title: Estimating residual kidney function in dialysis patients without urine collection.
abstract: Residual kidney function contributes substantially to solute clearance in dialysis patients but cannot be assessed without urine collection. We used serum filtration markers to develop dialysis-specific equations to estimate urinary urea clearance without the need for urine collection. In our development cohort, we measured 24-hour urine clearances under close supervision in 44 patients and validated these equations in 826 patients from the Netherlands Cooperative Study on the Adequacy of Dialysis. For the development and validation cohorts, median urinary urea clearance was 2.6 and 2.4 ml/min, respectively. During the 24-hour visit in the development cohort, serum β-trace protein concentrations remained in steady state but concentrations of all other markers increased. In the validation cohort, bias (median measured minus estimated clearance) was low for all equations. Precision was significantly better for β-trace protein and β2-microglobulin equations and the accuracy was significantly greater for β-trace protein, β2-microglobulin, and cystatin C equations, compared with the urea plus creatinine equation. Area under the receiver operator characteristic curve for detecting measured urinary urea clearance by equation-estimated urinary urea clearance (both 2 ml/min or more) were 0.821, 0.850, and 0.796 for β-trace protein, β2-microglobulin, and cystatin C equations, respectively; significantly greater than the 0.663 for the urea plus creatinine equation. Thus, residual renal function can be estimated in dialysis patients without urine collections.
authors.affiliation: Division of Nephrology, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA; Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland, USA. Electronic address: tshafi@jhmi.edu.
authors.forename: Tariq
authors.initials: T
authors.lastname: Shafi
authors.affiliation: Division of Nephrology, Department of Medicine, Academic Medical Center, Amsterdam, the Netherlands.
authors.forename: Wieneke M
authors.initials: WM
authors.lastname: Michels
authors.affiliation: Division of Nephrology, Department of Medicine, Tufts Medical Center, Boston, Massachusetts, USA.
authors.forename: Andrew S
authors.initials: AS
authors.lastname: Levey
authors.affiliation: Division of Nephrology, Department of Medicine, Tufts Medical Center, Boston, Massachusetts, USA.
authors.forename: Lesley A
authors.initials: LA
authors.lastname: Inker
authors.affiliation: Department of Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
authors.forename: Friedo W
authors.initials: FW
authors.lastname: Dekker
authors.affiliation: Division of Nephrology, Department of Medicine, Academic Medical Center, Amsterdam, the Netherlands.
authors.forename: Raymond T
authors.initials: RT
authors.lastname: Krediet
authors.affiliation: Department of Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
authors.forename: Tiny
authors.initials: T
authors.lastname: Hoekstra
authors.affiliation: Division of Nephrology, Department of Pediatrics, University of Rochester, Rochester, New York, USA.
authors.forename: George J
authors.initials: GJ
authors.lastname: Schwartz
authors.affiliation: Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, USA.
authors.forename: John H
authors.initials: JH
authors.lastname: Eckfeldt
authors.affiliation: Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland, USA; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA; Departments of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA; Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
authors.forename: Josef
authors.initials: J
authors.lastname: Coresh
mesh_terms: D000328:Adult; D000368:Aged; D019540:Area Under Curve; D015142:Baltimore; D015415:Biomarkers / Q000097:blood* / Q000652:urine; D003404:Creatinine / Q000097:blood; D003430:Cross-Sectional Studies; D055316:Cystatin C / Q000097:blood; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D019746:Intramolecular Oxidoreductases / Q000097:blood; D007668:Kidney / Q000503:physiopathology*; D007674:Kidney Diseases / Q000097:blood / Q000175:diagnosis / Q000503:physiopathology / Q000628:therapy*; D054834:Lipocalins / Q000097:blood; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D009426:Netherlands; D010530:Peritoneal Dialysis; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012372:ROC Curve; D006435:Renal Dialysis; D015203:Reproducibility of Results; D014508:Urea / Q000097:blood / Q000652:urine; D001613:beta 2-Microglobulin / Q000097:blood
chemical_list: D015415:Biomarkers; C525030:CST3 protein, human; D055316:Cystatin C; D054834:Lipocalins; D001613:beta 2-Microglobulin; D014508:Urea; D003404:Creatinine; D019746:Intramolecular Oxidoreductases; C022466:prostaglandin R2 D-isomerase
keywords: hemodialysis; peritoneal dialysis; residual kidney function