Immune Profiling To Predict Outcome of Clostridioides difficile Infection

Author:

Abhyankar Mayuresh M.1,Ma Jennie Z.2,Scully Kenneth W.3,Nafziger Andrew J.1,Frisbee Alyse L.1,Saleh Mahmoud M.1,Madden Gregory R.1,Hays Ann R.4,Poulter Mendy5,Petri William A.1ORCID

Affiliation:

1. Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia, USA

2. Division of Biostatistics, Department of Public Health Sciences, University of Virginia Health System, Charlottesville, Virginia, USA

3. Department of Public Health Sciences, University of Virginia Health System, Charlottesville, Virginia, USA

4. Division of Gastroenterology and Hepatology, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia, USA

5. Department of Pathology, University of Virginia Health System, Charlottesville, Virginia, USA

Abstract

Clostridioides difficile infection is the most common health care-associated infection in the United States with more than 20% patients experiencing symptomatic recurrence. The complex nature of host-bacterium interactions makes it difficult to predict the course of the disease based solely on clinical parameters. In the present study, we built a robust prediction model using representative plasma biomarkers and clinical parameters for 90-day all-cause mortality. Risk prediction based on immune biomarkers and clinical variables may contribute to treatment selection for patients as well as provide insight into the role of immune system in C. difficile pathogenesis.

Funder

HHS | NIH | National Institute of Allergy and Infectious Diseases

Publisher

American Society for Microbiology

Subject

Virology,Microbiology

Reference47 articles.

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