Presently, 2 to 4 days elapse between sampling at infection suspicion and result of microbial diagnostics. This delay for the identification of pathogens causes quite often a late and/or inappropriate initiation of therapy for patients suffering from infections. Bad outcome and high hospitalization costs are the consequences of these currently existing limited pathogen identification possibilities. For this reason, we aimed to apply the innovative method multi-capillary column–ion mobility spectrometry (MCC-IMS) for a fast identification of human pathogenic bacteria by determination of their characteristic volatile metabolomes. We determined volatile organic compound (VOC) patterns in headspace of 15 human pathogenic bacteria, which were grown for 24 h on Columbia blood agar plates. Besides MCC-IMS determination, we also used thermal desorption–gas chromatography–mass spectrometry measurements to confirm and evaluate obtained MCC-IMS data and if possible to assign volatile compounds to unknown MCC-IMS signals. Up to 21 specific signals have been determined by MCC-IMS for Proteus mirabilis possessing the most VOCs of all investigated strains. Of particular importance is the result that all investigated strains showed different VOC patterns by MCC-IMS using positive and negative ion mode for every single strain. Thus, the discrimination of investigated bacteria is possible by detection of their volatile organic compounds in the chosen experimental setup with the fast and cost-effective method MCC-IMS. In a hospital routine, this method could enable the identification of pathogens already after 24 h with the consequence that a specific therapy could be initiated significantly earlier.

MCC-IMS may be a suitable method to determine propofol concentrations in exhaled air, and may be used to predict propofol concentrations in serum.

Headspace analyses over microbial cultures using multi-capillary column-ion mobility spectrometry (MCC-IMS) could lead to a faster, safe and cost-effective method for the identification of pathogens. Recent studies have shown that MCC-IMS allows identification of bacteria and fungi, but no information is available from when on during their growth a differentiation between bacteria is possible. Therefore, we analysed the headspace over human pathogenic reference strains of Escherichia coli and Pseudomonas aeruginosa at four time points during their growth in a complex fluid medium. In order to validate our findings and to answer the question if the results of one bacterial strain can be transferred to other strains of the same species, we also analysed the headspace over cultures from isolates of random clinical origin. We detected 19 different volatile organic compounds (VOCs) that appeared or changed their signal intensity during bacterial growth. These included six VOCs exclusively changing over E. coli cultures and seven exclusively changing over P. aeruginosa cultures. Most changes occurred in the late logarithmic or static growth phases. We did not find differences in timing or trends in signal intensity between VOC patterns of different strains of one species. Our results show that differentiation of human pathogenic bacteria by headspace analyses using MCC-IMS technology is best possible during the late phases of bacterial growth. Our findings also show that VOC patterns of a bacterial strain can be transferred to other strains of the same species.

Ion mobility spectrometry is increasingly in demand for medical applications and its potential for implementation in food quality and safety or process control suggest rising use of instruments in this field as well. All those samples are commonly extremely complex and mostly humid mixtures. Therefore, pre-separation techniques have to be applied. As ion mobility spectrometers with gas-chromatographic pre-separation acquire a huge amount of data, effective data processing and automated evaluation by comparison of detected peak pattern with data bases have to be utilised. This requires accurate on-line calibration of the instruments to guarantee reproducible results, in particular with respect to identification of an analyte by determination of its ion mobility and retention time. To reduce environmental and instrumental influence, the reduced ion mobility is used. It is derived from the drift time normalised to electric field, length of the drift region and to temperature and pressure of the drift gas (traditional method). All data required for this normalisation are afflicted with a particular error and thus leading to a deviation of the calculated ion mobility value. Furthermore, this traditional method enables a calculation of the reduced ion mobility only after the measurement. To avoid those errors and to enable on-line calibration of ion mobility, an instrument specific factor is implemented generally representing all relevant variables. This factor can be determined from an initial measurement of few spectra and can thereafter be applied on the following measurement. The application of this approach obtained reproducible reduced ion mobility values for positive and negative ions over a broad drift time range and for common variation of ambient conditions as well for varying instrument conditions such as electric fields respectively drift times and in different drift gases. Moreover, the reduced ion mobility is available already during the measurements with a significantly higher reliability and accuracy which was increased to a factor of 5 compared to the traditional ion mobility determination and enables an on-line identification of analytes for the first time.

Patients operated for infective endocarditis (IE) are at high risk of developing an excessive systemic hyperinflammatory state, resulting in systemic inflammatory response syndrome and septic shock. Hemoadsorption (HA) by cytokine adsorbers has been successfully applied to remove inflammatory mediators. This randomized controlled trial investigates the effect of perioperative HA therapy on inflammatory parameters and hemodynamic status in patients operated for IE. A total of 20 patients were randomly assigned to either HA therapy or the control group. HA therapy was initiated intraoperatively and continued for 24 hours postoperatively. Cytokine levels (IL‐6, IL‐1b, TNF‐α), leukocytes, C‐reactive protein (CRP), and Procalcitonin (PCT) as well as catecholamine support, and volume requirement were compared between both groups. Operative procedures included aortic (n = 7), mitral (n = 6), and multiple valve surgery (n = 7). All patients survived to discharge. No significant differences concerning median cytokine levels (IL‐6 and TNF‐α) were observed between both groups. CRP and PCT baseline levels were significantly higher in the HA group (59.5 vs. 26.3 mg/dL, P = .029 and 0.17 vs. 0.05 µg/L, P = .015) equalizing after surgery. Patients in the HA group required significantly higher doses of vasopressors (0.093 vs. 0.025 µg/kg/min norepinephrine, P = .029) at 12 hours postoperatively as well as significantly more overall volume replacement (7217 vs. 4185 mL at 12 hours, P = .015; 12 021 vs. 4850 mL at 48 hours, P = .015). HA therapy did neither result in a reduction of inflammatory parameters nor result in an improvement of hemodynamic parameters in patients operated for IE. For a more targeted use of HA therapy, appropriate selection criteria are required.