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Development of medical point-of-care applications for renal medicine and tuberculosis based on electronic nose technology

By Reinhard Fend


INTRODUCTION: Current clinical diagnostics are based on biochemical, immunological or microbiological methods. However, these methods are operator dependent, time consuming, expensive and require special skills, and are therefore not suitable for point-of-care testing. Recent developments in gas-sensing technology and pattern recognition methods make electronic nose technology an interesting alternative for medical point-of-care devices. METHODS: We applied a gas sensor array based on 14 conducting polymers to monitor haemodialysis in vitro and to detect pulmonary tuberculosis in both culture and sputum. RESULTS and DISCUSSION: The electronic nose is able to distinguish between control blood and “uraemic” blood. Furthermore, the gas sensor array is not only capable of discriminating pre- from post-dialysis blood (97% accuracy) but also can follow the volatile shift occurring during a single haemodialysis session. The electronic nose can be used for both dialysate side and blood-side monitoring of haemodialysis. The pattern observed for post- and pre-dialysis blood might reflect the health status of the patients and can therefore be related to the long-term outcome. Furthermore, the gas sensor array was also able to discriminate between Mycobacterium spp. and other lung pathogens such as Pseudomonas aeruginosa. More importantly the gas sensor array was capable of resolving different Mycobacterium spp. such as Mycobacterium tuberculosis, M. scrofulaceum, and M. avium in both liquid culture and spiked sputum samples. The detection limit for M. tuberculosis in both sputum and liquid culture is 1 x 104 mycobacteria ml-1 and therefore partially fulfils the requirement set by the WHO. The gas sensor array was able to detect culture proven TB with a sensitivity of 89% and a specificity of 91%. CONCLUSIONS: In conclusion, this study has shown the ability of an electronic nose as a point-of-care device in these areas

Publisher: Cranfield University at Silsoe
Year: 2004
OAI identifier:
Provided by: Cranfield CERES

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  1. (1988). A case-control study of chorioamnionic infection and histologic chorioamnionitis in prematurity.
  2. (1997). A highly sensitive amperometric creatinine sensor, Anal Chim Acta, doi
  3. (2000). An electronic nose system to diagnose illness,
  4. (1988). Chemometrics: A Textbook. Elsevier Science Publishers, Amsterdam, The Netherlands,
  5. (2004). Comparison of PCR with the routine diagnostic procedure of tuberculosis in a population of high tuberculosis
  6. (2004). Detection of Mycobacterium tuberculosis (TB) in vitro and in situ using an electronic nose in combination with a neural network system, Biosens Bioelectron (in press) References 222 Cranfield University at Silsoe Reinhard Fend
  7. (1994). Determination of Kt/V and Protein Catabolic Rate Using Pre- and Postdialysis Blood Urea Nitrogen Concentrations, Nephron, doi
  8. (1997). Effect of a two compartment distribution on apparent urea distribution volume, Kidney Int, 51:1270-1273 References 207 Cranfield University at Silsoe Reinhard Fend doi
  9. (1993). Effect of haemodialysate and its peptide fractions on acetylcholinesterase activity in erythrocytes from healthy subjects and patients with terminal renal failure. Int Urol Nephrol, 25:503-508 References 228 Cranfield University at Silsoe Reinhard Fend
  10. (1999). Electronic nose analysis of urine samples containing blood.
  11. (1982). Gas detection by means of surface plasmon resonance, doi
  12. (1996). How much peritoneal dialysis is required for the maintenance of a good nutritional state. Kidney Int, 50:56-61 Mc Dermott FT.
  13. (1999). Imbalance of Oxidants and Antioxidants doi
  14. (1976). Inhibition of bovine renal adenylate cyclase by urinary products,
  15. (1997). Mycobacterium Growth Indicator Tube testing in conjunction with the AccuProbe or the Amplicor-PCR assay for detecting and identifying mycobacteria from sputum samples,
  16. (2002). Predicting type 2 diabetes using an electronic nose-based artificial neural network analysis. Diabetes Nutr Metab, 15: 215- 221 Moret-Bonillo V.
  17. (1990). Rapid diagnosis of meningitis by frequency-pulsed electron-capture gas-liquid chromatography detection of carboxylic aid in cerebrospinal fluid,
  18. (1994). Rapid identification of species within the Mycobacterium tuberculosis complex by artificial neural network analysis of pyrolysis mass spectra, J Med Microbiol, 40:170-173 References 210 Cranfield University at Silsoe Reinhard Fend
  19. (2004). References 202 Cranfield University at Silsoe Reinhard Fend
  20. References 230 Cranfield University at Silsoe Reinhard Fend
  21. (2003). The internet classic archive. New York: Web Atomics Ampuero
  22. (1999). Use of nucleic acid probes for identification of Mycobacterium tuberculosis directly from MB/BactT bottles,

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