ArticleNursing research
Physical Symptom Cluster Subgroups in Chronic Kidney Disease.
Article in Nursing research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06257134 (Impact on Quality of Life of Symptoms Routine E-monitoring Among Dialysis Patients, With Results Notification to Teams. A Cluster Randomised Controlled Trial Nested in a National Registry F-SWIFT), which is not on this map. Cited by 11 papers.
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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.
Impact on Quality of Life of Symptoms Routine E-monitoring Among Dialysis Patients, With Results Notification to Teams. A Cluster Randomised Controlled Trial Nested in a National Registry F-SWIFT (French Symptom Monitoring WIth Feedback Trial)
Who cites it
11 citing papers in PubMed.
- A latent profile analysis of cancer-related fatigue in patients with breast cancer undergoing chemotherapy and its relationship with quality of life: a cross-sectional study.Frontiers in public health · 2026Article
- Clinical validation of ICNP® Terminological Subset for people with chronic kidney disease undergoing hemodialysis.Revista da Escola de Enfermagem da U S P · 2026Article
- Furosemide and the Symptom Burden: The Potential Mediating Role of Uremic Toxins in Patients with CKD.Toxins · 2025Article
- Article
- Optimizing Nursing Communication for Symptom Management in Hemodialysis: Development of an Artificial Intelligence-Based Web Predictive Model for Burden Classification and Evidence Navigation.Journal of nursing management · 2025Article
- Symptom profiles in patients receiving maintenance hemodialysis and their association with quality of life: a longitudinal study.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024Article
- The Heterogeneity of Symptom Burden and Fear of Progression Among Kidney Transplant Recipients: A Latent Class Analysis.Psychology research and behavior management · 2024Article
- Factors associated with subgroups of fatigue in maintenance hemodialysis patients: a cross-sectional study.Renal failure · 2023Article
- Five-Year Symptom Trajectories in Nondialysis-Dependent CKD Patients.Clinical journal of the American Society of Nephrology : CJASN · 2022Article
- Patient-centred approaches for the management of unpleasant symptoms in kidney disease.Nature reviews. Nephrology · 2022Review
- Obstacles to Early Diagnosis and Treatment of Pruritus in Patients with Chronic Kidney Disease: Current Perspectives.International journal of nephrology and renovascular disease · 2022Review
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
backgroundSymptom burden associated with chronic kidney disease can be debilitating, with a negative effect on patient health-related quality of life. Latent class clustering analysis is an innovative tool for classifying patient symptom experience.
objectivesThe aim of the study was to identify subgroups of patients at greatest risk for high symptom burden, which may facilitate development of patient-centered symptom management interventions.
methodsIn this cross-sectional analysis, baseline data were analyzed from 3,921 adults enrolled in the Chronic Renal Insufficiency Cohort Study from 2003 to 2008. Latent class cluster modeling using 11 items on the Kidney Disease Quality of Life symptom profile was employed to identify patient subgroups based on similar observed physical symptom response patterns. Multinomial logistic regression models were estimated with demographic variables, lifestyle and clinical variables, and self-reported measures (Kidney Disease Quality of Life physical and mental component summaries and the Beck Depression Inventory).
resultsThree symptom-based subgroups were identified, differing in severity (low symptom, moderate symptom, and high symptom). After adjusting for other variables in multinomial logistic regression, membership in the high-symptom subgroup was less likely for non-Hispanic Blacks and men. Other factors associated with membership in the high-symptom subgroup included lower estimated glomerular filtration rate, history of cardiac/cardiovascular disease, higher Beck Depression Inventory scores, and lower Kidney Disease Quality of Life physical and mental component summaries. DISCUSSION: Three symptom subgroups of patients were identified among patients with mild-to-moderate chronic kidney disease. Several demographic and clinical variables predicted membership in subgroups. Further research is needed to determine if symptom subgroups are stable over time and can be used to predict healthcare utilization and clinical outcomes.
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