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慢性阻塞性肺疾病急性加重患者的症状网络及亚组分析:一项横断面研究

Symptom Network and Subgroup Analysis in Patients with Exacerbation of Chronic Obstructive Pulmonary Disease: A Cross-Sectional Study.

作者信息

Yu Chunchun, Xu Mengying, Pang Xinyue, Zhang Yuting, Cao Xinmei, Xu Yixin, Huang Shuai, Zhao Hongjun, Chen Chengshui

机构信息

Key Laboratory of Interventional Pulmonology of Zhejiang Province, Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People's Republic of China.

Zhejiang Province, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People's Republic of China.

出版信息

Int J Chron Obstruct Pulmon Dis. 2025 Jan 23;20:181-192. doi: 10.2147/COPD.S498792. eCollection 2025.

Abstract

PURPOSE

This study aims to construct a contemporaneous symptom network of inpatients with Exacerbation of Chronic Obstructive Pulmonary Disease (ECOPD) based on the symptom cluster, identify core and bridge symptoms, and patient subgroups with different symptom clusters based on individual differences in the intensity of patient symptom experiences.

PATIENTS AND METHODS

This study used convenience sampling to collect demographic, symptom, auxiliary examination, and prognosis information of 208 inpatients with ECOPD from April 2022 to October 2023. The data underwent exploratory factor analysis (EFA), symptom network analysis, latent class analysis (LCA), Spearman correlation analysis, Wilcoxon signed-rank test, single-factor regression and multiple-factor stepwise regression.

RESULTS

In hospitalized patients with ECOPD, symptom network analysis revealed that loss of appetite was the core symptom, while chest distress was the bridge symptom. Through LCA analysis, two symptom subgroups were identified: a high-symptom group (53.8%) and a low-symptom group (46.2%). This suggests that there is significant heterogeneity in symptom experience among ECOPD individuals. Patients in the high-symptom group had a higher probability of experiencing symptom clusters related to nutrition-sleep.

CONCLUSION

The combination of symptom network analysis and LCA comprehensively captures the symptom/symptom cluster characteristics and accounts for the heterogeneity of ECOPD patients from both individual and group perspectives. This study identifies core symptoms, bridge symptoms, and symptom subgroups, offering valuable insights for precision symptom management in ECOPD.

摘要

目的

本研究旨在基于症状簇构建慢性阻塞性肺疾病急性加重期(ECOPD)住院患者的同期症状网络,识别核心症状和桥梁症状,并根据患者症状体验强度的个体差异确定具有不同症状簇的患者亚组。

患者与方法

本研究采用便利抽样法,收集了2022年4月至2023年10月期间208例ECOPD住院患者的人口统计学、症状、辅助检查及预后信息。数据进行了探索性因子分析(EFA)、症状网络分析、潜在类别分析(LCA)、Spearman相关性分析、Wilcoxon符号秩检验、单因素回归和多因素逐步回归。

结果

在ECOPD住院患者中,症状网络分析显示食欲不振是核心症状,而胸部憋闷是桥梁症状。通过LCA分析,确定了两个症状亚组:高症状组(53.8%)和低症状组(46.2%)。这表明ECOPD个体在症状体验上存在显著异质性。高症状组患者出现与营养 - 睡眠相关症状簇的概率更高。

结论

症状网络分析与LCA相结合,从个体和群体角度全面捕捉了症状/症状簇特征,并解释了ECOPD患者的异质性。本研究确定了核心症状、桥梁症状和症状亚组,为ECOPD的精准症状管理提供了有价值的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b20/11771159/e7855de52591/COPD-20-181-g0001.jpg

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