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Cluster analysis categorizes five phenotypes of pulmonary tuberculosis

Authors :
Hyeon-Kyoung Koo
Jinsoo Min
Hyung Woo Kim
Yousang Ko
Jee Youn Oh
Yun-Jeong Jeong
Hyeon Hui Kang
Ji Young Kang
Sung-Soon Lee
Minseok Seo
Edwin K. Silverman
Ju Sang Kim
Jae Seuk Park
Source :
Scientific Reports, Vol 12, Iss 1, Pp 1-10 (2022)
Publication Year :
2022
Publisher :
Nature Portfolio, 2022.

Abstract

Abstract Tuberculosis (TB) has a heterogeneous phenotype, which makes it challenging to diagnose. Our study aimed to identify TB phenotypes through cluster analysis and compare their initial symptomatic, microbiological and radiographic characteristics. We systemically collected data of notified TB patients notified in Korea and constructed a prospective, observational cohort database. Cluster analysis was performed using K-means clustering, and the variables to be included were determined by correlation network. A total of 4,370 subjects with pulmonary TB were enrolled in the study. Based on the correlation network, age and body mass index (BMI) were selected for the cluster analysis. Five clusters were identified and characterised as follows: (1) middle-aged overweight male dominance, (2) young-aged relatively female dominance without comorbidities, (3) middle-aged underweight male dominance, (4) overweight elderly with comorbidities and (5) underweight elderly with comorbidities. All clusters had distinct demographic and symptomatic characteristics. Initial microbiologic burdens and radiographic features also varied, including the presence of cavities and bilateral infiltration, which reflect TB-related severity. Cluster analysis of age and BMI identified five phenotypes of pulmonary TB with significant differences at initial clinical presentations. Further studies are necessary to validate our results and to assess their clinical implications.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
20452322
Volume :
12
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Scientific Reports
Publication Type :
Academic Journal
Accession number :
edsdoj.7bbd9bf68d624d4dbe13ab913da6e948
Document Type :
article
Full Text :
https://doi.org/10.1038/s41598-022-13526-1