2019 article
Human fecal metabolomic profiling could inform Clostridioides difficile infection diagnosis and treatment
Theriot, C. M., & Fletcher, J. R. (2019, September 3). JOURNAL OF CLINICAL INVESTIGATION, Vol. 129, pp. 3539–3541.
MeSH headings : Clostridioides difficile; Clostridium Infections; Diarrhea; Feces; Humans; Microbiota
TL;DR:
A logistic regression model based on the fecal metabolome is used and a metabolic definition of human C. difficile infection is constructed, which could improve diagnostic accuracy and aid in the development of targeted therapeutics against this pathogen.
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UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science; OpenAlex)
Source: Web Of Science
Added: September 30, 2019
Clostridioides difficile is a significant public health threat, and diagnosis of this infection is challenging due to a lack of sensitivity in current diagnostic testing. In this issue of the JCI, Robinson et al. use a logistic regression model based on the fecal metabolome that is able to distinguish between patients with non-C. difficile diarrhea and C. difficile infection, and to some degree, patients who are asymptomatically colonized with C. difficile. The authors construct a metabolic definition of human C. difficile infection, which could improve diagnostic accuracy and aid in the development of targeted therapeutics against this pathogen.