BACKGROUND: Quality of life (QoL) in end-stage renal disease patients has become an important focus of attention in evaluating dialysis. We studied risk factors of poor QoL at 1 year follow-up. METHODS: Of a baseline sample of 80 dialysis patients, we contacted 60 patients who were alive at 1 year follow-up. QoL data were obtained for 46 (76.7%) of these patients. QoL measured with the SF-36 [physical health component score (PCS) and mental health component score (MCS)] at 1 year-follow-up was predicted by means of multivariate regression analysis by data collected at baseline using INTERMED-an observer-rated method to assess biopsychosocial care needs-and several indicators for disease severity and comorbidity. RESULTS: The regression models explained 32% of the variance in PCS and 40% in MCS. INTERMED score (P < 0.01) was the only independent risk factor for low MCS, while for low PCS, diabetic comorbidity (P = 0.02) and age (P = 0.03) were independent risk factors. A simple risk score consisting of INTERMED > or =21, diabetic comorbidity and age > or =65 was significantly correlated with non-survival (P = 0.02) and with PCS (P < 0.01) and MCS (P < 0.01) in surviving patients, although not with hospital admissions during follow-up. CONCLUSIONS: A simple risk score based on INTERMED, age (> or =65) and comorbid diabetes (yes/no) can be used to detect patients at risk of poor QoL and non-survival at an early stage of treatment.
BACKGROUND: Quality of life (QoL) in end-stage renal diseasepatients has become an important focus of attention in evaluating dialysis. We studied risk factors of poor QoL at 1 year follow-up. METHODS: Of a baseline sample of 80 dialysis patients, we contacted 60 patients who were alive at 1 year follow-up. QoL data were obtained for 46 (76.7%) of these patients. QoL measured with the SF-36 [physical health component score (PCS) and mental health component score (MCS)] at 1 year-follow-up was predicted by means of multivariate regression analysis by data collected at baseline using INTERMED-an observer-rated method to assess biopsychosocial care needs-and several indicators for disease severity and comorbidity. RESULTS: The regression models explained 32% of the variance in PCS and 40% in MCS. INTERMED score (P < 0.01) was the only independent risk factor for low MCS, while for low PCS, diabetic comorbidity (P = 0.02) and age (P = 0.03) were independent risk factors. A simple risk score consisting of INTERMED > or =21, diabetic comorbidity and age > or =65 was significantly correlated with non-survival (P = 0.02) and with PCS (P < 0.01) and MCS (P < 0.01) in surviving patients, although not with hospital admissions during follow-up. CONCLUSIONS: A simple risk score based on INTERMED, age (> or =65) and comorbid diabetes (yes/no) can be used to detect patients at risk of poor QoL and non-survival at an early stage of treatment.
Authors: Camila Almeida de Oliveira; Bernardete Weber; Jair Lício Ferreira Dos Santos; Miriane Lucindo Zucoloto; Lisa Laredo de Camargo; Ana Carolina Guidorizzi Zanetti; Magdalena Rzewuska; João Mazzoncini de Azevedo-Marques Journal: PLoS One Date: 2022-02-18 Impact factor: 3.240
Authors: Eric Y F Wan; Julie Y Chen; Edmond P H Choi; Carlos K H Wong; Anca K C Chan; Karina H Y Chan; Cindy L K Lam Journal: Health Qual Life Outcomes Date: 2015-07-29 Impact factor: 3.186