Abstract: SA-PO890
Identification of Symptom Clusters and Their Association with Clinical Characteristics and Quality of Life Outcomes in CKD: A Multicenter Study
Session Information
- CKD: Pharmacoepidemiology
November 09, 2019 | Location: Exhibit Hall, Walter E. Washington Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: CKD (Non-Dialysis)
- 2101 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention
Authors
- Wilkinson, Thomas James, University of Leicester, Leicester, United Kingdom
- Nixon, Daniel, University of Leicester, Leicester, United Kingdom
- Smith, Alice C., University of Leicester, Leicester, United Kingdom
Group or Team Name
- Leicester Kidney Lifestyle Team
Background
Renal patients suffer from an overwhelming symptom burden including fatigue, dyspnea, sleep problems and depression. Research into symptom clusters (co-occurrence of symptoms) is emerging although primarily limited to end stage renal disease. Whilst individual symptoms are established contributors to poor quality of life (QoL), no research has investigated the role of symptom clusters on these outcomes.
Methods
Self-reported symptoms of 876 CKD pre-dialysis patients (44% females, age 67±16 years, eGFR 40±25ml/min) were assessed using the Kidney Symptom Questionnaire. Clusters were derived based on the frequency of the 13 symptoms using Principle Component Analysis (minimum factor loading 0.4, KMO=.925). Associations between clusters, QoL (EQ5D), and physical function (Duke Activity Status Index) was analysed using generalized regression modeling (age and sex used as co-variants).
Results
Symptom clusters based are shown in Figure 1.
Cluster 1-type patients were older (β=.297, P<.001) whilst cluster 2 patients were younger (β=-.211, P<.001). Sex had no effect on symptom clustering. Symptom cluster 1 was the greatest predictor of reduced QoL (using the EQ5D index; β=-.465, P<.001) and physical function (β=-.407, P<.001). Cluster 3 was least predictive of poor QoL (β=-.108, P=.044) and cluster 4 least predictive of physical function (β=-.079, P=.015), although both significant.
Worsening of eGFR was associated with cluster 2 symptoms only (β=-.142, P=.001). Higher inflammation (CRP) was associated with cluster 1 symptoms (β=.181, P=.040).
Conclusion
We identified 4 unique symptom clusters in patients with non-dialysis dependent CKD. QoL was primarily affected by physiological symptoms relating to muscle and joint pain, dynapenia and dyspnea. Routine clinical assessment and management strategies targeted at cluster level could have synergistic effects in reducing the burden of CKD symptoms.
Funding
- Private Foundation Support