Analytical and Bioanalytical Chemistry

, Volume 403, Issue 2, pp 391–399

Infrared spectroscopy in hemodialysis: reagent-free monitoring of patient detoxification by infrared spectroscopy

  • Andreas Roth
  • Fabian Dornuf
  • Oliver Klein
  • Daniel Schneditz
  • Hildegard Hafner-Gießauf
  • Werner Mäntele
Paper in Forefront

DOI: 10.1007/s00216-012-5880-3

Cite this article as:
Roth, A., Dornuf, F., Klein, O. et al. Anal Bioanal Chem (2012) 403: 391. doi:10.1007/s00216-012-5880-3

Abstract

A method for monitoring hemodialysis based on quantitative infrared spectroscopic determination of the molecules dialyzed from patient blood is reported. The measurements are reagent-free and aim at real-time and in-line monitoring of the hemodialysis patient. A flow cell using attenuated total reflection infrared spectroscopy is coupled downstream of the dialysis filter unit. A calibration model has been developed from real hemodialysis samples analyzed by chemical reference analysis and from artificially mixed dialysis samples. The infrared monitoring of hemodialysis includes quantitative determination of urea as the lead substance, as well as glucose, lactate, and creatinine, all at a precision only limited by the chemical reference analysis. The flow cell can be fitted to all standard hemodialysis systems. Preliminary tests with hemodialysis patients have demonstrated that detoxification can be clearly monitored. Furthermore, these experiments demonstrate that a wide, real-time control of the patient’s physiological parameters is possible with this method, which could lead to increased patient safety.

Figure

Infrared Spectroscopy in hemodialysis: Dialysis and measuring principle

Keywords

Hemodialysis Infrared spectroscopy Attenuated total reflection Fourier transform infrared spectroscopy, FT-IR Glucose Urea 

Abbreviations

ATR

Attenuated total reflection

FT-IR

Fourier transform infrared

OGTT

Oral glucose tolerance test

PLS

Partial least squares

RMSECV

Root-mean-square error of cross-validation

RMSEP

Root-mean-square error of prediction

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Andreas Roth
    • 1
  • Fabian Dornuf
    • 1
  • Oliver Klein
    • 1
  • Daniel Schneditz
    • 2
  • Hildegard Hafner-Gießauf
    • 3
  • Werner Mäntele
    • 1
  1. 1.Institute of BiophysicsGoethe University Frankfurt am MainFrankfurt am MainGermany
  2. 2.Institute of Physiology, Center for Physiological MedicineMedical University of GrazGrazAustria
  3. 3.Division of Nephrology, Department of Internal MedicineMedical University of GrazGrazAustria

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