Results of evaluating health care workers with prick and patch testing
Bibliographic record
Abstract
BACKGROUND: Health care workers are exposed to many agents that can cause irritant or allergic contact dermatitis. Recently, much attention has been focused on latex sensitivity, which commonly causes contact urticaria. Most studies have examined the conditions of irritant or allergic contact dermatitis and contact urticaria independently. Therefore, we have little information about the possible occurrence of these conditions in the context of combined assessment including both prick and patch testing. OBJECTIVE: To determine the prevalence of irritant and allergic contact dermatitis and contact urticaria in a group of health care workers presenting with skin problems. METHODS: Retrospective review of health care workers assessed by both prick and patch testing in an occupational health clinic. RESULTS: The diagnoses included 61% with irritant contact dermatitis, 31% with allergic contact dermatitis, and 27% with contact urticaria to latex. Eleven percent had both allergic contact dermatitis related to thiuram and contact urticaria to latex. Ninety five percent were deemed to be work-related. CONCLUSION: Health care workers presenting with skin complaints should be assessed with both prick and patch testing.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".