Issue 3—The occupational burden of respiratory diseases, an update
Bibliographic record
Abstract
INTRODUCTION AND AIMS: Workplace exposures are widely known to cause specific occupational diseases such as silicosis and asbestosis, but they also can contribute substantially to causation of common respiratory diseases. In 2019, the American Thoracic Society (ATS) and the European Respiratory Society (ERS) published a joint statement on the occupational burden of respiratory diseases. Our aim on this narrative review is to summarise the most recent evidence published after the ATS/ERS statement as well as to provide information on traditional occupational lung diseases that can be useful for clinicians and researchers. RESULTS: Newer publications confirm the findings of the ATS/ERS statement on the role of workplace exposure in contributing to the aetiology of the respiratory diseases considered in this review (asthma, COPD, chronic bronchitis, idiopathic pulmonary fibrosis, hypersensitivity pneumonitis, infectious pneumonia). Except for COPD, chronic bronchitis and infectious pneumonia, the number of publications in the last 5 years for the other diseases is limited. For traditional occupational lung diseases such as silicosis and asbestosis, there are old as well as novel sources of exposure and their burden continues to be relevant, especially in developing countries. CONCLUSIONS: Occupational exposure remains an important risk factor for airways and interstitial lung diseases, causing occupational lung diseases and contributing substantially in the aetiology of common respiratory diseases. This information is critical for public health professionals formulating effective preventive strategies but also for clinicians in patient care. Effective action requires shared knowledge among clinicians, researchers, public health professionals, and policy makers.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".