A131: Associations of Short–Term Pollution Exposures With Childhood Autoimmune Disease
Bibliographic record
Abstract
Background/Purpose: Fine particulate matter (aerodynamic diameter less than or equal to a 2.5–mm cut point, PM2.5) is a measurable component of ambient urban pollution. Our preliminary data suggests that short‐term PM2.5 exposures are associated with the clinical presentation of Juvenile idiopathic Arthritis (JIA) in young children (). In this EPA funded project, we are further testing the hypothesis that clinical autoimmune disease presentation and exacerbation is associated with exposures to short–term pollution, focusing on PM2.5. We are establishing associations between short–term PM2.5 exposure and the clinical onset of systemic onset Juvenile Idiopathic Arthritics (soJIA) and Kawasaki Disease (KD) and the clinical exacerbation of Henoch Schonlein Purpura (HSP). Methods: Cases are from existing physician operated SoJIA and KD datasets diagnosed in United States and Canadian metropolitan regions. Cases of HSP arise from a US national hospital database (Children's Hospital Association). The study utilizes a case–crossover study design to define associations of short‐term PM2.5 with the event dates of symptom onset of soJIA and KD (fever onset) and of hospitalization for HSP exacerbation from metropolitan regions, stratified by parameters of disease activity. Results: We have assembled PM2.5 exposure measurements from urban monitors and have carefully imputed PM2.5 to provide day–to–day temporal variability and resolution for reliable time series indexes of pollution exposures for each metropolitan area (Philadelphia, Boston, Toronto, Chicago, Atlanta, Cincinnati, San Diego, Salt Lake City, Denver, Cleveland). To date, case–crossover analysis results establishing risk of the event dates of clinical symptom onset and hospitalization exacerbation for the pediatric rheumatic diseases under study are preliminary. Conclusion: Well–constructed, environmental epidemiology studies examining the triggers of disease onset and exacerbation in pediatric rheumatic diseases are few and far between. Findings from this Environmental Protection Agency funded project will have a significant impact on the field of particulate induced environmental epidemiology research of autoimmune disease.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".