Is foundry work a risk for cardiovascular disease? A systematic review
Bibliographic record
Abstract
UNLABELLED: Aims Foundry work has been associated with an increased risk of adverse cardiovascular events. The objective of this review was systematically and qualitatively to review the published literature to determine whether foundry work is significantly associated with cardiac disease. METHODS: MEDLINE and Cochrane databases were systematically searched to identify relevant English-language publications between 1966 and October 2002. Articles were rated as 'good', 'fair' or 'poor', using published quality review criteria. Additionally, variables suggesting causality were extracted. A qualitative summation of the literature was presented for two scenarios: all studies, or using only studies rated 'fair' and above. RESULTS: Fourteen studies were analysed. Four were found to be of 'fair' quality, the remainder 'poor'. No 'good' quality studies were found. Nine studies show increased cardiac mortality among foundry worker groups and four studies also show a decreased risk. When only 'fair' quality studies are taken into consideration, two support increased risk of cardiac disease, one supports a protective effect of foundry work on cardiac disease and one revealed both increased and decreased risk for different cardiac outcomes. CONCLUSIONS: The exploration of foundry workers' risks of cardiac events reveals conflicting findings, which can only be partly attributed to confounders. Further prospective research to establish the independent contribution of foundry work to cardiac disease is needed.
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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 | 0.008 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".