ArticleClinical and translational allergy2023
Pollen grading prediction scale for patients with Artemisia pollen allergy in China: A 3-day moving predictive model.
Article in Clinical and translational allergy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- Research on pollen allergy in Fuzhou, China: from the online public concern surveys to pollen monitoring.Frontiers in public health · 2026Article
- Genetic mechanisms of pollinosis: interactions between genes and environmental factors.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2025Review
- Inhaled Allergy Diagnostics and Treatment in a Polluted Environment.International journal of molecular sciences · 2025Review
- Article
- [Clinical characteristics of allergic rhinitis induced by pollen in northern China].Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery · 2025Article
- Pollen grading prediction scale for patients with Artemisia pollen allergy in China: A 3-day moving predictive model.Clinical and translational allergy · 2023Article
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundArtemisia pollen is the most prevalent outdoor aeroallergen causing respiratory allergies in Beijing, China. Pollen allergen concentrations have a direct impact on the quality of life of those suffering from allergies. Artemisia pollen deposition grading predictions can provide early warning for the protection and treatment of patients as well as provide a scientific basis for allergen specific clinical immunotherapy.
objectiveTo develop a model of Artemisia pollen grading to predict development in patients with pollen allergy.
methodsArtemisia pollen data from four pollen monitoring stations in Beijing as well as the number of Artemisia pollen allergen serum specific immunoglobulin E positive cases in Beijing Tongren Hospital from 2014 to 2016 were used to develop a statistical model of pollen deposition and provide optimised threshold values.
resultsA logarithmic correlation existed between the number of patients with Artemisia pollen allergy and Artemisia pollen deposition, and the average pollen deposition for three consecutive days was most correlated with the number of allergic patients. Based on the threshold of the number of patients and the characteristics of Artemisia pollen, a five-stage pollen deposition grading model was developed to predict the degree of pollen allergy.
conclusionsGraded prediction of pollen deposition may help pollen allergic populations benefit from preventive interventions before onset.
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