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Risk factors for Bell’s palsy based on the Korean National Health Insurance Service National Sample Cohort data

The associations between hypertension, diabetes, and dyslipidemia with Bell’s palsy have been controversial and only a few studies have assessed risk factors for Bell’s palsy based on population-based data. The aim of the present study was to evaluate whether sociodemographic factors such as sex, ag...

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Detalles Bibliográficos
Autores principales: Jeong, Junhui, Yoon, So Ra, Lim, Hyunsun, Oh, Jangwon, Choi, Hyun Seung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8642421/
https://www.ncbi.nlm.nih.gov/pubmed/34862431
http://dx.doi.org/10.1038/s41598-021-02816-9
Descripción
Sumario:The associations between hypertension, diabetes, and dyslipidemia with Bell’s palsy have been controversial and only a few studies have assessed risk factors for Bell’s palsy based on population-based data. The aim of the present study was to evaluate whether sociodemographic factors such as sex, age, residence, household income, and metabolic diseases such as hypertension, diabetes, and dyslipidemia were risk factors for Bell’s palsy using the National Health Insurance Service National Sample Cohort data of Korea. Patients who visited an outpatient clinic twice or more or had one or more admission and received steroid medication under the International Classification of Diseases diagnostic codes for Bell’s palsy from 2006 to 2015 were defined as patients with Bell’s palsy in this study. The associations between sociodemographic factors and metabolic diseases to Bell’s palsy were analyzed with univariate and multivariate Cox proportional hazard regression models. There were 2708 patients with Bell’s palsy recorded from 2006 to 2015. Male sex, advanced age, residence in a location other than the capital and metropolitan cities, hypertension, and diabetes were significant risk factors for Bell’s palsy. This study is significant for patients and providers because we analyzed the relationships using a population-based database over a long-term follow-up period.