N8. Clostridium difficile
Oral Abstract Submission
Michael G. Dieterle, BS
MSTP Student
Medical Scientist Training Program (MSTP), Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, Michigan
Ann Arbor, MI
Disclosure: Nothing to disclose
Rosemary K.B. Putler, MS
Bioinformatics Scientist
Thermo Fisher Scientific
Ann Arbor, MI
Disclosure: Nothing to disclose
Donald A. Perry, MD,MS,MPH
Fellow
University of Michigan
Ann Arbor, MI
Disclosure: Nothing to disclose
Lisa Abernathy-Close, Ph.D.
Postdoctoral Research Fellow
University of Michigan
Ann Arbor, MI
Disclosure: Nothing to disclose
Naomi Perlman
Undergraduate Student
University of Michigan
Ann Arbor, MI
Disclosure: Nothing to disclose
Aline Penkevich, BS
Research Laboratory Technician
University of Michigan
Ann Arbor, MI
Disclosure: Nothing to disclose
Alexandra Standke, German University Diplom equivalent to US Master
Research Laboratory Technician
Department of Internal Medicine, Infectious Diseases Division University of Michigan, Ann Arbor, Michigan
Ann Arbor, MI
Disclosure: Nothing to disclose
Micah Keidan, BS
Research Laboratory Technician
University of Michigan
Ann Arbor, MI
Disclosure: Nothing to disclose
Kimberly Vendrov, B.S. in Animal Science
Research Lab Specialist, Lab Manager
Department of Internal Medicine, Infectious Diseases Division University of Michigan, Ann Arbor, Michigan
Ann Arbor, MI
Disclosure: Nothing to disclose
Ingrid L. Bergin, VMD, MS, DACLAM, DACVP
Associate professor
University of Michigan
Ann Arbor, MI
Disclosure: Nothing to disclose
Vincent B. Young, MD, PhD
William Henry Fitzbutler Collegiate Professor
University of Michigan
Ann Arbor, MI
Disclosure: Bio-K+ International: Consultant
Pantheryx: Consultant
Vedanta Biosciences: Consultant
Krishna Rao, MD, MS
Assistant Professor
Department of Internal Medicine, Infectious Diseases Division University of Michigan, Ann Arbor, Michigan
Ann Arbor, MI
Disclosure: BIO-K PLUS INTERNATIONAL, INC.: Consultant
Background : Clostridium difficile infection (CDI) can result in severe disease and death. We are currently unable to identify patients at risk for developing adverse outcomes. We previously showed multiple inflammatory mediators were associated with severity and adverse outcomes. Here, we set out to validate these findings in patients and a murine model of CDI.
Methods : CDI was diagnosed by the clinical microbiology laboratory. Sera was collected ≤48 hours after diagnosis from pilot (Oct 2010–Nov 2012) and validation (Jan–Sept 2016) cohorts. Inflammatory mediators were measured with a custom multiplex assay. IDSA severity was defined as serum creatinine > 1.5-fold above baseline or white blood cell count > 15,000 cells/mL. The 30-day outcomes were all-cause mortality and disease-related complications (DRCs): ICU admission, colectomy or death attributed to CDI. We sought to validate our patient findings in murine model of CDI: 67 antibiotic treated mice were infected with 630g (37 mice), a low virulence strain, or VPI 10463 (30 mice), a highly virulent strain. Host responses were assessed with a murine version of the multiplex panel. Unadjusted and adjusted models were built using logistic and L1 regression, respectively.
Results : The pilot cohort had 156 CDI cases; 63 (40%) with IDSA severity. The inflammatory response in IDSA severe cases was distinct based on redundancy analysis of all measured analytes (P =.01). In unadjusted analysis, IL-2R, IL-6, and procalcitonin associated with severity (P < .001, P =.003, & P =.003 respectively). The same findings were seen in the validation cohort of 272 cases (Figure 1). Unadjusted analyses revealed several predictors of severity and outcomes (Table 1). Adjusted models performed well (Figure 2) with AUCs of 0.74 [0.67-0.81] (IDSA severity), 0.89 [0.83-0.95] (death) and 0.84 [0.74-0.95] (DRCs). Application of each model to the mouse cohort for high vs. low virulence infections revealed AUCs of 0.59 [0.44-0.74], 0.96 [0.90-1.0], and 0.89 [0.81-0.97] (Figure 3).
Conclusion : In both humans and a murine CDI model, a panel of biomarkers from sera associated with severe CDI and predicted adverse outcomes. Our results support the possibility of a serum-based biomarker panel to inform medical decision making for patients with CDI.
