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Variable-Volume Kinetic Model to Estimate Absolute Blood Volume in Patients on Dialysis Using Dialysate Dilution

Samandari, Hamed*; Schneditz, Daniel; Germain, Michael J.; Horowitz, Joseph§; Hollot, Christopher V.; Chait, Yossi*

doi: 10.1097/MAT.0000000000000608
Biomedical Engineering

Long- and short-term adverse outcomes in hemodialysis (HD) have been associated with intradialytic hypotension, a common HD complication and significant cause of morbidity. It has been suggested that knowledge of absolute blood volume (ABV) could be used to significantly improve treatment outcomes. Different dilution-based protocols have been proposed for estimating ABV, all relying on the classic mono-exponential back-extrapolation algorithm (BEXP). In this paper, we introduce a dialysate dilution protocol and an estimation algorithm based on a variable-volume, two-compartment, intravascular blood water content kinetic model (VVKM). We compare ABV estimates derived using the two algorithms in a dialysate dilution study including three arterio-venous (AV) and three central-venous (CV) access patients, and multiple bolus injection tests (3–5) within each of several (2–6) HD treatments. The distribution of differences between ABV estimated from the two methods showed negligible systematic difference between the mean values of ABVs estimated from the BEXP and VVKM algorithms, however, the VVKM estimates were 53% and 42% more precise for the CV and AV patients, respectively. Good agreement was observed between measured and VVKM-estimated blood water concentration with the root-mean-square error (RMSE) less than 0.02 kg/kg (2%) and 0.03 kg/kg (3%) for AV and CV patients, respectively. The dilution protocol and the new VVKM-based estimation algorithm offer a noninvasive, inexpensive, safe, and practical approach for ABV estimation in routine HD settings.

From the *Department of Mechanical and Industrial engineering, University of Massachusetts at Amherst, Amherst, Massachusetts; Institute of Physiology, Medical University of Graz, Graz, Austria; Renal and Transplant Associates of New England, Springfield, Massachusetts; §Department of Mathematics and Statistics, University of Massachusetts at Amherst, Amherst, Massachusetts; and Department of Electrical and Computer Engineering, University of Massachusetts at Amherst, Amherst, Massachusetts.

Submitted for consideration January 2017; accepted for publication in revised form May 2017.

Disclosure: Daniel Schneditz received a speaker honorarium from Fresenius Medical Care Germany. Michael J. Germain is on the speaker bureau for Relypsa and OPKO and received a research grant from Rockwell Medical. Yossi Chait received a research grant from Rockwell Medical.

This work was supported in part by a grant from National Institutes of Health National Institute of Diabetes and Digestive and Kidney Diseases (K25 DK096006 to Yossi Chait).

Correspondence: Yossi Chat, Department of Mechanical and Industrial Engineering, University of Massachusetts at Amherst, Amherst, MA, 01003. Email: ychait@umass.edu Phone: +1 (413)545-0134

Copyright © 2018 by the American Society for Artificial Internal Organs