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Developing nomograms for identifying allergic rhinitis among chronic rhinitis: A real-world study

BACKGROUND: It is difficult to discriminate allergic rhinitis (AR) and nonallergic rhinitis (NAR) in clinical practice due to the similar clinical manifestations. The study was to assess both the demographical and clinical features of AR and NAR in the real-world data of outpatients in China. METHOD...

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Detalles Bibliográficos
Autores principales: Huang, Yanran, Wang, Chengshuo, Zhang, Yuan, Zhang, Luo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: World Allergy Organization 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8054181/
https://www.ncbi.nlm.nih.gov/pubmed/33912321
http://dx.doi.org/10.1016/j.waojou.2021.100534
Descripción
Sumario:BACKGROUND: It is difficult to discriminate allergic rhinitis (AR) and nonallergic rhinitis (NAR) in clinical practice due to the similar clinical manifestations. The study was to assess both the demographical and clinical features of AR and NAR in the real-world data of outpatients in China. METHODS: It was a cross-sectional real-world study. AR and NAR were defined based on both subjective symptoms and objective specific serum IgE test. General demographic characteristics as well as clinical information were documented. Patients were further classified according the seasons of initial visiting hospital (during pollen seasons or not). A scoring system presented as nomograms for presence of AR was performed. RESULTS: In the pollen season group, age distribution, the duration of rhinitis, comorbidity of asthma, food allergies, and score of coughing were found significantly associated with AR. Additionally, in the non-pollen season group, we found that ethnicity, age distributions, duration of rhinitis, comorbidity of asthma, food allergies, and family history of allergy, together with scores of gritty eyes were associated factors of AR. Based on multivariate logistic model, we built two nomograms which included previously identified significant risk factors that could be acquired easily during clinical practice with predictive variables to assess their roles in predicting the risk of AR among outpatients with rhinitis. CONCLUSIONS: The characteristics of patients with different phenotypes of chronic rhinitis are distinctive in different seasons and the developed nomogram in this study might be beneficial for clinical practice.