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

Content Provider	Springer Nature Link
Author	Fernández, E. A. Valtuille, R. Willshaw, P. Perazzo, C. A.
Copyright Year	2003
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.
Starting Page	392
Ending Page	396
Page Count	5
File Format	PDF
ISSN	01400118
Journal	Medical and Biological Engineering and Computing
Volume Number	41
Issue Number	4
e-ISSN	17410444
Language	English
Publisher	Springer-Verlag
Publisher Date	2003-01-01
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Artificial intelligence Urea Monitors Dialysate-side urea kinetics Neural networks Human Physiology Computer Applications Neurosciences Imaging Radiology Biomedical Engineering
Content Type	Text
Resource Type	Article
Subject	Biomedical Engineering Computer Science Applications

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