Dialysate-side urea kinetics. Neural network predicts dialysis dose during dialysis |
| |
Authors: | Email author" target="_blank">E?A?FernándezEmail author R?Valtuille P?Willshaw C?A?Perazzo |
| |
Institution: | (1) Bioengineering Department, Favaloro University, Buenos Aires, Argentina;(2) RTC Adrogue, Dialysis Unit Center, Buenos Aires, Argentina |
| |
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 |
本文献已被 PubMed SpringerLink 等数据库收录! |
|