2010. Volatile Organic Compounds Patterns in Breath, Plasma, and Stool in Patients with Clostridium difficile Infection: A Cross-Sectional Proof of Concept Study. (26th November 2018)

• Record Type: Journal Article
• Authors: John, Teny Mathew; Shrestha, Nabin; Procop, Gary W; Grove, David; Leal, Sixto; Jacob, Ceena Neena; Butler, Robert; Dweik, Raed
• Is Part Of: Open forum infectious diseases. Volume 5(2018)Supplement 1
• Page Start: S585
• Page End: S585
• Publication Date: 2018-11-26
• Subjects: Communicable diseases -- Periodicals; Medical microbiology -- Periodicals; Infection -- Periodicals; 616.9
• DOI: 10.1093/ofid/ofy210.1666
• Languages: English
• ISSNs: 2328-8957

Abstract

Abstract: Background: Volatile organic compounds (VOCs) are hydrocarbon compounds which are end product metabolites of physiological and pathophysiological processes. Many disease processes can be identified by examining metabolome patterns in clinical samples from patients. The purpose of this study was to identify Clostridium difficile infection (CDI) based on differences in VOCs in stool, blood and breath of patients with CDI and controls without. Methods: Patients aged >18 years at Cleveland Clinic with CDI (> 3 watery stools in the preceding 24 hours and stool PCR positive for C. difficile ), and matched controls (for age, sex, and date of PCR test) were included. Stool and plasma samples (within 24 hours of collection) and fresh breath samples were collected. Headspace gas from clinical samples was tested using selected ion flow tube mass spectrometry (SIFT-MS) on a VOICE200 instrument ( Syft Technologies Ltd., Christchurch, New Zealand ). The MS assay comprised of 22 common analytes: 2-propanol, acetaldehyde, acetone, acetonitrile, acrylonitrile, benzene, carbon disulfide, dimethyl sulfide, ethanol, isoprene, pentane, 1-decene, 1-heptene, 1-nonene, 1-octene, 3-methyl hexane, 2-nonene, ammonia, ethane, hydrogen sulfide, triethyl amine, and trimethyl amine. VOC analysis findings were classified as positive or negative using the K-nearest neighbors (KNN) method. Model accuracy was evaluated by k -fold cross-validation with 5-folds. Sensitivity and specificity were determined and receiver-operating characteristics curves generated for each sample type. Results: Thirty-one patients with CDI and 31 controls were studied. The optimal KNN classifier model was achieved with k = 7, 5, and 9, for breath, plasma, and stool samples, respectively. The sensitivity/specificity for detection of CDI were 87.1%/77.4%, 66.7%/63.6%, and 61.3%/36.4%, for breath, stool, and plasma samples, respectively. Model accuracy was no better if positives were limited to those with C. difficile PCR CT <30 cycles. Conclusion: VOC analysis of fresh breath, but not plasma or stool samples ≤24 hours old, by the method studied had good sensitivity and moderate specificity for identifying patients with CDI. Disclosures: All authors: No reported disclosures.