Time-Series Analysis of the Association Between Daily Outpatient Visits for Adult Atopic Dermatitis and Air Pollution in Beijing
Bibliographic record
Abstract
Abstract: Background: Few studies have examined the potential impact of air pollutants on atopic dermatitis (AD) in adults. Objective: This study aims to assess the relationship between atmospheric pollutants and the frequency of daily outpatient visits for AD in adults in Beijing. Methods: Data from Xiyuan Hospital were analyzed to assess the relationship between atmospheric pollutants and the frequency of daily outpatient visits for AD in adults in Beijing. Results: For individuals aged 41–60 years, a 10 μ g/m 3 increase in particulate matter (PM) 2.5 , PM 10 , nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ), and ozone (O 3 ) corresponded to a 0.3–2.9 increase, while a 10 mg/m 3 increase in carbon monoxide (CO) was associated with a 3.4 increase (odds ratio [OR] = 1.034; 95% confidence interval [CI]: 1.014–1.054). Among individuals aged ≥60 years, a positive association with all pollutants was observed, particularly CO, presenting the strongest link to outpatient visits on day 6 (OR = 1.024; 95% CI: 1.003–1.044). Adult female patients with AD exhibited heightened susceptibility to air pollution, as evidenced by the positive correlations between the concentrations of PM 2.5 , PM 10 , SO 2 , CO, NO 2 , and O 3 and the frequency of female outpatient visits. Conclusion: These findings highlight the positive relationship between air pollution and outpatient visits in adult patients with AD.
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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 | 0.000 |
| 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 | 0.000 |
| 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".