ArticleJournal of clinical nursing2014
Symptom cluster, healthcare use and mortality in patients with severe chronic obstructive pulmonary disease.
Article in Journal of clinical nursing, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 33 citations in OpenAlex.
- Symptom Clusters of Chronic Obstructive Pulmonary Disease and Their Correlation With Health-Related Quality of Life: A Systematic Review.Nursing open · 2026Pooled it
- Chronic Obstructive Pulmonary Disease Symptom Cluster Composition, Associated Factors, and Methodologies: A Systematic Review.Western journal of nursing research · 2022Pooled it
- Transdiagnostic Symptoms in Electronic Health Records of Sick-Listed Employees.Journal of occupational rehabilitation · 2026Article
- Quantifying the Degree of Fatigue in People Reporting Symptoms of Post-COVID-19 Syndrome: Results from a Rasch Analysis.Physiotherapy Canada. Physiotherapie Canada · 2025Article
- Identifying the Core Symptoms in Chinese Patients of Chronic Obstructive Pulmonary Disease: A Contemporaneous Symptom Network Analysis.International journal of chronic obstructive pulmonary disease · 2025Article
- Effect of Anticipatory Nursing on Psychological Status and Quality of Life in Patients with Chronic Obstructive Pulmonary Disease: A Quasi-Experimental Study.International journal of chronic obstructive pulmonary disease · 2025Article
- Association of Patient-Reported Outcome Patterns and Major Clinical Factors with Frailty in Stable COPD.International journal of chronic obstructive pulmonary disease · 2025Article
- Symptom phenotyping in people with cystic fibrosis during acute pulmonary exacerbations using machine-learning K-means clustering analysis.Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society · 2024Article
- Predicting return of lung function after a pulmonary exacerbation using the cystic fibrosis respiratory symptom diary-chronic respiratory infection symptom scale.BMC pulmonary medicine · 2024Observational
- A Mixed Methods Evaluation of a Pilot Multidisciplinary Breathlessness Support Service.Evaluation review · 2023Article
- Symptom clusters, associated factors and health-related quality of life in patients with chronic obstructive pulmonary disease: A structural equation modelling analysis.Journal of clinical nursing · 2023Article
- Characterizing shared and distinct symptom clusters in common chronic conditions through natural language processing of nursing notes.Research in nursing & health · 2021Article
- A Proposed Theory of Symptom Cluster Management.Belitung nursing journal · 2021Article
- Could symptom burden predict subsequent healthcare use in patients with end stage kidney disease on hemodialysis care? A prospective, preliminary study.Renal failure · 2020Article
- Polymorphisms in Estrogen Synthesis Genes and Symptom Clusters During the Menopausal Transition and Early Postmenopause: Observations From the Seattle Midlife Women's Health Study.Biological research for nursing · 2018Article
- Advancing Symptom Science Through Symptom Cluster Research: Expert Panel Proceedings and Recommendations.Journal of the National Cancer Institute · 2017Review
- Symptom profiles and inflammatory markers in moderate to severe COPD.BMC pulmonary medicine · 2016Observational
- Distinct symptom experiences in subgroups of patients with COPD.International journal of chronic obstructive pulmonary disease · 2016Article
- Effect of symptoms on physical performance in COPD.Heart & lung : the journal of critical careObservational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
Abstract
AIMS AND
objectivesTo examine how subgroups of patients with chronic obstructive pulmonary disease, identified by ratings of symptoms (dyspnoea, anxiety, depression and fatigue), affect healthcare use and mortality.
backgroundPeople with chronic obstructive pulmonary disease often experience multiple symptoms. The importance of multiple symptoms and symptom clusters has received increased attention. However, little is known about symptom clusters and their effect on healthcare use and mortality in this population.
designDescriptive cross-sectional study.
methodsThis secondary data analysis used data from the National Emphysema Treatment Trial. Participants (n = 597) had severe chronic obstructive pulmonary disease. Descriptive and inferential statistics were used to analyse the data that were drawn from structured interviews, questionnaires and clinical measures.
resultsThree subgroup clusters emerged based on four symptom ratings. Mean age, proportion with higher education, proportion using oxygen, disease severity, exercise capacity and quality of life differed significantly between subgroups. Participants with high levels of symptoms used healthcare services more and were more likely to have died at the five-year follow-up than those with low levels of symptoms. Symptom cluster subgroups had more significant relationship with mortality than single symptoms.
conclusionPatients with high levels of symptoms require greater clinical attention. RELEVANCE TO CLINICAL PRACTICE: Understanding subgroups of patients, based on symptom ratings and their adverse effect on outcomes, may enable healthcare providers to assess multiple symptoms and identify subgroups of patients at risk of increased healthcare use and mortality. Targeting modifiable symptoms within the cluster may be more beneficial than focusing on a single symptom for certain health-related outcome.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.