Evidence map›Paper›PMID 41667969›Full record

ArticleBMC infectious diseases2026

Network analysis of symptom clusters among patients with pulmonary tuberculosis: a cross-sectional study.

Hanhan Kong, Chang Liu, Xiao Wang, Dan Wu, Lin Tang, Zijiao Chen, Jinbing Bai, Min Wen

Abstract read
In one paragraph

Article in BMC infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Hanhan KongShenzhen Third People's Hospital, 29 Bulan Road, Longgang District, Shenzhen City, Guangdong Province, 518112, China.
Chang LiuShenzhen Third People's Hospital, 29 Bulan Road, Longgang District, Shenzhen City, Guangdong Province, 518112, China.
Xiao WangShenzhen Third People's Hospital, 29 Bulan Road, Longgang District, Shenzhen City, Guangdong Province, 518112, China.
Dan WuShenzhen Third People's Hospital, 29 Bulan Road, Longgang District, Shenzhen City, Guangdong Province, 518112, China.
Lin TangShenzhen Third People's Hospital, 29 Bulan Road, Longgang District, Shenzhen City, Guangdong Province, 518112, China.
Zijiao ChenShenzhen Third People's Hospital, 29 Bulan Road, Longgang District, Shenzhen City, Guangdong Province, 518112, China.
Jinbing BaiEmory University Nell Hodgson Woodruff School of Nursing, Atlanta, GA, USA.
Min WenShenzhen Third People's Hospital, 29 Bulan Road, Longgang District, Shenzhen City, Guangdong Province, 518112, China. Wenmin5hlb@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients with pulmonary tuberculosis (PTB) experience complex and co-occurring symptoms. Understanding the structure of these symptom clusters and their interrelationships is crucial for effective management. This study aimed to map the symptom network and identify core symptoms and clusters among PTB patients in China and targets for precise intervention.

methodsA convenience sampling method was used to recruit 356 pulmonary tuberculosis patients between November 2024 and April 2025 from Shenzhen Third People's Hospital. Data were collected using a sociodemographic questionnaire and the Chinese version of the Memorial Symptom Assessment Scale (MSAS-C), a valid and reliable instrument (Cronbach's α = 0.87) for this population. Data normality was assessed using Shapiro-Wilk tests; non-normally distributed continuous variables were expressed as median and interquartile range. Exploratory factor analysis was used to identify symptom clusters, and a symptom network was analyzed using the qgraph package in R, with strength centrality serving as the primary metric for identifying core symptoms.

resultsThe exploratory factor analysis demonstrated appropriate sampling adequacy, as indicated by a KMO value of 0.643 and a significant Bartlett's test of sphericity (χ²= 661.633, p < 0.001). This study identified four symptom clusters in patients with pulmonary tuberculosis: nutritional deficiency symptoms (eigenvalue = 2.001), inflammatory-related symptoms (eigenvalue = 1.692), somatic discomfort symptoms (eigenvalue = 1.563), and respiratory system-related symptoms (eigenvalue = 1.529). These four clusters collectively accounted for 54.76% of the total variance. The symptom network revealed edge weights ranging from |r| = 0.01 to 0.42, and centrality indices demonstrated good stability (correlation stability coefficient of strength = 0.689). Core symptoms included difficulty sleeping (strength rs = 2.691), fatigue (rs = 2.681), lack of appetite (rs = 2.654), and weight loss (rs = 2.604).

conclusionThese findings identified four symptom clusters in pulmonary tuberculosis patients, with difficulty sleeping, fatigue, lack of appetite, and weight loss constituting the core symptoms. A targeted management strategy should prioritize these core symptoms through structured monitoring and intervention. Future longitudinal studies are needed to validate symptom dynamics and develop PTB-specific assessment tools. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Tuberculosis, PulmonaryAdultAgedChinaCluster AnalysisCross-Sectional StudiesFactor Analysis, StatisticalFemaleHumansMaleMiddle AgedSurveys and QuestionnairesYoung AdultChinaCross-sectional studiesNetwork analysisPulmonary tuberculosisSymptom cluster

Identifiers

PMID41667969
PMCPMC12998172

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.