Sensitization to Formaldehyde in Northeastern Italy, 1996 to 2012
Bibliographic record
Abstract
BACKGROUND: Formaldehyde is a widely used organic compound, used in several applications (hard thermoset resins, adhesives, disinfectants, tissue fixatives, etc), in its free form or released by formaldehyde releaser products. Its use is under control due to its toxic, carcinogenic, and allergenic properties. OBJECTIVE: The aim of this study was to investigate the frequency of formaldehyde sensitization, time trend, and correlation to occupations. METHODS: This study is a cross-sectional study on a population of 23,774 patients tested from 1996 to 2012 in Northeastern Italy. RESULTS: Frequency of sensitization was 3.3%, without any significant time trend. Hands (39.8% overall) and face (25.6% females, 15.5% males) were mainly involved. We found a trend toward decrease by age in females (3.11% in first quintile [14-26 years], 2.29% in fifth quintile [59-97 years], P < 0.01). On a logistic regression analysis (control group: white-collar workers), we found associations in health care (odds ratio [OR], 1.37; 95% confidence interval [CI], 1.04-1.81), wood (OR, 2.14; 95% CI, 1.30-3.51), and textile (OR, 1.79; 95% CI, 1.14-2.79) sectors and professional drivers (OR, 1.94; 95% CI, 1.05-3.60). We found a high rate of cosensitization to formaldehyde in patients with positive patch test reactions to quaternium-15 (OR, 18.7; 95% CI, 12.6-27.7). CONCLUSIONS: Sensitization to formaldehyde is relevant in our population, especially in the health care sector, wood and textile industries, and professional drivers. No significant time trend was found.
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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 | 0.001 | 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".