Relationship between symptom clusters and quality of life in patients at stages 2 to 4 chronic kidney disease in Korea

Lee, Suk Jeong; Jeon, Jaehee

doi:10.1016/j.apnr.2015.03.004

Cited by 25 publications

(82 citation statements)

References 19 publications

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“…Some data are available on symptom clusters in patients with HIV disease (10,11), chronic kidney failure and endstage renal disease (15,16), COPD (12,13), osteoarthritis (45), rheumatoid arthritis (46), and heart failure (14). Similar to studies in oncology, the occurrence of symptom clusters in these chronic conditions is associated with decrements in functional status and QOL, as well as increased health care utilization and mortality.…”

Section: Transferability To Other Chronic Conditionsmentioning

confidence: 84%

“…While the psychiatric literature provides excellent examples of the use of hierarchical cluster analysis to define subgroups of patients within a diagnostic subgroup (for examples, see 5-7) or as diagnostic criteria (for examples, see 8,9), the majority of the research on symptom clusters in patients with chronic conditions was conducted with oncology patients. However, an emerging body of evidence suggests that symptom clusters occur in patients with a variety of chronic conditions (eg, HIV disease [10,11], chronic obstructive pulmonary disease [COPD] [12,13], heart disease [14], end-stage renal disease [ESRD] [15,16]). Nonetheless, research on symptom clusters is extremely limited.…”

mentioning

confidence: 99%

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Advancing Symptom Science Through Symptom Cluster Research: Expert Panel Proceedings and Recommendations

Miaskowski

Barsevick

Berger

et al. 2017

JNCI J Natl Cancer Inst

306

330

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An overview of proceedings, findings, and recommendations from the workshop on "Advancing Symptom Science Through Symptom Cluster Research" sponsored by the National Institute of Nursing Research (NINR) and the Office of Rare Diseases Research, National Center for Advancing Translational Sciences, is presented. This workshop engaged an expert panel in an evidenced-based discussion regarding the state of the science of symptom clusters in chronic conditions including cancer and other rare diseases. An interdisciplinary working group from the extramural research community representing nursing, medicine, oncology, psychology, and bioinformatics was convened at the National Institutes of Health. Based on expertise, members were divided into teams to address key areas: defining characteristics of symptom clusters, priority symptom clusters and underlying mechanisms, measurement issues, targeted interventions, and new analytic strategies. For each area, the evidence was synthesized, limitations and gaps identified, and recommendations for future research delineated. The majority of findings in each area were from studies of oncology patients. However, increasing evidence suggests that symptom clusters occur in patients with other chronic conditions (eg, pulmonary, cardiac, and end-stage renal disease). Nonetheless, symptom cluster research is extremely limited and scientists are just beginning to understand how to investigate symptom clusters by developing frameworks and new methods and approaches. With a focus on personalized care, an understanding of individual susceptibility to symptoms and whether a "driving" symptom exists that triggers other symptoms in the cluster is needed. Also, research aimed at identifying the mechanisms that underlie symptom clusters is essential to developing targeted interventions.Patients with chronic conditions, such as cancer and other rare diseases, experience an array of multiple co-occurring symptoms (eg, pain, fatigue, sleep disturbance). When these symptoms remain underdiagnosed and undertreated, they have a negative impact on patient-reported outcomes (PROs) including functional performance, cognitive status, and quality of life (QOL). A reduction in symptom burden in these patients has the potential to improve their capacity to live well over their entire lives. To achieve this goal, a transformation is needed in how multiple co-occurring symptoms are assessed and managed in order to improve patient outcomes and stimulate a reduction in health care utilization and costs. A strategic plan that advances REVIEW

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Section: Transferability To Other Chronic Conditionsmentioning

confidence: 84%

mentioning

confidence: 99%

Advancing Symptom Science Through Symptom Cluster Research: Expert Panel Proceedings and Recommendations

Miaskowski

Barsevick

Berger

et al. 2017

JNCI J Natl Cancer Inst

306

330

View full text Add to dashboard Cite

show abstract

“…, Amro et al . , , Lee & Jeon ), although most of these studies occur in the final stage of CKD (i.e. end stage kidney disease).…”

Section: Introductionmentioning

confidence: 99%

“…). One recent study assessed 17 symptoms using the Patient Outcome Scale in 143 people with CKD stages 2‐4, finding five symptom clusters (energy insufficiency and pain, skin problems, emotional instability and uraemia, circulatory problems and anaemia, neurological and bowel problems) (Lee & Jeon ).…”

Section: Introductionmentioning

confidence: 99%

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Multidimensional symptom clusters: an exploratory factor analysis in advanced chronic kidney disease

Almutary

Douglas

Bonner

2016

Journal of Advanced Nursing

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Adopting a symptom cluster approach has the potential to significantly advance symptom assessment and nursing care for people in advanced stages of chronic kidney disease. Routine clinical assessment and management strategies targeted at the cluster level should have synergistic effects in reducing symptoms. Fatigue is a pervasive symptom in advanced chronic kidney disease that is interconnected with global symptom burden, suggesting better management of symptom clusters may also reduce fatigue.

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Comparison of Fatigue, Pain, and Depression in Patients With Advanced Kidney Disease and Cancer—Symptom Burden and Clusters

Jhamb

Abdel-Kader

Yabes

et al. 2019

Journal of Pain and Symptom Management

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Context. Although symptom clusters have been studied in the context of cancer, few data exist in chronic and end-stage kidney disease (CKD/ESKD) patients. Objectives. The objectives of this study were to 1) characterize and compare symptom cluster phenotypes in patients with advanced CKD, ESKD, and cancer and 2) explore predictors of symptom clusters. Methods. We conducted secondary data analysis of three prospective studies in which pain, depression, and fatigue were assessed in patients with Stage 4e5 CKD, ESKD, and gastrointestinal cancer. Tetrachoric correlations between these symptoms were quantified, and partitioning around medoids algorithm was used for symptom cluster analysis. Results. In the 82 CKD, 149 ESKD, and 606 cancer patients, no differences in the average fatigue (P ¼ 0.17) or pain levels (P ¼ 0.21) were observed. Over 80% of patients in each group had at least one symptom. Moderate or severe depressive symptoms were more common in patients with cancer (31% vs. 19% in ESKD vs. 9% in CKD; P < 0.001). Mild-moderate correlations were observed between the three symptoms in ESKD and cancer patients. Three distinct clusters were observed in each group. In ESKD, the HIGH cluster (with high probability of pain, depression, and fatigue) had higher body mass index (P < 0.001) and antidepressant use (P ¼ 0.01). In cancer patients, the HIGH cluster patients were more likely to be female (P ¼ 0.04), use antidepressants (P ¼ 0.04), and have lower serum albumin (P < 0.001) and hemoglobin (P ¼ 0.03) compared to the other two clusters. Conclusion. Although the burden of fatigue, pain, and depressive symptoms for CKD and ESKD patients is similar to patients with gastrointestinal cancer, symptom cluster phenotypes differed between the groups as did the predictors of symptom clusters.

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Relationship between symptom clusters and quality of life in patients at stages 2 to 4 chronic kidney disease in Korea

Cited by 25 publications

References 19 publications

Advancing Symptom Science Through Symptom Cluster Research: Expert Panel Proceedings and Recommendations

Advancing Symptom Science Through Symptom Cluster Research: Expert Panel Proceedings and Recommendations

Multidimensional symptom clusters: an exploratory factor analysis in advanced chronic kidney disease

Comparison of Fatigue, Pain, and Depression in Patients With Advanced Kidney Disease and Cancer—Symptom Burden and Clusters

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