Clinical phenotypes of chronic cough categorised by cluster analysis

Jiyeon Kang, Woo Jung Seo, Jieun Kang, So Hee Park, Hyung Koo Kang, Hye Kyeong Park, Sung-Soon Lee, Ji-Yong Moon, Deog Kyeom Kim, Seung Hun Jang, Jin Woo Kim, Minseok Seo and Hyeon-Kyoung Koo

PLOS ONE, 2023, vol. 18, issue 3, 1-11

Abstract: Background: Chronic cough is a heterogeneous disease with various aetiologies that are difficult to determine. Our study aimed to categorise the phenotypes of chronic cough. Methods: Adult patients with chronic cough were assessed based on the characteristics and severity of their cough using the COugh Assessment Test (COAT) and the Korean version of the Leicester Cough Questionnaire. A cluster analysis was performed using the K-prototype, and the variables to be included were determined using a correlation network. Results: In total, 255 participants were included in the analysis. Based on the correlation network, age, score for each item, and total COAT score were selected for the cluster analysis. Four clusters were identified and characterised as follows: 1) elderly with mild cough, 2) middle-aged with less severe cough, 3) relatively male-predominant youth with severe cough, and 4) female-predominant elderly with severe cough. All clusters had distinct demographic and symptomatic characteristics and underlying causes. Conclusions: Cluster analysis of age, score for each item, and total COAT score identified 4 distinct phenotypes of chronic cough with significant differences in the aetiologies. Subgrouping patients with chronic cough into homogenous phenotypes could provide a stratified medical approach for individualising diagnostic and therapeutic strategies.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0283352

DOI: 10.1371/journal.pone.0283352

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