Monitoring haemodialysis using electronic nose and chemometrics

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dc.contributor.author Fend, Reinhard en_UK
dc.contributor.author Bessant, Conrad M. en_UK
dc.contributor.author Williams, Anthony J. en_UK
dc.contributor.author Woodman, Anthony C. en_UK
dc.date.accessioned 2005-11-23T13:04:32Z
dc.date.available 2005-11-23T13:04:32Z
dc.date.issued 2004-07-15 en_UK
dc.identifier.citation Reinhard Fend, Conrad Bessant, Anthony J. Williams and Anthony C. Woodman, Monitoring haemodialysis using electronic nose and chemometrics, Biosensors and Bioelectronics, Volume 19, Issue 12, 15 July 2004, Pages 1581-1590 en_UK
dc.identifier.issn 0956-5663
dc.identifier.uri http://hdl.handle.net/1826/807
dc.identifier.uri http://dx.doi.org/10.1016/j.bios.2003.12.010
dc.description.abstract An ever-increasing number of patients have to undergo regular renal dialysis to compensate for acute or chronic renal failure. The adequacy of the treatment has a profound effect on patients’ morbidity and mortality. Therefore it is necessary to assess the delivered dialysis dose. For the quantification of the dialysis dose two parameters are most commonly used, namely the Kt/V value (normalised dose of dialysis) and the urea reduction rate, yet the prescribed dialysis dose often differs from the actual delivered dialysis dose. Currently, no interactive process is available to ensure optimal treatment. The aim of this study was to investigate the potential for an “electronic nose” as a novel monitoring tool for haemodialysis. Blood samples were analysed using an electronic nose, comprising an array of 14 conducting polymer sensors, and compared to traditional biochemistry. Principal component analysis and hierarchical cluster analysis were applied to evaluate the data, and demonstrated the ability to distinguish between pre-dialysis blood from post-dialysis blood independent of the method used. It is concluded that the electronic nose is capable of discriminating pre-dialysis from post-dialysis blood and hence, together with an appropriate classification model, suitable for on-line monitoring. en_UK
dc.format.extent 1946 bytes
dc.format.extent 263348 bytes
dc.format.mimetype text/plain
dc.format.mimetype application/pdf
dc.language.iso en en_UK
dc.publisher Elsevier en_UK
dc.subject.other Kidney disease en_UK
dc.title Monitoring haemodialysis using electronic nose and chemometrics en_UK
dc.type Article en_UK


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