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Cluster analysis categorizes five phenotypes of pulmonary tuberculosisopen access

Authors
Koo, Hyeon-KyoungMin, JinsooKim, Hyung WooKo, YousangOh, Jee YounJeong, Yun-JeongKang, Hyeon HuiKang, Ji YoungLee, Sung-SoonSeo, MinseokSilverman, Edwin K.Kim, Ju SangPark, Jae Seuk
Issue Date
16-Jun-2022
Publisher
NATURE PORTFOLIO
Citation
SCIENTIFIC REPORTS, v.12, no.1
Indexed
SCIE
SCOPUS
Journal Title
SCIENTIFIC REPORTS
Volume
12
Number
1
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/142799
DOI
10.1038/s41598-022-13526-1
ISSN
2045-2322
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.
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