Occupational Dermatitis in Health Care Workers Evaluated for Suspected Allergic Contact Dermatitis
Bibliographic record
Abstract
BACKGROUND: Contact dermatitides occur commonly among health care workers (HCWs). OBJECTIVE: To contrast the atopic status and incidence, location, and final diagnosis of skin diseases afflicting HCWs versus non-HCWs (NHCWs) evaluated for suspicion of allergic contact dermatitis (ACD); and among the population diagnosed with ACD, to compare the incidence and occupational relatedness of allergens found in HCWs with the rates observed in NHCWs. METHODS: Between July 1, 1994, and May 30, 2014, 2611 patients underwent patch testing by the senior author. Of these, 165 were classified as HCWs based on their primary occupation. Statistical analysis was done using a χ test. RESULTS: Health care workers were more likely than NHCWs to be women and to have hand dermatitis. Women, but not men, HCWs suffered more irritant contact dermatitis. Health care workers had significantly more work-related ACD, especially to formaldehyde, quaternium-15, 2-bromo-2-nitropropane-1,3-diol, cocamide diethanolamine (DEA), thiuram mix, carba mix, thimerosal, benzalkonium chloride, glutaraldehyde, and bacitracin. LIMITATIONS: Only patients suspected of having ACD were tested. Our population was geographically limited to metropolitan Kansas City, MO and metropolitan New York, NY. CONCLUSIONS: Health care workers suffer more from occupational ACD, especially of the hands, than do NHCWs, including to allergens not present on available standard allergen series.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".