Yang Zhenjiao, Cui Miaoling, Zhang Xiaofang, Bai Jing, Tang Lian, Tan Guirong, Jiang Yun
Department of Nursing, The First Hospital Affiliated to Guangxi Medical University, Nanning, Guangxi, China.
Department of Nursing, The First Hospital Affiliated to Guangxi Medical University, Nanning, Guangxi, China.
J Pain Symptom Manage. 2020 Sep;60(3):559-567. doi: 10.1016/j.jpainsymman.2020.03.037. Epub 2020 Apr 7.
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).
In this study, we aimed to investigate SCs in patients with AECOPD and explore their influencing factors and relationships with inflammatory biomarkers.
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.
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.
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.
针对慢性阻塞性肺疾病急性加重期(AECOPD)患者的症状集群(SCs)及其危险因素以及与炎症生物标志物的关系,相关研究有限。
在本研究中,我们旨在调查AECOPD患者的SCs,并探讨其影响因素以及与炎症生物标志物的关系。
通过社会人口学和疾病信息问卷收集数据,并用修订后的纪念症状评估量表测量症状。通过探索性因素分析提取SCs。进行逻辑回归分析以探讨SCs的危险因素。
共招募了151名患者。识别出两个SCs,即情绪和呼吸功能SCs。逻辑回归分析表明,在情绪SCs中,C反应蛋白水平高、Charlson合并症指数评分高以及改良医学研究理事会呼吸困难量表评分高的个体比低严重程度症状组更有可能属于高严重程度症状亚组。体重指数低且未进行吸入药物治疗或吸入药物治疗不规范的患者是呼吸功能SCs高严重程度症状组成员的显著预测因素。
AECOPD患者经历的症状被归为特定的集群。应基于SCs进行有针对性的干预,在提供个性化方法和干预措施时应考虑影响因素和生物学机制。