Immune Profiling To Predict Outcome of Clostridioides difficile Infection
Mayuresh M. Abhyankar, Z. Jennie, Kenneth W. Scully, Andrew J. Nafziger, Alyse Frisbee, Mahmoud Saleh, Gregory R. Madden, Ann R. Hays, Mendy Poulter, William A. Petri
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.