A novel ANFIS application for prediction of post-dialysis blood urea concentration

摘要

Dialysis dose (Kt/V) is mostly dependent on dialysis kinetic variables such as pre-dialysis and post-dialysis blood urea nitrogen concentration (C_(post)), ultrafiltration (UF) volume, duration of the dialysis procedure, and urea distribution volume. Therefore, post-dialysis blood urea concentration is used to assess the dialysis efficiency. It gradually decreases to about 30% of the pre-dialysis value depending on the urea clearance rate during the period of dialysis. If the urea removal is inadequate, then dialysis is inadequate. This paper proposes a novel method, Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict the post-dialysis blood urea concentration. The advantage of this neuro-fuzzy hybrid approach is that it does not require the model structure to be known a priori, in contrast to most of the urea kinetic modelling techniques. The accuracy of the ANFIS was prospectively compared with other traditional methods for predicting single pool dialysis dose (_(sp)Kt/V). The results are highly promising, and a comparative analysis suggests that the proposed modelling approach outperforms other traditional urea kinetic models (UKM).