Contact Dermatitis in Northeast Italy Mechanics (1996–2016)
Bibliographic record
Abstract
BACKGROUND: Mechanics are at higher risk to develop occupational skin diseases from exposure to irritants, oils, greases, preservatives, and metals. AIMS: The aim of the study was to investigate contact dermatitis in mechanics who underwent patch test in Northeastern Italy and compare them with white-collar workers (WCW). SUBJECTS AND METHODS: From 1996 to 2016, 27,381 patients with suspected allergic contact dermatitis were patch tested in Northeastern Italy; in this group, 1270 mechanics were studied. Odds ratios (ORs) and 95% confidence interval (CI), adjusted by age and sex, were calculated assuming WCW as the reference category (n = 6933). RESULTS: Mechanics represented 4.6% of the population tested. Their mean ± SD age was 36.1 ± 11.2 years. Compared with WCW, they were found to have an increased risk of occupational dermatitis (OR = 14.4; 95% CI = 11.6-18) and hand/forearm dermatitis (OR = 2.5; 95% CI = 2.3-2.9). They presented an increased risk of sensitization to epoxy resin (OR = 2.7; 95% CI = 1.5-4.8), to thiurams (OR = 2.4; 95% CI = 1.5-3.8), to 2-mercaptobenzothiazole (OR = 1.9; 95% CI = 1.1-3.4), and to diaminodiphenylmethane (OR = 1.7; 95% CI = 1.1-2.5). CONCLUSIONS: Compared to WCW, mechanics were found to be at higher risk to develop occupational contact dermatitis, associated mainly to sensitization to epoxy resin and rubber accelerators.
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 | 0.001 |
| 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) | 0.002 | 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".