Occupational exposures and sarcoidosis: a rapid review of the evidence
Bibliographic record
Abstract
BACKGROUND: Sarcoidosis is a rare, multisystem, inflammatory condition associated with the formation of granulomas. Diagnosis can be challenging because of non-specific symptoms complicating epidemiological investigations of its aetiology. Despite research efforts, a review of the current state of the evidence is needed. AIMS: To assess the evidence for an association between occupational exposures and the development of sarcoidosis. To determine if workers in any occupation are at a greater risk of developing sarcoidosis. METHODS: This rapid review follows the methodology suggested by the World Health Organization. Two electronic databases were systematically searched until April 2022. The methodological quality of the studies was critically appraised, and a best-evidence approach was used to synthesize the results. RESULTS: Titles and abstracts of 2916 articles were screened, with 67 full-text articles reviewed for eligibility. Among the 13 studies eligible for this review, none were of high quality (i.e. low risk of bias). Six studies exploring the association between sarcoidosis and a range of occupations and exposures, and one previous systematic review were of low quality reporting inconsistent findings. Six studies examined the risk of sarcoidosis associated with occupational silica exposure, two of which were of acceptable quality. Overall, the study methodologies and results were inadequate to support causal relationships. CONCLUSIONS: There is limited evidence of acceptable methodological quality to assess the risk of sarcoidosis associated with occupational exposures. There is a growing body of research examining occupational exposure to silica and sarcoidosis. Additional high-quality confirmatory research is needed.
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 | 0.016 | 0.068 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.025 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".