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

Research Trends of Traditional Chinese Medicine Therapies on Chronic Obstructive Pulmonary Disease: A Bibliometric Analysis

BACKGROUND

Traditional Chinese Medicine (TCM) therapies have shown great improvement in chronic obstructive pulmonary disease (COPD) patients, yet no bibliometric analysis on TCM therapies for COPD exists.

SUMMARY

A comprehensive literature search was conducted on TCM therapies for COPD within the past decade, utilizing the Web of Science (WOS) Core Collection and China National Knowledge Infrastructure (CNKI) databases. To analyze collaborative patterns among countries/regions, institutions, and authors, as well as identify influential references and emerging research trends, CiteSpace and VOSviewer software were employed. The dataset comprised 625 articles from WOS and 5,641 from CNKI, revealing a consistent growth in COPD-related TCM research over the past 10 years. China emerged as the leading contributor, with a predominant focus on TCM Universities. The American Journal of Respiratory and Critical Care Medicine was the most cited journal, while Medicine published the highest number of articles. Li JS was the most prolific author, and Barnes PJ was the most frequently cited researcher. Key studies by Leung RWM [Eur Respir J. 2013;41(5):1051-7], Li SY [BMC Complement Altern Med. 2012;12:197], and Polkey MI [Chest. 2018;153(5):1116-24] garnered significant attention. Keyword analysis highlighted the prominence of Tai Chi, Chinese herbal medicine, acupoint sticking, acupuncture, lung function, quality of life, and inflammation as core research themes.

KEY MESSAGES

Research on TCM therapies for COPD has gained growing attention over the past decade. Among the most commonly studied TCM interventions are Tai Chi, Chinese herbal medicine, acupoint sticking, and acupuncture. Lung function, quality of life, and inflammation have emerged as key areas of investigation and are likely to remain focal points for future research endeavors.

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

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.

A Structural Equation Model of the Relationship Between Symptom Burden, Psychological Resilience, Coping Styles, Social Support, and Psychological Distress in Elderly Patients With Acute Exacerbation Chronic Obstructive Pulmonary Disease in China

PURPOSE

The prevalence of psychological distress is frequently observed among old adults with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). However, current researches are insufficient to clarify the correlation among these relevant factors. This study examined the effects of symptom burden, psychological resilience, coping styles, and social support on psychological distress.

METHODS

Two hundred fifty five elderly patients with AECOPD were conveniently selected in Taian, Shandong Province. The General Information Questionnaire, Distress Thermometer, The Revised Memorial Symptom Assessment Scale, Connor-Davidson Resilience Scale, Simplified Coping Style Questionnaire, Perceived Social Support Scale were used to investigate. The relationship among factors was estimated by using a structural equation model.

RESULTS

Psychological distress score of elderly patients with AECOPD was (5.25 ± 1.01); coping styles, psychological resilience, symptom burden, and social support directly affected psychological distress (the direct effects were -.93, .17, .17, and -.09); coping styles had the largest total effect on psychological distress (the total effect was -.93); psychological resilience indirectly affected psychological distress through coping styles (the indirect effect was -.74); symptom burden indirectly affected psychological distress through psychological resilience (the indirect effect was .25); social support indirectly affected psychological distress through symptom burden, psychological resilience, and coping styles (the indirect effect was -.80).

CONCLUSION

The psychological distress of elderly patients with AECOPD is at a moderate level; coping styles, psychological resilience, and social support have positive effects on alleviating the psychological distress of elderly patients with AECOPD; symptom burden is negatively correlated with psychological distress. Healthcare professionals should pay more attention to elderly patients with AECOPD who are particularly prone to experience higher levels of psychological distress, especially in the presence of low coping style, limited psychological resilience, inadequate levels of social support, and high symptom burden.

Exploring the impact of OSA on short-term survival in patients with AECOPD admitted to the ICU

BACKGROUND

Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is characterized by a sudden worsening of chronic obstructive pulmonary disease (COPD) symptoms, which significantly contributes to hospitalizations related to COPD symptoms. Previous research has mainly focused on the correlation between obstructive sleep apnea (OSA) and COPD. However, there were few studies that investigated the short-term mortality rate of AECOPD patients with or without OSA.

METHODS

Data for our research was taken from the Medical Information Mart for Intensive Care Database IV. A total of 1332 patients were included in the study based on well-defined criteria for selection and exclusion. By analyzing the characteristics of AECOPD patients, we compared those with and without OSA.

RESULTS

There were 1122 AECOPD patients without OSA, 210 patients with OSA. In comparison to those without OSA, patients with OSA exhibited lower 30-day and 90-day ICU mortality with unadjusted HR, as well as lower hospital mortality with unadjusted OR. However, after adjustments were made, there were no significant associations observed between OSA and short-term mortality, including 30-day ICU mortality, 90-day ICU mortality, ICU mortality, and hospital mortality in AECOPD patients. Subgroup analysis revealed that OSA may act as a risk factor for AECOPD patients with a BMI lower than 30 kg/m2.

CONCLUSIONS

There is no impact on short-term survival in AECOPD patients with OSA under intensive care unit (ICU) management and nursing.

Symptom clusters, associated factors and health-related quality of life in patients with chronic obstructive pulmonary disease: A structural equation modelling analysis

AIMS AND OBJECTIVES

To identify symptom clusters and develop a symptom cluster model among people living with chronic obstructive pulmonary disease (COPD).

BACKGROUND

The examination of symptom clusters in COPD patients is an emerging field of scientific inquiry directed towards symptom management. However, no studies have modelled the relationships among symptom clusters, associated factors and health-related quality of life.

DESIGN

A cross-sectional design with convenience sampling following STROBE guidelines.

METHODS

Data were collected from 450 COPD participants in three university teaching hospitals. Participants were invited to complete a structured questionnaire comprised of a socio-demographic/clinical questionnaire, Integrated Palliative Care Outcome Scale and Clinical Respiratory Questionnaire. Exploratory factor analysis and confirmatory factor analysis were used to identify symptom clusters. Structural equation modelling was used to examine the proposed model.

RESULTS

The respiratory related symptom cluster, psychological symptom cluster and cough-insomnia related symptom cluster were identified. The final model demonstrated a good fit with the data. Gender, stage of disease and monthly income were significant factors associated with symptom clusters. Respiratory related and cough-insomnia related symptom clusters had a direct negative impact on health-related quality of life, while the psychological symptom cluster was found to have a direct and indirect negative effect on health-related quality of life.

CONCLUSIONS

Final COPD symptom cluster model should serve as a framework to guide intervention research targeting symptom clusters to improve health-related quality of life of people living with COPD.

RELEVANCE TO CLINICAL PRACTICE

Nurses should be especially attuned to identify those at most risk of facing a higher symptom burden in this case those who are female, have advanced stage COPD and/or lower income. During the clinical symptom assessment, nurses should pay attention to the close relationships among symptoms within a cluster to identify any 'trigger' symptom that could cause the development or exacerbation of other symptoms.

A nomogram for predicting lung-related diseases among construction workers in Wuhan, China

Objective

To develop a prediction nomogram for the risk of lung-related diseases (LRD) in construction workers.

Methods

Seven hundred and fifty-two construction workers were recruited. A self- designed questionnaire was performed to collected relevant information. Chest X-ray was taken to judge builders' lung health. The potential predictors subsets of the risk of LRD were screened by the least absolute shrinkage and selection operator regression and univariate analysis, and determined by using multivariate logistic regression analysis, then were used for developing a prediction nomogram for the risk of LRD. C-index, calibration curve, receiver operating characteristic curve, decision curve analysis (DCA) and clinical impact curve analysis (CICA) were used to evaluation the identification, calibration, predictive ability and clinical effectiveness of the nomogram.

Results

Five hundred and twenty-six construction workers were allocated to training group and 226 to validation group. The predictors included in the nomogram were symptoms, years of dust exposure, work in shifts and labor intensity. Our model showed good discrimination ability, with a bootstrap-corrected C index of 0.931 (95% CI = 0.906-0.956), and had well-fitted calibration curves. The area under the curve (AUC) of the nomogram were (95% CI = 0.906-0.956) and 0.945 (95% CI = 0.891-0.999) in the training and validation groups, respectively. The results of DCA and CICA indicated that the nomogram may have clinical usefulness.

Conclusion

We established and validated a novel nomogram that can provide individual prediction of LRD for construction workers. This practical prediction model may help occupational physicians in decision making and design of occupational health examination.

Advances in Conceptual and Methodological Issues in Symptom Cluster Research: A 20-Year Perspective

Two conceptual approaches are used to evaluate symptom clusters: "clustering" symptoms (ie, variable-centered analytic approach) and "clustering" patients (ie, person-centered analytic approach). However, these methods are not used consistently and conceptual clarity is needed. Given the emergence of novel methods to evaluate symptom clusters, a review of the conceptual basis for older and newer analytic methods is warranted. Therefore, this article will review the conceptual basis for symptom cluster research; compare and contrast the conceptual basis for using variable-centered versus patient-centered analytic approaches in symptom cluster research; review their strengths and weaknesses; and compare their applications in symptom cluster research.

The Effect of Symptom Clusters and Sleep Disorder on Quality of Life among Patients with Chronic Obstructive Pulmonary Disease

Background

Symptoms (cough, dyspnea, fatigue, depression, and sleep disorder) in chronic obstructive pulmonary disease (COPD) are related to poor quality of life (QOL). Better understanding of the symptom clusters (SCs) and sleep disorder in COPD patients could help to accelerate the development of symptom-management interventions.

Objective

We aim to explore the effect of sleep disorder and symptom clusters on the QOL in patients with COPD.

Methods

223 patients with stable COPD from November 2019 to November 2020 at the Affiliated People's Hospital of Ningbo University in China were included in this cross-sectional survey. A demographic and clinical characteristics questionnaire, the Revised Memorial Symptom Assessment Scale (RMSAS), the Pittsburgh Sleep Quality Index (PSQI), and the St George Respiratory Questionnaire for COPD (SGRQ-C) were completed by the patients. Exploratory factor analysis was conducted to extract SCs, and logistic regression analysis was performed to analyze the risk factors affecting QOL.

Results

Three clusters were extracted: respiratory functional cluster, emotional cluster, and fatigue-sleep cluster. 70.4% of the participants were poor sleepers. Subgroup analysis showed that COPD patients with poor sleep quality were significantly different in QOL, emotional cluster, and fatigue-sleep cluster compared with patients with normal sleep. In multiple regression, sleep quality and respiratory functional cluster were associated with QOL.

Conclusion

In patients with stable COPD, three symptom clusters were explored. Symptom clusters correlate with clinical features and negatively affect QOL. Appropriate interventions are expected to inform future approaches to symptom management. Future studies are needed to test interventions that may be effective at improving the QOL of COPD patients.

Chronic Obstructive Pulmonary Disease Symptom Cluster Composition, Associated Factors, and Methodologies: A Systematic Review

This systematic review details symptom clusters, their compositions, and associated factors and appraises the methodologies of studies that reported symptom clusters in patients with chronic obstructive pulmonary disease (COPD). Ten studies were eligible for inclusion in this study. Four common symptom clusters were identified. Two theoretical frameworks, four statistical methods, and various symptom assessment tools were used to identify symptom clusters. Factors associated with symptom clusters included demographic, clinical, and biological factors. No studies examined the subjective experiences of symptom clusters. Overall, inconsistencies were identified in the composition of symptom clusters across studies. This may be due to variations in study design, assessment tools, and statistical methods. Future studies should attempt to arrive at a common definition, especially that is theoretically derived, for symptom clusters, standardize the criteria for symptoms for inclusion in the clusters, and focus on patients' subjective experience to inform which clusters are clinically relevant.