CONTEXT: Patients with end-stage renal disease receiving dialysis experience multiple concurrent symptoms. A person-centered understanding of patients' symptom experiences may offer insights into individualized management. OBJECTIVES: We identified subgroups of patients based on their symptom experiences and the characteristics that differentiated among these subgroups. Outcomes associated with these subgroups were evaluated. METHODS: A total of 354 patients on dialysis were recruited at two regional hospitals in Hong Kong. While the Dialysis Symptom Index was adopted to assess symptoms, the Kidney Disease Quality of Life 36 and Karnofsky Performance Status Scale were used to evaluate the quality of life outcomes. Information on health care utilization and mortality were retrieved from medical records. Subgroups of patients were identified using latent class analysis based on the occurrence ratings. Differences in characteristics and outcomes were determined using Chi-squared test, analysis of variance, and Cox regression analysis. RESULTS: Three latent classes were identified: low (37.8%), moderate physical-low psychological (29.7%), and moderate physical-high psychological (32.5%). Higher comorbidity burden and lower serum albumin levels differentiated between the low and moderate physical-low psychological classes. The moderate physical-high psychological class had the highest number of symptoms, poorest quality of life outcomes, and more unscheduled clinic visits. A shorter mean survival time (421 vs. 431 days) was also found. CONCLUSION: Consistent with findings in other chronic conditions, subgroups of patients on dialysis have unique symptom experiences. Therefore, an individualized approach to symptom management is warranted. Our findings offer a phenotypic characterization for research on the underlying mechanisms for these symptom experiences.
CONTEXT: Patients with end-stage renal disease receiving dialysis experience multiple concurrent symptoms. A person-centered understanding of patients' symptom experiences may offer insights into individualized management. OBJECTIVES: We identified subgroups of patients based on their symptom experiences and the characteristics that differentiated among these subgroups. Outcomes associated with these subgroups were evaluated. METHODS: A total of 354 patients on dialysis were recruited at two regional hospitals in Hong Kong. While the Dialysis Symptom Index was adopted to assess symptoms, the Kidney Disease Quality of Life 36 and Karnofsky Performance Status Scale were used to evaluate the quality of life outcomes. Information on health care utilization and mortality were retrieved from medical records. Subgroups of patients were identified using latent class analysis based on the occurrence ratings. Differences in characteristics and outcomes were determined using Chi-squared test, analysis of variance, and Cox regression analysis. RESULTS: Three latent classes were identified: low (37.8%), moderate physical-low psychological (29.7%), and moderate physical-high psychological (32.5%). Higher comorbidity burden and lower serum albumin levels differentiated between the low and moderate physical-low psychological classes. The moderate physical-high psychological class had the highest number of symptoms, poorest quality of life outcomes, and more unscheduled clinic visits. A shorter mean survival time (421 vs. 431 days) was also found. CONCLUSION: Consistent with findings in other chronic conditions, subgroups of patients on dialysis have unique symptom experiences. Therefore, an individualized approach to symptom management is warranted. Our findings offer a phenotypic characterization for research on the underlying mechanisms for these symptom experiences.
Authors: Jieling Chen; Lingling Liu; Jing Chen; Marques S N Ng; Vivian W Q Lou; Bibo Wu; Weijie Jiang; Yanqing Jie; Jingfen Zhu; Yaping He Journal: Qual Life Res Date: 2021-05-11 Impact factor: 4.147
Authors: Marques Shek Nam Ng; Winnie Kwok Wei So; Kai Chow Choi; Wallace Chi Ho Chan; Helen Yue Lai Chan; Carmen Wing Han Chan Journal: BMJ Open Date: 2022-06-17 Impact factor: 3.006