You are in:Home/Publications/Azar AT, Wahba KM (2011) Artificial Neural Network for Prediction of Equilibrated Dialysis Dose without Intradialytic Sample. Saudi J Kidney Dis Transpl.; 22(4):705-711.[Impact Factor: 0.77]

Dr. Assoc. Prof. Ahmad Taher Azar :: Publications:

Title:
Azar AT, Wahba KM (2011) Artificial Neural Network for Prediction of Equilibrated Dialysis Dose without Intradialytic Sample. Saudi J Kidney Dis Transpl.; 22(4):705-711.[Impact Factor: 0.77]
Authors: Not Available
Year: 2011
Keywords: Not Available
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Pages: Not Available
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Local/International: International
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Abstract:

Post-dialysis urea rebound (PDUR) is a cause of Kt/V overestimation when it is calculated from pre-dialysis and the immediate post-dialysis blood urea collections. Measuring PDUR requires a 30-or 60-min post-dialysis sampling, which is inconvenient. In this study, a supervised neural network was proposed to predict the equilibrated urea (C eq) at 60 min after the end of hemodialysis (HD). Data of 150 patients from a dialysis unit were analyzed. C eq was measured 60 min after each HD session to calculate PDUR, equilibrated urea reduction rate eq (URR), and ( eq Kt/V). The mean percentage of true urea rebound measured after 60 min of HD session was 19.6 ± 10.7. The mean urea rebound observed from the artificial neural network (ANN) was 18.6 ± 13.9%, while the means were 24.8 ± 14.1% and 21.3 ± 3.49% using Smye and Daugirdas methods, respectively. The ANN model achieved a correlation coefficient of 0.97 (P

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