Bedside Linear Regression Equations to Estimate Equilibrated Urea

FERNANDEZ E.; BALZARINI M.; VALTUILLE R.

Technical Problems in Patients on Hemodialysis

InTech

Año: 2011; p. 1 - 16

Three decades ago Sargent and Gotch established the clinical applicability of Kt/V, a dimensionless ratio which includes clearance of dialyzer (K),duration of treatment(t) and volume of total water of the patient (V), as an index of Hemodialysis (HD) adequacy (Gotch & Keen, 2005). This parameter, derived from single-pool(sp) urea(U) kinetic modelling, has become the gold standard for HD dose monitoring and it is widely used as a predictor of outcome in HD populations (Locatelli et al., 1999; Eknoyan et al., 2002; Locatelli, 2003). However, this spKt/V overestimates the HD dose because it does not take into account the concept of U rebound (UR). UR begins immediately at the end of HD session and it is completed 30-60 minutes after. UR is related to disequilibriums in blood/cell compartments as well as the flow between organs desequilibriums, both produced during HD treatment. Therefore, equilibrated (Eq) Kt/V is the true HD dose and it requires the measurement of a true eqU when UR is completed. A blood sample to obtain an eqU concentration has several drawbacks that make this option impractical (Gotch and Keen,2005). For this reason in the last decade several formulas were developed to predict the eqU and also (Eq) Kt/V eliminating the need of waiting for a equilibrated urea mesurement. For instance, the “rate formula” (Daurgidas et al., 1995) is the most popular and validated equation. It is based in the prediction of (Eq)Kt/V as a linear function of (sp)Kt/V and the rate of dialysis(K/V). Another approach has been proposed by Tattersall, a robust formula based on double–pool analysis (Smye et al.1999). However, spite this eqU prediction approach is conceptually rigorous, it is not accurate (Gotch, 1990; Guh et al., 1999; Fernandez et al., 2001). Consequently, the availability of a model to predict subject-specific equilibrated concentration will be very helpful. Although the behaviour of urea is non-linear since its extraction from blood follows some exponential family model as a function of time, we found that prediction of its equilibrated concentration after the end of the treatment session by means of linear models is accurate. In this study, we have shown how to build linear models to predict equilibrated urea based on two statistical procedures and a machine learning method that can be implemented in hemodialysis centres.