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Updated: Aug 5, 2026
09:12
A Protein Microarray Assay for Serological Determination of Antigen-specific Antibody Responses Following Clostridium difficile Infection
Published on: June 15, 2018
Biomarkers for Early Severity Prediction in Clostridioides difficile Infection: Current Evidence, Clinical Utility,
Bianca Balas-Maftei1, Carmen-Elena Florea1, Lorena Abudanii2
1Grigore T. Popa University of Medicine and Pharmacy, 700115 Iasi, Romania.
Medicina (Kaunas, Lithuania)
|July 28, 2026
Summary
Identifying patients at high risk for severe Clostridioides difficile infection (CDI) is crucial. This review examines biomarkers to predict CDI severity, aiding early risk stratification and treatment decisions.
Area of Science:
- Infectious Diseases
- Clinical Biomarkers
- Healthcare Epidemiology
Background:
- Clostridioides difficile infection (CDI) is a major healthcare-associated infection with significant global impact.
- CDI presents with a spectrum of illness, from mild diarrhea to life-threatening complications.
- Early identification of high-risk patients is critical for effective management and reducing mortality.
Purpose of the Study:
- To review recent epidemiological data and risk factors for CDI severity.
- To evaluate the utility and limitations of various biomarkers in predicting CDI severity.
- To highlight the need for validated predictive models integrating biomarkers for clinical decision-making.
Main Methods:
- Narrative review of epidemiological data, trends, and risk factors.
- Examination of inflammatory, hematological, fecal, renal, and immune-response biomarkers.
- Analysis of current clinical practice and emerging research markers.
Main Results:
- Existing markers like CRP and WBC have limited specificity for predicting CDI severity.
- Emerging biomarkers (procalcitonin, interleukins, presepsin) may offer complementary prognostic value.
- A key challenge lies in determining the clinical utility and optimal application of these biomarkers.
Conclusions:
- Validated predictive models combining biomarkers with clinical and microbiological data are essential.
- Improved risk stratification at diagnosis can guide therapeutic decisions and optimize patient outcomes.
- Further research is needed to integrate biomarkers effectively into clinical practice for CDI management.
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