2008
DOI: 10.2215/cjn.00820208
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Biomarkers and Health-Related Quality of Life in End-Stage Renal Disease

Abstract: Background and objectives: Health-related quality of life (HRQOL) predicts mortality in ESRD, yet adoption of HRQOL monitoring is not widespread, and regulatory authorities remain predominantly concerned with monitoring traditional biologic parameters. To assist with future efforts to adopt HRQOL monitoring while acknowledging the importance of biomarkers, this study sought to establish which domains of HRQOL are most affected by ESRD and to measure the strength of evidence linking common biomarkers to HRQOL i… Show more

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Cited by 112 publications
(102 citation statements)
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“…Spiegel et al [15] documented highly significant independent correlations between dry weight and both PCS and MCS scores of the SF-36, similar to results of our study. Also, Kalantar-Zadeh et al [16] documented highly significant independent correlations between BMI and both PCS and MCS scores of the SF-36, which was in agreement with our study.…”
Section: Discussionsupporting
confidence: 92%
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“…Spiegel et al [15] documented highly significant independent correlations between dry weight and both PCS and MCS scores of the SF-36, similar to results of our study. Also, Kalantar-Zadeh et al [16] documented highly significant independent correlations between BMI and both PCS and MCS scores of the SF-36, which was in agreement with our study.…”
Section: Discussionsupporting
confidence: 92%
“…In our study, there was no significant relation between dialysis adequacy, as measured by Kt/V and QOL. Our findings were similar to the findings of Fabrizi et al [8] and Spiegel et al [15]. In contrast, Asfar et al [4] found that Kt/V was only correlated with the mental health subscale.…”
Section: Discussionsupporting
confidence: 92%
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“…Multiple confounding factors previously reported to be associated with mental health and outcomes in the general population and dialysis patients were considered as covariates (27)(28)(29). Demographic and clinical factors included in the analysis were age, sex, race, education, marital status, history of cardiovascular disease (CVD), history of coronary artery disease (CAD), body mass index, blood pressure, smoking status, comorbidities (including ICED scores and diabetic status), dialysis vintage, treatment arms, sleep quality, and medication use.…”
Section: Covariate Selectionmentioning
confidence: 99%
“…In addition, patients on hemodialysis, with little prospect of no longer requiring treatment, increase the cost of health systems, and their quality of life markedly reduces. Thus, it is becoming increasingly necessary to organize and facilitate patient access to services 13,14,15,16 .…”
Section: Introductionmentioning
confidence: 99%