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The Scientific World Journal
Volume 2012, Article ID 506486, 8 pages
Research Article

Optical Method for Cardiovascular Risk Marker Uric Acid Removal Assessment during Dialysis

1Department of Biomedical Engineering, Technomedicum, Tallinn University of Technology, Ehitajate tee 5, EST-19086 Tallinn, Estonia
2Department of Medicine and Health Sciences, Faculty of Health Sciences, Linköping University, SE 581 85 Linköping, Sweden
3Department of Nephrology UHL, County Council of Östergötland, SE 581 85 Linköping, Sweden
4Centre of Nephrology, North Estonian Medical Centre, Tallinn, Estonia

Received 13 December 2011; Accepted 30 January 2012

Academic Editors: B. R. Di Iorio and N. Futrakul

Copyright © 2012 Jana Holmar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The aim of this study was to estimate the concentration of uric acid (UA) optically by using the original and processed ultraviolet (UV) absorbance spectra of spent dialysate. Also, the effect of using several wavelengths (multi-wavelength algorithms) for estimation was examined. This paper gives an overview of seven studies carried out in Linköping, Sweden, and Tallinn, Estonia. A total of 60 patients were monitored over their 188 dialysis treatment procedures. Dialysate samples were taken and analysed by means of UA concentration in a chemical laboratory and with a double-beam spectrophotometer. The measured UV absorbance spectra were processed. Three models for the original and three for the first derivate of UV absorbance were created; concentrations of UA from the different methods were finally compared in terms of mean values and SD. The mean concentration (micromol/L) of UA was 49.7±23.0 measured in the chemical laboratory, and 48.9±22.4 calculated with the best estimate among all models. The concentrations were not significantly different (𝑃0.17). It was found that using a multi-wavelength and processed signal approach leads to more accurate results, and therefore these approaches should be used in future.