363 Does inhalation of silica dust cause chronic renal disease? - A systematic review
Bibliographic record
Abstract
Objective To prove the evidence for a causal relationship between exposure to silica dust and chronic renal disease, in particular Glomerulonephritis (GN) Methods The review is based on a search of the Medline database for relevant epidemiological studies published between 1987 and 2012. The quality of selected papers was evaluated based on the Newcastle-Ottawa Scale and the CASP checklist. Meta-analyses were performed separately for cohorts of workers compensated for silicosis and for industry-based cohorts. In addition, synopses were undertaken for studies based on quantitative exposure estimates and for studies using end-stage renal disease (ESRD) as the outcome. Results The review includes 10 cohorts of silicotics, 12 industry-based cohort studies, 5 case-control-studies and one pooled analysis. The pooling of the cohorts of silicotics did not show any excess risk for renal diseases (ICD-9: 580–589; SMR = 1,00 [0.84–1.18]95%). By contrast, the meta-analysis of the industry-based cohort studies showed an elevated risk (SMR = 1,42 [1.15–1.75]95%) when applying a random effects model to account for the strong heterogeneity of these studies. Five of those studies investigated the incidence of ESRD as the outcome. The corresponding relative risk estimators were in the range of 0.77 to 1.97, two of them were significantly elevated (p < 0.05). Three studies went further and investigated GN as the outcome. They resulted in markedly higher risk estimators (SIR in the range of 3.85 to 4.27) then for ESRD. Results could have been affected by a possible diagnostic bias and confounding by other occupational risk factors. Conclusion The review does not provide sufficient evidence for establishing a causal link between exposure to silica dust and chronic renal disease. To clarify this relationship, further longitudinal studies are needed, which should make use of clinical or even pre-clinical data, including data of health surveillance programs for workers with high exposure to silica dust.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".