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Journal of Tuberculosis and Lung Disease ›› 2022, Vol. 3 ›› Issue (3): 203-208.doi: 10.19983/j.issn.2096-8493.20220016

• Original Articles • Previous Articles     Next Articles

Study on the identification of chronic obstructive pulmonary disease symptom clusters and their subgroups

XU Yan-song1, LIU Qing-hua2, QIU Xiao-ting1()   

  1. 1Nursing Department of Zaozhuang Tumour Hospital,Shandong Province,Tengzhou 277500,China
    2Respiratory Department of Zaozhuang Tumour Hospital,Shandong Province,Tengzhou 277500,China
  • Received:2022-02-14 Online:2022-06-20 Published:2022-06-15
  • Contact: QIU Xiao-ting E-mail:2758776114@qq.com

Abstract:

Objective: To determine the composition of symptom clusters according to the incidence of different symptoms in chronic obstructive pulmonary disease (COPD) patients. Based on the intensity of experiences for different symptoms in patients within symptom clusters, we can identify the subgroups of symptom clusters and provide ideas for developing personalized clinical management strategies. Methods: A total of 165 COPD patients hospitalized in Zaozhuang Tumour Hospital of Shandong Province from August 2020 to August 2021 were selected. General data questionnaire and Memory symptom rating scale were used to investigate the severity of symptoms. Exploratory factor analysis was performed to analyze the composition of symptom clusters based on symptoms with incidences of 30% or more, and systematic cluster analysis was used to identify subgroups of each symptom cluster based on the score of the obtained symptom clusters. A total of 165 questionnaires were issued with convenience sampling method, and all of them were effectively retrieved. Results: The five most common symptoms in hospitalized COPD patients were shortness of breath (87.27%, 144/165), cough (84.85%,140/165), anenergia (57.58%,95/165), dry mouth (51.52%,85/165), drowsy (46.06%,76/165). Factor analysis identified three symptom clusters: affective symptom cluster, cough-fatigue symptom cluster and pain-shortness of breath symptom cluster, and the cumulative variance contribution rate was 56.34%. Cluster analysis showed that there were differences in symptom experiences among patients in the three symptom clusters, and two symptom sub-groups were identified for each symptom cluster. Conclusion: COPD patients experience complex symptoms that are correlated and present as clusters of symptoms. Patients experience different intensities of symptoms in the cluster, which can be divided into subgroups for symptom clusters. The identification of symptom clusters and their subgroups can provide a basis for medical staff to comprehensively evaluate the condition and formulate individualized intervention measures in advance, thus promote the recovery of patients to a greater extent.

Key words: Pulmonary disease,chronic obstructive, Signs and symptoms, Respiratory, Cluster analysis

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