Incidence of cardiovascular disease in a cohort of mine workers exposed to ultrafine aluminum powder in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: A retrospective cohort study was conducted to estimate associations between an ultrafine aluminum powder, McIntyre Powder (MP), and cardiovascular disease incidence in a cohort of mine workers from Ontario, Canada. Disease outcomes included ischemic heart disease (IHD), acute myocardial infarction (AMI), congestive heart failure (CHF), and strokes and transient ischemic attacks (STIA). METHODS: Using work history records from the Ontario Mining Master File (MMF) mine workers were followed for disease incidence in administrative health records. The analysis included 25,813 mine workers who were exposed to MP between 1943 and 1979 and followed for cardiovascular disease (CVD) diagnoses between 2006 and 2018. Cardiovascular disease cases were ascertained using physician, hospital, and ambulatory care records. Poisson regression models were used to estimate age and birth-year adjusted incidence rate ratios (RR) and 95% confidence intervals (CI) for associations between MP exposure and CVD outcomes. RESULTS: Ever-exposure to MP was positively associated with modest increases in the incidence rate of IHD, AMI, and CHF, but not STIA, using both assessment approaches. Duration of self-reported MP exposure was positively associated with monotonically increasing rates of IHD and AMI compared to never-exposed miners, with the greatest association observed among miners with >20 years of exposure (for IHD: RR 1.24, 95% CI: 0.91-1.68; and for AMI: RR 1.52, 95% CI 1.01-2.28). CONCLUSION: Mine workers ever-exposed to MP had modestly elevated rates of CVD. The rate of CVD diagnoses appeared to increase with longer duration of exposure when assessed by both self-reported exposure and through historical records.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".