Testing and Diagnosis of Clostridioides difficile Infection in Special Scenarios: A Systematic Review

Clostridioides difficile infection (CDI) is a clinical and laboratory diagnosis. Populations at higher risk of developing disease require a high clinical index of suspicion for laboratory testing to avoid incorrect assumptions of colonization. Common risk factors include recent antibiotic use, elderly (>65 years old), and immunocompromised patients. C. difficile assays should be ordered in an algorithm approach to diagnose an infection rather than colonization. Screening tests are widely available in hospital systems, but novel molecular testing may aid in diagnosis in patients with inconclusive or discordant antigen and toxin test results.  Methods: Data was extracted from PubMed, Scopus, and Cumulative Index of Nursing and Allied Health Literature (CINAHL) databases based on the keywords "clostridioides difficile", "toxin assay", and "toxic megacolon". The data extracted is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. A total of 27 reports were included in this systematic review.

Testing patients with a significant gastrointestinal surgical history, hypogammaglobulinemia, inflammatory bowel disease, intensive care unit, and immunocompromised patients for CDI is highly recommended. Diarrhea in these subsets of patients requires correlation of clinical context and an understanding of assay results to avoid over- and under-treating.

CDI should be considered in all patients with traditional risk factors. Heightened clinical suspicion of CDI is required in patients with hypogammaglobulinemia, transplant recipients, patients with gastrointestinal surgical history, and inflammatory bowel disease. Testing should be limited to patients with clinical manifestations of CDI to ensure a high pretest probability for test interpretation. Healthcare workers should adhere to testing algorithms to optimize yield in the appropriate clinical context. Diagnostic assays should follow a sequential, stepwise approach to categorize the toxin expression status of the bacteria accurately.