Comparative analysis of chronic rhinitis patient profiles during autumn pollen season between grassland and non-grassland cities in North China
Bibliographic record
Abstract
Abstract Background The symptoms of patients with respiratory disease are influenced by local environmental factors. The incidence of allergic rhinitis in grassland areas was significantly higher than that in non-grassland areas. We aimed to compare the profiles of chronic rhinitis patients obtained during the autumn pollen season in Baotou (grassland city) and Beijing (non-grassland city), China. Methods Questionnaire surveys and allergen testing were conducted on 1170 and 1232 patients with chronic rhinitis visiting the Second Affiliated Hospital of Baotou Medical College and Beijing Tongren Hospital, respectively, during the autumn pollen period. Information regarding medical history, severity of symptoms, and diagnosis and treatment was collected. Results More patients with moderate to severe chronic rhinitis and asthma (both, P < 0.001) were present in Baotou than in Beijing. Mugwort was the most abundant allergen in both regions, but the number of patients sensitized to outdoor allergens in Baotou was higher than that in Beijing ( P < 0.001). Indoor allergens in Beijing represented a considerable proportion of allergens, especially dust mites (33.4%). For patients with allergic rhinitis, nasal congestion, nasal itching, and runny nose were more severe in Baotou than in Beijing ( P < 0.001). In both Baotou and Beijing, allergy ( P < 0.001 vs. P = 0.004) and combined asthma ( P = 0.049 vs. P = 0.005) were common factors affecting the severity of the clinical symptoms chronic rhinitis. In Baotou, age ( r s = 0.195, P < 0.001) and family allergy history ( P = 0.010) were also associated with symptom severity. Although significantly more patients in Baotou received oral antihistamines, nasal corticosteroids, and surgical treatment than in Beijing ( P < 0.001), the number of people receiving allergy immunotherapy in Baotou was lower ( P = 0.004) and post-treatment symptom control was worse ( P < 0.001) that that in Beijing. Conclusions During the pollen period, there were significant differences in the allergen spectrum between Baotou and Beijing. Allergy and combined asthma were common factors affecting the severity of clinical symptoms. Patients in Baotou presented with more severe clinical symptoms that were not satisfactorily managed due to the impact of pollen exposure, inconsistent access to care, and differing treatment modalities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".