已发表论文

慢性阻塞性肺疾病中国患者核心症状的识别:一项同期症状网络分析

 

Authors Yang Z, Cui M, Zhang J, Wang Z, Yao G, Fu X

Received 12 December 2024

Accepted for publication 29 June 2025

Published 22 July 2025 Volume 2025:20 Pages 2569—2579

DOI https://doi.org/10.2147/COPD.S511879

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Professor Min Zhang

Zhenjiao Yang,1 Miaoling Cui,2 Jianquan Zhang,1 Zixiu Wang,3 Guirui Yao,1 Xia Fu4 

1Department of Respiratory and Critical Care Medicine, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, People’s Republic of China; 2Department of Nursing, The First Hospital Affiliated to Guangxi Medical University, Nanning, Guangxi, People’s Republic of China; 3Department of Respiratory and Critical Care Medicine, The First Hospital Affiliated to Guangxi Medical University, Nanning, Guangxi, People’s Republic of China; 4Department of Nursing, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, People’s Republic of China

Correspondence: Xia Fu, Department of Nursing, The Eighth Affiliated Hospital, Sun Yat-sen University, No. 3025 Shennan Middle Road, Shenzhen, Guangdong Province, 518000, Email fuxia5@mail.sysu.edu.cn

Context: Patients with chronic obstructive pulmonary disease (COPD) exhibit various patterns of co-occurring complex symptoms. However, identifying core symptoms based on these distinct symptom patterns remains limited.
Objective: The aims of this current study were to explore symptom subgroups among patients with COPD based on their unique symptom experiences and to identify the core symptoms within these subgroups, along with the correlation of these core symptoms with laboratory indicators.
Methods: From May 2018 to December 2023, we recruited 252 participants with COPD through a convenience sample in China. Participants were investigated using the Revised Memorial Symptom Assessment Scale (RMSAS). Latent profile analysis (LPA) was conducted to identify symptom subgroups, while network analysis was used to reveal core symptoms among subgroups identified by LPA.
Results: Based on symptom experiences, two subgroups of patients were identified: the “low” symptom burden subgroup and the “high” symptom burden subgroup. In both the total sample and the low symptom burden subgroup, “feeling sad” was identified as the core symptom, whereas “feeling drowsy” was the core symptom in the high symptom burden subgroup. The neutrophil-to-lymphocyte ratio was associated with the severity of drowsiness.
Conclusion: This study highlights the heterogeneity among COPD patients with multiple symptoms, resulting in the identification of two distinct symptom subgroups. Addressing symptoms of sadness and drowsiness may serve as a crucial target for alleviating the overall symptom burden in individuals with COPD.

Keywords: COPD, symptom subgroup, core symptom, heterogeneity, network analysis