ONLINE ESTIMATION AND PREDICTION OF UREA KINETICS DURING HEMODIALYSIS- A SIMULATION APPROACH

Citation
G. Comai et al., ONLINE ESTIMATION AND PREDICTION OF UREA KINETICS DURING HEMODIALYSIS- A SIMULATION APPROACH, International journal of artificial organs, 18(5), 1995, pp. 245-253
Citations number
12
Categorie Soggetti
Engineering, Biomedical
ISSN journal
03913988
Volume
18
Issue
5
Year of publication
1995
Pages
245 - 253
Database
ISI
SICI code
0391-3988(1995)18:5<245:OEAPOU>2.0.ZU;2-C
Abstract
A new method for the on-line estimation of urea kinetic parameters fro m blood urea concentration (BUN) continuously measured during a dialys is session is proposed. The method, based on the variable-volume doubl e-pool model, is evaluated through a simulation approach in order to e asily consider a large set of well-controlled test conditions. The mod el is characterized by six parameters, knowledge of which enables earl y prediction of the end dialysis urea concentration and the dose of di alysis. The sensitivity of the model predicted BUN with respect to the parameters was first analyzed to investigate which can be reliably es timated from blood urea measurements taken at a suitable rate. This an alysis showed that the model predicted BUN is highly sensitive to the initial blood urea concentration and to the dialyzer clearance, normal ized with respect to the total initial distribution volume, while if i s scarcely influenced by the normalized ultrafiltration and urea gener ation rates. The new on-line estimation technique keeps these two last parameters constant and takes advantage of an original analytic solut ion of the second order urea kinetics. The results of the estimation p rocess on realistic simulated data showed that the proposed method pro vides early and reliable estimates of the normalized clearance and of the end dialysis concentration. The transcellular mass transfer coeffi cient and the intra-extra cellular volume ratio can also be estimated, although with less accuracy. Moreover, it was shown that the use of t he single-pool model, instead of the double-pool one, provides systema tic errors on the estimates.