Care of patients with potential CDI can involve isolation and use of antibiotics, often before a definitive diagnosis is available, impacting healthcare resource and contributing to antibiotic resistance. There is… Click to show full abstract
Care of patients with potential CDI can involve isolation and use of antibiotics, often before a definitive diagnosis is available, impacting healthcare resource and contributing to antibiotic resistance. There is anecdotal evidence that the faeces of CDI patients have a distinctive odour, while it is well-established that changes in the gut microbiota are associated with changes in the volatile organic compounds (VOC) produced. A total of twenty-four candidate volatile biomarkers were identified from a review of the literature including in vitro, animal and human studies. Using thermal desorption-gas chromatography-time-of flight mass spectrometry (TD-GC-ToFMS), VOC emission rates were determined on stored frozen stool samples from 53 CDI-positive and 53 CDI-negative patients with unexplained diarrhoea which had previously been diagnosed using enzymatic and nucleic acid amplification tests. Sample preparation was limited to placement of a subsample in an appropriate container. Compounds exhibiting a statistically significant difference (p < 0.05) in emission rate between the CDI-positive and–negative groups and a corresponding area under the receiver-operator characteristic curve (ROC) >0.7 were considered potentially indicative of CDI. Seven compounds were so identified: propan-1-ol (ROC 0.75), 3-methylbutanal (ROC 0.84), ethyl propionate (ROC 0.81), hexanoic acid (ROC 0.73), 4-methylphenol (ROC 0.81), dodecane (ROC 0.80) and indole (ROC 0.85). A number of potential volatile biomarkers of CDI can be sampled rapidly and with little prior preparation from faecal samples of patients with diarrhoea. Of these 4-methylphenol (p-cresol) is of particular interest as it has been anecdotally linked to CDI and is closely related to the biology and virulence of Clostridium difficile. This approach shows promise for the rapid, point-of-care diagnosis of CDI with good sensitivity and specificity.
               
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