The association between air pollution and hospitalization for patients with systemic lupus erythematosus in Chile: A daily time series analysis
Bibliographic record
Abstract
Genetic and environmental factors are thought to influence the activity of systemic lupus erythematosus (SLE), but relatively little is known about the effects of ambient air pollution. Using pollution data from air monitoring stations in the urban centers in Santiago Chile, along with daily patient hospitalization data from 2001 to 2012, an association between ambient air pollution and daily hospital admissions for SLE was tested using generalized linear models. Averaged over all regions pollutant mean 24 h concentrations were: 0.96 ppm carbon monoxide (CO), 64 ppb ozone (O3), 43 ppb nitrogen dioxide (NO2), 9 ppb sulphur dioxide (SO2), 29 μg/m3 particulate matter ≤ 2.5 μm in mean aerodynamic diameter (PM2.5), and 67 μg/m3 particulate matter ≤ 10 μm in diameter (PM10). The relative risk estimates in single pollutant models for an interquartile range (IQR) increase in pollutant were: RR = 1.34 (95% CI: 1.06–1.83) for SO2, RR = 1.60 (95% CI: 1.15–2.24) for CO, and RR = 1.41 (95% CI: 1.14–1.86) for PM2.5. In two-pollutant models, the significance of SO2 and PM2.5 persisted despite adjustments for each of the other measured pollutants. These findings suggest that acute increases in air pollution increase the risk of hospitalization with a primary diagnosis of SLE.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".