Dose of dialysis predicted by continuous measurement of dialysate urea concentration

A. Cappello, R. Tartarini, F. Paolini, P. Calzavara
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Abstract

On-line estimation of urea kinetic parameters from dialysate urea concentration (DUN) is proposed and applied to dialysis dose prediction during therapy. Continuous measurement of DUN was performed by a post-filter enzymatic sensor (Hospal Dasco Spa) on six patients undergoing standard haemodialysis. In order to allow for early and reliable prediction of the end of dialysis values, a variable-volume double-pool model is used since the classical first order model cannot account for the fast-to-slow dynamics occurring during the first hour. Three parameter combinations are estimated at each time on the basis of the past DUN history: K/sub d//V/sub 0/, K/sub d/C/sub 0/ and VR, where K/sub d/, V/sub o/, C/sub o/, and VR are the dialyzer clearance, the total urea distribution volume, the initial plasma concentration, and the intra-extracellular volume ratio, respectively. Residuals between model-predicted and measured data have an average root mean square error of about 3% of the DUN excursion and model parameters show realistic values. The final dose of dialysis is predicted by multiplying K/sub d//V/sub o/ for the scheduled duration of the dialysis session. Prediction after 70 min from the beginning of the session differs on the average by less than 5% from the final value thus demonstrating the applicability of the proposed method. Furthermore, knowledge of model parameters allows for early and accurate prediction of the total urea removed.
通过连续测定透析液尿素浓度预测透析剂量
从透析液尿素浓度(DUN)中在线估计尿素动力学参数,并将其应用于治疗期间的透析剂量预测。通过过滤后酶传感器(Hospal Dasco Spa)对6名接受标准血液透析的患者进行DUN的连续测量。为了允许早期和可靠的预测透析值的结束,由于经典的一阶模型不能解释在第一个小时内发生的从快到慢的动态,因此使用了变容量双池模型。根据以往DUN病史,每次估计三个参数组合:K/sub d//V/sub 0/、K/sub d/C/sub 0/和VR,其中K/sub d/、V/sub 0/、C/sub 0/和VR分别为透析器清除率、总尿素分布体积、初始血浆浓度和细胞内-外体积比。模型预测和实测数据之间的残差平均均方根误差约为DUN偏移的3%,模型参数显示真实值。最后的透析剂量是通过乘以K/sub - d//V/sub - o/来预测透析的预定持续时间。从会议开始70分钟后的预测与最终值的平均差异小于5%,从而证明了所提出方法的适用性。此外,模型参数的知识允许早期和准确的总尿素去除预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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