BackgroundAlthough “uremic fetor” has long been felt to be diagnostic of renal failure, the compounds exhaled in uremia remain largely unknown so far. The present work investigates whether breath analysis by ion mobility spectrometry can be used for the identification of volatile organic compounds retained in uremia.MethodsBreath analysis was performed in 28 adults with an eGFR ≥60 ml/min per 1.73 m2, 26 adults with chronic renal failure corresponding to an eGFR of 10–59 ml/min per 1.73 m2, and 28 adults with end-stage renal disease (ESRD) before and after a hemodialysis session. Breath analysis was performed by ion mobility spectrometryafter gas-chromatographic preseparation. Identification of the compounds of interest was performed by thermal desorption gas chromatography/mass spectrometry.ResultsBreath analyses revealed significant differences in the spectra of patients with and without renal failure. Thirteen compounds were chosen for further evaluation. Some compounds including hydroxyacetone, 3-hydroxy-2-butanone and ammonia accumulated with decreasing renal function and were eliminated by dialysis. The concentrations of these compounds allowed a significant differentiation between healthy, chronic renal failure with an eGFR of 10–59 ml/min, and ESRD (p<0.05 each). Other compounds including 4-heptanal, 4-heptanone, and 2-heptanone preferentially or exclusively occurred in patients undergoing hemodialysis.ConclusionImpairment of renal function induces a characteristic fingerprint of volatile compounds in the breath. The technique of ion mobility spectrometry can be used for the identification of lipophilic uremic retention molecules.
Abstract. In this paper we propose a novel peak detection algorithm for 2-dimensional analytical data. The proposed algorithm utilizes the properties of the second derivative and curvature of (regular) surfaces to perform peak detection. Raw data used in this study for performance demonstration were obtained by a hyphenated system called gas-chromatographic column ion mobility spectrometer (GC-IMS). GC-IMS is a two stage technique for separation of gasphased (organic) compounds. Despite the good performance of the MCC-IMS separation in general, there are still unsatisfactory cases where the substances overlap and the recorded signals nearly merge. Frequently used peak detection algorithm for 2-dimensional data, like the watershed algorithm, do not perform well in those cases. Preliminary empirical results show good peak detection performance of the proposed algorithm. Furthermore the results indicate that the proposed algorithm is capable to solve the problem of peak detection even in cases of strong peak overlapping.
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