Identification of Symptom Clusters and Their Influencing Factors in Subgroups of Chinese Patients With Acute Exacerbation of Chronic Obstructive Pulmonary Disease

J Pain Symptom Manage. 2020 Sep;60(3):559-567. doi: 10.1016/j.jpainsymman.2020.03.037. Epub 2020 Apr 7.

Abstract

Context: Limited studies have identified symptom clusters (SCs) and their risk factors and the relationships with inflammatory biomarkers in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD).

Objectives: In this study, we aimed to investigate SCs in patients with AECOPD and explore their influencing factors and relationships with inflammatory biomarkers.

Methods: Data were collected with sociodemographic and disease information questionnaires, and symptoms were measured with the revised Memorial Symptom Assessment Scale. SCs were extracted through exploratory factor analysis. Logistic regression analysis was conducted to explore the risk factors of SCs.

Results: A total of 151 patients were recruited. Two SCs, namely, emotional and respiratory functional SCs, were identified. Logistic regression analysis showed that individuals with high C-reactive protein level, Charlson Comorbidity Index score, and high modified Medical Research Council Dyspnea Scale score were more likely to belong to the high-severity symptom subgroup than to the low-severity symptom group in the emotional SC. The patients with a low body mass index and without or lax inhaled drug therapy exhibited highly prominent predictors of membership in the high-severity symptom group of the respiratory functional SC.

Conclusion: Symptoms experienced by patients with AECOPD were grouped into specific clusters. Targeted interventions should be performed based on SCs, and influencing factors and biological mechanisms should be considered when providing individualized approaches and interventions.

Keywords: AECOPD; C-reactive protein; Symptom severity; exploratory factor analysis; procalcitonin; symptom cluster.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers
  • China / epidemiology
  • Humans
  • Pulmonary Disease, Chronic Obstructive* / epidemiology
  • Risk Factors
  • Syndrome

Substances

  • Biomarkers