Creatinine clearance in continuous peritoneal dialysis: dialysis dose required for a minimal acceptable level. 1996

A H Tzamaloukas, and G H Murata, and D Malhotra, and L Fox, and R S Goldman, and P S Avasthi
Medical Service, Veterans Affairs Medical Center. Albuquerque, New Mexico 87108 USA.

OBJECTIVE To identify the most advantageous formula for estimating creatinine clearance (CCr) and to establish a dose of dialysis that will ensure minimal acceptable levels of creatinine clearance in patients on continuous peritoneal dialysis (CPD). METHODS Analysis of all CCr studies performed in CPD patients over 40 months. METHODS All four dialysis units following CPD patients in one city. One dialysis unit is government-owned, one is university-affiliated, and two are community based. METHODS One hundred and ninety-four patients representing almost the entire CPD population in Albuquerque. METHODS Creatinine and urea clearance studies were performed in 24-hour urine and drained dialysate samples. Creatinine clearance (peritoneal plus urinary) was normalized to either 1.73 m2 body surface area (CCr) or body water estimated by the Watson formulas (KT/VCr). CCr and KT/VCr were either corrected by averaging urinary creatinine and urea clearances or were not corrected. Two dialysis units were designated as the training set (92 patients, 143 clearance studies) and the other two units as the validation set (102 patients, 181 clearance studies). METHODS Minimal acceptable creatinine clearance levels were determined in the training set by computing the creatinine clearance value corresponding to 1.70 weekly KT/V urea by linear regression. Logistic regression models predicting low creatinine clearance were developed in the training set and were tested in the validation set. RESULTS The following weekly creatinine clearance values corresponded to 1.70 KT/V urea: corrected CCr 52.0 L/1.73 m2, uncorrected CCr 54.4 L/1.73 m2, corrected KT/VCr 1.46, uncorrected KT/VCr 1.53. Logistic regression identified as predictors of low creatinine clearance low daily urine volume (UV) and low daily dialysate drain volume/body water (DV/V) for all four creatinine clearance formulas, plus low/low-average peritoneal solute transport (only for uncorrected CCr) and serum creatinine (for both KT/VCr formulas). In the validation set, the predictive models produced an area under the receiver operating characteristic (ROC) curve between 0.835 and 0.919 indicating very good predictive accuracy. For corrected CCr and anuria, the regression model produced a minimal normalized drain volume (DV/V) value consistent with minimal acceptable CCr equal to 0.305 L/L per 24 hours. This DV/V cutoff detected low corrected CCR in validation set anuric subjects (n = 55) with a sensitivity of 85% and a specificity of 71%. For uncorrected CCR and anuria, DV/V cutoffs were 0.273 L/L per 24 hours (high/high-average peritoneal solute transport) and 0.420 L/L per 24 hours (low/low-average transport). Sensitivity and specificity of these cutoffs in validation set anuric subjects were 87% and 85%, plus 86% and 33%, respectively. CONCLUSIONS The uncorrected CCr appears to be the most advantageous creatinine clearance formula in CPD, because it allows the use of peritoneal solute transport type in the calculation of the minimal required normalized drain volume. The minimal acceptable uncorrected CCr is 54.4 L/1.73 m2 weekly. To achieve this uncorrected CCr in anuria, the required minimal normalized drain volume is 0.273 L per liter of body water daily if peritoneal solute transport is high or high-average and around 0.420 L per liter of body water daily if peritoneal solute transport is low or low-average. The required total daily drain volume is computed by multiplying the required normalized drain volume by body water.

UI MeSH Term Description Entries
D007684 Kidney Tubules Long convoluted tubules in the nephrons. They collect filtrate from blood passing through the KIDNEY GLOMERULUS and process this filtrate into URINE. Each renal tubule consists of a BOWMAN CAPSULE; PROXIMAL KIDNEY TUBULE; LOOP OF HENLE; DISTAL KIDNEY TUBULE; and KIDNEY COLLECTING DUCT leading to the central cavity of the kidney (KIDNEY PELVIS) that connects to the URETER. Kidney Tubule,Tubule, Kidney,Tubules, Kidney
D008297 Male Males
D010531 Peritoneal Dialysis, Continuous Ambulatory Portable peritoneal dialysis using the continuous (24 hours a day, 7 days a week) presence of peritoneal dialysis solution in the peritoneal cavity except for periods of drainage and instillation of fresh solution. CAPD,Continuous Ambulatory Peritoneal Dialysis
D003404 Creatinine Creatinine Sulfate Salt,Krebiozen,Salt, Creatinine Sulfate,Sulfate Salt, Creatinine
D005260 Female Females
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D001692 Biological Transport The movement of materials (including biochemical substances and drugs) through a biological system at the cellular level. The transport can be across cell membranes and epithelial layers. It also can occur within intracellular compartments and extracellular compartments. Transport, Biological,Biologic Transport,Transport, Biologic
D012372 ROC Curve A graphic means for assessing the ability of a screening test to discriminate between healthy and diseased persons; may also be used in other studies, e.g., distinguishing stimuli responses as to a faint stimuli or nonstimuli. ROC Analysis,Receiver Operating Characteristic,Analysis, ROC,Analyses, ROC,Characteristic, Receiver Operating,Characteristics, Receiver Operating,Curve, ROC,Curves, ROC,ROC Analyses,ROC Curves,Receiver Operating Characteristics
D014508 Urea A compound formed in the liver from ammonia produced by the deamination of amino acids. It is the principal end product of protein catabolism and constitutes about one half of the total urinary solids. Basodexan,Carbamide,Carmol
D015233 Models, Statistical Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc. Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model

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