Influence of Air Pollutants on the Disease Activity and Quality of Life in Rheumatoid Arthritis, an Iranian Observational Longitudinal Study
Bibliographic record
Abstract
Background: Environmental exposures and genetic predisposition interactions may result in autoimmune rheumatic diseases.This study aimed to determine the effect of outdoor air pollutants on the activity of rheumatoid arthritis (RA) in a longitudinal follow-up. Methods:We longitudinally studied 50 patients with RA bimonthly over 6 months in Mashhad, one of the most polluted cities in Iran.Disease activity and health-related quality of life (HRQoL) were examined according to the disease activity score (DAS28ESR), health assessment questionnaires (HAQ), physical health component summary (PCS), and visual analogue scale (VAS) criteria.The outdoor air pollutant was measured by monitoring the average concentration of nitrogen oxide (NO), carbon monoxide (CO), O2 level, Sulfur dioxide (SO2), and some particles less than 10 and 2.5 micrometers in diameter (PM <10 µm, PM <2.5 µm).The temperature and humidity levels were also measured.The univariate and multivariate statistical analyses were used for data analysis and the role of confounding factors was determined using the generalized estimation equation method.Results: Statistical analysis indicated a significant increase of the DAS28ESR (B = 0.04 [0.08]; P = 0.01) and VAS (B = 4.48 [1.73]; P = 0.01) by CO concentration.Moreover, a number of polluted days increased the VAS in patients.In addition, other air pollutants, temperature, and humidity were not affected significantly by the DAS28ESR and quality of life indexes by considering confounders such as medications, age, and job.Conclusion: Based on our findings, CO concentration was the only effective outdoor air pollutant that could increase RA disease activity.In addition, CO concentration and the number of polluted days make patients feel more ill.As the role of indoor air pollutants is highly important, further research on this critical topic is required to establish the role of air pollution on RA disease activity.
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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 | 0.002 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".