Incidence and Determinants of IgE-mediated Sensitization in Apprentices
Bibliographic record
Abstract
We investigated prospectively the incidence and determinants of work-related specific skin sensitization in a cohort of 769 apprentices, including 417 in animal health technology, 230 in pastry-making, and 122 in dental-hygiene technology. Subjects were recruited when starting exposure to laboratory animals, flour, or latex. A questionnaire and skin-prick tests with common and work-related allergens were administered on entry and at follow-up visits from 8 to 44 mo; information on number of hours of exposure to specific allergens was obtained. Among 769 apprentices, 698 attended >/= 1 follow-up visit. A total of 111 subjects developed specific sensitization over the study period. The incidence of work-related sensitization (per person-year) was 8.9% (95% CI 7.3 to 11.0%) in the animal-health program, 4.2% (95% CI 1.8 to 8.2%) in the pastry-making program, and 2.5% (95% CI = 0.7 to 4.3%) in the dental-hygiene program. In the animal health group, Cox regression analyses showed that atopy, nasal, and respiratory symptoms in the pollen season, and exposure assessed by the school attended or by duration of exposure to rodents were the most significant predictors of sensitization. In the dental-hygiene program, atopy and asthma were significant determinants. This study shows that: (1) an apprenticeship in animal-health technology carries a greater risk of developing specific sensitization than do apprenticeships in pastry-making and dental-hygiene; (2) atopy, respiratory symptoms in the pollen season, and number of hours in contact with rodents determine the risk of sensitization in apprentices in the animal health program.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".