Journal of the American Society of Nephrology
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Journal of the American Society of Nephrology, Vol 7, 780-785, Copyright © 1996 by American Society of Nephrology


REGULAR ARTICLES

Equations for normalized protein catabolic rate based on two-point modeling of hemodialysis urea kinetics

TA Depner and JT Daugirdas
Department of Medicine, University of California at Davis, Sacramento 95817, USA.

The normalized protein catabolic rate (PCRn) can be calculated from predialysis and postdialysis BUN measurements in patients receiving intermittent dialysis. This measure of net protein catabolism, adjusted for body size, is a useful clinical measure of nutrition that correlates with patient outcome and, in patients who are in nitrogen balance, is a reasonable estimate of dietary protein intake. Whereas simplified formulae that estimate the per-treatment dose of hemodialysis, expressed as Kt/Vurea (Kt/V), are in common use, simplified methods for determining PCRn have only recently appeared. In the study presented here, equations were derived for calculating PCRn from the predialysis BUN and Kt/V. The equations were of the general form: PCRn = C0/(a + bKt/V + c/(Kt/NLL)) + 0.168, where Co is the predialysis BUN in mg/dL. Three sets of coefficients were developed for patients dialyzed thrice weekly: one for patients dialyzed after the long interval at the beginning of the week, one for patients dialyzed at midweek, and the third for patients dialyzed at the end of the week. Two similar sets of coefficients were developed for patients dialyzed twice weekly. For patients with remaining function in the native kidney remnant, equations were developed and refined for upgrading PCRn by adjusting C0 upward. The equations were validated by comparing the calculated PCRn with PCRn determined by a formal iterative model of urea kinetics in a series of 119 dialyses in 51 patients dialyzed thrice weekly (r = 0.9952; mean absolute error, 1.97 +/- 1.39%) and in a series of 71 dialyses in 25 patients dialyzed twice weekly (r = 0.9956; mean absolute error, 2.17 +/- 1.56%). These simple yet accurate equations should be useful in epidemiologic studies or in clinical laboratories where limited data are available for each patient or when iterative computer techniques cannot be applied.


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