Long-term respiratory effects of exposure to welding fumes: Quebec apprentice cohort study
Bibliographic record
Abstract
Background: Welding fumes are known to cause respiratory health problems. Aims and Objectives: We evaluated the long-term respiratory effects of exposure to welding fumes. Methods: Inception cohorts of welding, plumbing and heating apprentices were prospectively contacted 7-17 years post-apprenticeship. Questionnaires, spirometry and non-specific bronchial hyper-responsiveness (NSBHR) test were repeatedly administered. Long-term evaluation was done in 90 of 330 former apprentices at the Hôpital du Sacré-Cœur de Montréal between 2013 and 2017. Characteristics at the end of apprenticeship were comparable between subjects who participated and who did not. The risk of work-related lower respiratory symptoms suggestive of occupational asthma (OA) and excessive lung function decline given continued post-apprenticeship exposure to welding fumes was estimated with Cox regression. Results: Incident symptoms suggestive of OA was found in 25.8% subjects and excessive lung function decline was observed in 12.7% subjects. Based on an asthma-specific job exposure matrix, post-apprenticeship exposure to welding fumes was significantly associated with a reduced risk of developing symptoms suggestive of OA (hazards ratio (HR) 0.24; 95% confidence interval (CI) 0.06-0.91). The association persisted after adjusting for obesity, self-reported wheezing, and NSBHR at the end of apprenticeship (HR 0.22; 95% CI 0.05-1.0). A reduced risk of developing excessive lung function decline was also found, but the association was not significant (HR 0.63; 95% CI 0.07-5.3). Conclusions: Continued post-apprenticeship exposure to welding fumes was not associated with an increased risk of developing long-term respiratory outcomes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".