Diagnostic Guidance for C. difficile Infections

  • Monique J. T. Crobach
  • Amoe Baktash
  • Nikolas Duszenko
  • Ed J. Kuijper
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 1050)


Diagnosis of Clostridium difficile infection (CDI) can be challenging. First of all, there has been debate on which of the two reference assays, cell cytotoxicity neutralization assay (CCNA) or toxigenic culture (TC) should be considered the gold standard for CDI detection. Although the CCNA suffers most from suboptimal storage conditions and subsequent toxin degradation, TC is reported to falsely increase CDI detection rates as it cannot differentiate CDI patients from patients asymptomatically colonised by toxigenic C. difficile. Several rapid assays are available for CDI detection and fall into three broad categories: (1) enzyme immunoassays for glutamate dehydrogenase, (2) enzyme immunoassays for toxins A/B and (3) nucleic acid amplification tests detecting toxin genes. All three categories have their own limitations, being suboptimal specificity and/or sensitivity or the inability to discern colonised patients from CDI patients. In light of these limitations, multi-step algorithmic testing has now been advocated by international guidelines in order to optimize diagnostic accuracy. Despite these recommendations, testing methods between hospitals vary widely, which impacts CDI incidence rates. CDI incidence rates are also influenced by sample selection criteria, as several studies have shown that if not all unformed stool samples are tested for CDI, many cases may be missed due to an absence of clinical suspicion. Since methods for diagnosing CDI remain imperfect, there has been a growing interest in alternative testing strategies like faecal biomarkers, immune modulating interleukins, cytokines and imaging methods. At the moment, these alternative methods might play an adjunctive role, but they are not suitable to replace conventional CDI testing strategies.


Clostridium difficile Diagnostics Testing Algorithmic testing 


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Monique J. T. Crobach
    • 1
  • Amoe Baktash
    • 1
  • Nikolas Duszenko
    • 1
  • Ed J. Kuijper
    • 2
    • 3
  1. 1.Department of Medical Microbiology, Centre for Infectious DiseasesLeiden University Medical CentreLeidenThe Netherlands
  2. 2.ESCMID Study Group for C.difficile (ESGCD)BaselSwitzerland
  3. 3.Department of Medical Microbiology, Center of Infectious DiseasesLeiden University Medical CenterLeidenThe Netherlands

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