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Dialysate-side urea kinetics. Neural network predicts dialysis dose during dialysis

  • E. A. Fernández
  • R. Valtuille
  • P. Willshaw
  • C. A. Perazzo
Article

Abstract

Determination of the adequacy of dialysis is a routine but crucial procedure in patient evaluation. The total dialysis dose, expressed as Kt/V, has been widely recognised to be a major determinant of morbidity and mortality in haemodialysed patients. Many different factors influence the correct determination of Kt/V, such as urea sequestration in different body compartments, access and cardiopulmonary recirculation. These factors are responsible for urea rebound after the end of the haemodialysis session, causing poor Kt/V estimation. There are many techniques that try to overcome this problem. Some of them use analysis of blood-side urea samples, and in recent years, on-line urea monitors have become available to calculate haemodialysis dose from dialysate-side urea kinetics. All these methods require waiting until the end of the session to calculate the Kt/V dose. In this work, a neural network (NN) method is presented for early prediction of the Kt/V dose. Two different portions of the dialysate urea concentration-time profile (provided by an on-line urea minitor) were analysed: the entire curve A and the first half B, using an NN to predict the Kt/V and compare this with that provided by the monitor. The NN was able to predict Kt/V is the middle of the 4h session (B data) without a significant increase in the percentage error (B data: 6.69%±2.46%; A data: 5.58%±8.77%, mean±SD) compared with the monitor Kt/V.

Keywords

Artificial intelligence Urea Monitors Dialysate-side urea kinetics Neural networks 

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Copyright information

© IFMBE 2003

Authors and Affiliations

  • E. A. Fernández
    • 1
  • R. Valtuille
    • 2
  • P. Willshaw
    • 1
  • C. A. Perazzo
    • 1
  1. 1.Bioengineering DepartmentFavaloro UniversityBuenos AiresArgentina
  2. 2.RTC AdrogueDialysis Unit CenterBuenos AiresArgentina

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