subgroups of HCWs, and non-HCWs. RESULTS: 1,255 patients (7.9%) were HCWs. Female gender (HCWs, 86.2%; non-HCWs, 63.6%) and hand involvement (HCWs, 54.7%; non-HCWs, 27.8%) were more common in HCWs (p < .05); 18.2% of HCWs and 6.6% of non-HCWs had occupation-related allergens of current clinical relevance. Thiuram mix (HCWs, 8.87% non-HCWs, 0.90%) and carba mix (HCWs, 5.43%; non-HCWs, 0.87%) were the most common occupation-related currently relevant antigens in HCWs and were more common in HCWs than in non-HCWs (p < .05). CONCLUSIONS: Among HCWs patch-tested by the NACDG between 1998 and 2004, the most common allergens were thiuram mix and carba mix, followed by glutaraldehyde, cocamide diethanolamine, and chloroxylenol. Gloves, sterilizing solutions, and soaps were common sources of responsible allergens.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".