Predictors of quality of life in patients with end-stage renal disease on hemodialysis

• Main Authors: Saad MM, El Douaihy Y, Boumitri C, Rondla C, Moussaly E, Daoud M, El Sayegh SE
• Format: Article
• Language: English
• Published: Dove Medical Press 2015-09-01
• Series: International Journal of Nephrology and Renovascular Disease
• Online Access: https://www.dovepress.com/predictors-of-quality-of-life-in-patients-with-end-stage-renal-disease-peer-reviewed-article-IJNRD

Marc M Saad,1 Youssef El Douaihy,1 Christine Boumitri,1 Chetana Rondla,2 Elias Moussaly,1 Magda Daoud,1 Suzanne E El Sayegh3 1Internal Medicine, Staten Island University Hospital, Staten Island, NY, 2Nephrology, Emory University Hospital, Atlanta, GA, 3Nephrology, Staten Island University Hospital, Staten Island, NY, USA Background: Assessment of quality of life (QOL) of end-stage renal disease (ESRD) patients (physical, mental, and social well-being) has become an essential tool to develop better plans of care. Objective of this study is to determine which demographic and biochemical parameters correlate with the QOL scores in patients with ESRD on hemodialysis (HD) using Kidney Disease QOL-36 surveys (KDQOL). Methods: A retrospective chart review of all ESRD patients who underwent HD at an outpatient center. The five components of the KDQOL were the primary end points of this study (burden of kidney disease, symptoms and problems, effects of kidney disease on daily life, mental component survey, and physical component survey). Scores were grouped into three categories (below average, average, and above average). In addition to demographics (age, sex, and race), the independent variables such as weight gain, number of years on dialysis, urea reduction ratio, calcium, phosphorus, parathyroid hormone, albumin, and hemoglobin in the serum were collected. Chi-square analysis for dependent variables and the nominal independent variables was used, and analysis of variance analysis was used for continuous independent variables. Ordinal regression using PLUM (polytomous universal model) method was used to weigh out possible effects of confounders. Results: The cohort size was 111 patients. Mean age was 61.8 (±15.5) years; there were more males than females (64.9% vs 35.1%), the mean time-on-dialysis at the time of the study was 4.3 (4.8) years. Approximately two-thirds of the responses on all five domains of the questionnaire ranked average when compared to the national numbers. The remainders were split between above average (20.6%) and below average (13.4%). In our cohort, no relationships were statistically significant between the five dependent variables of interest and the independent variables by chi-square- and t-test analyses. This was further confirmed by regression analysis. Of note, sex carried the strongest statistical significance (with a P-value of 0.16) as a predictor of “the burden of kidney disease on daily life” in ordinal regression. Conclusion: Prior studies have shown variables such as serum phosphate level, intradialytic weight gain, and dialysis adequacy are associated with lower KDQOL scores; however, this was not evident in our analysis likely due to smaller sample size. Larger size studies are required to better understand the predictors of QOL in ESRD patients on HD. Keywords: quality of life, end-stage renal disease, hemodialysis, metabolic profile