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

• Published in: TheScientificWorld Vol. 2012; no. 2012; pp. 1 - 8
• Main Authors: Holmar, Jana, Fridolin, Ivo, Uhlin, Fredrik, Lauri, Kai, Luman, Merike
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Puplishing Corporation 01.01.2012; The Scientific World Journal; Hindawi Limited; Wiley
• Subjects: Absorbance; Biomarkers - blood; Cardiovascular diseases; Cardiovascular Diseases - blood; Cardiovascular Diseases - diagnosis; Dialysis; Dialysis Solutions - chemistry; Female; Health risks; Humans; Male; Middle Aged; Prognosis; Reproducibility of Results; Risk Factors; Sensitivity and Specificity; Signal processing; Spectrophotometry, Ultraviolet - methods; Ultraviolet spectra; Uric acid; Uric Acid - isolation & purification; Uric Acid - urine; Wavelength; Wavelengths; Sweden; Estonia
• ISSN: 2356-6140; 1537-744X; 1537-744X
• DOI: 10.1100/2012/506486

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 (P≥0.17). 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.