BACKGROUND: To date, the pathophysiology underlying symptoms in renal patients is still unclear. Symptom management research suggests that identification of related clusters of symptoms could provide insight into underlying determinants associated with multiple symptom experience. Theoretically, symptoms within a cluster could have a synergistic relationship. We aimed to identify symptom clusters in incident dialysis patients, and investigated associations between symptom clusters, clinical variables, functional status as measured by the Karnofsky Index and quality of life. METHODS: 1553 haemodialysis (HD) and peritoneal dialysis (PD) patients completed the Kidney Disease Quality of Life Short Form symptom/problem list at 3 months after the start of dialysis. Principal component analysis using varimax rotation was used to identify symptom clusters. RESULTS: Patients were bothered by an average of 2.8 (+/-2.4) symptoms of 'moderate bother' or more. Three clusters were identified, explaining 49% of the total variance. All clusters showed strong negative associations with the SF-36 quality of life dimensions (-0.142 to -0.593) and with functional status (-0.130 to -0.332) in HD and PD patients. In contrast, only the clinical variables serum albumin (-0.084 to -0.232) and haemoglobin (-0.068 to -0.126) were associated with all clusters in HD patients, and Kt/V(urea) (-0.089 to -0.125) in PD patients. CONCLUSIONS: Symptom clustering does not explain the lack of meaningful associations between symptoms and clinical variables. Strong associations of symptom clusters with quality of life dimensions suggest that psychological factors could better explain symptom burden. Patients' perceptions of symptoms should be routinely assessed as part of clinical care to improve self-management strategies.
BACKGROUND: To date, the pathophysiology underlying symptoms in renalpatients is still unclear. Symptom management research suggests that identification of related clusters of symptoms could provide insight into underlying determinants associated with multiple symptom experience. Theoretically, symptoms within a cluster could have a synergistic relationship. We aimed to identify symptom clusters in incident dialysis patients, and investigated associations between symptom clusters, clinical variables, functional status as measured by the Karnofsky Index and quality of life. METHODS: 1553 haemodialysis (HD) and peritoneal dialysis (PD) patients completed the Kidney Disease Quality of Life Short Form symptom/problem list at 3 months after the start of dialysis. Principal component analysis using varimax rotation was used to identify symptom clusters. RESULTS:Patients were bothered by an average of 2.8 (+/-2.4) symptoms of 'moderate bother' or more. Three clusters were identified, explaining 49% of the total variance. All clusters showed strong negative associations with the SF-36 quality of life dimensions (-0.142 to -0.593) and with functional status (-0.130 to -0.332) in HD and PDpatients. In contrast, only the clinical variables serum albumin (-0.084 to -0.232) and haemoglobin (-0.068 to -0.126) were associated with all clusters in HDpatients, and Kt/V(urea) (-0.089 to -0.125) in PDpatients. CONCLUSIONS: Symptom clustering does not explain the lack of meaningful associations between symptoms and clinical variables. Strong associations of symptom clusters with quality of life dimensions suggest that psychological factors could better explain symptom burden. Patients' perceptions of symptoms should be routinely assessed as part of clinical care to improve self-management strategies.
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