Journal Article

2409. External Validation and Comparison of Clostridioides difficile Severity Scoring Systems

Perry, Donald A, Patel, Pratish, Micic, Dejan, Menon, Anitha, Higgins, Peter, Shirley, Daniel, Putler, Rosemary K B, Young, Vincent B, Rao, Krishna

2019

Overview

Background Annually in the US alone, Clostridioides difficile infection (CDI) afflicts nearly 500,000 patients causing 29,000 deaths. Since early and aggressive interventions could save lives but are not optimally deployed in all patients, numerous studies have published predictive models for adverse outcomes. These models are usually developed at a single institution, and largely are not externally validated. This aim of this study was to validate the predictability for severe CDI with previously published risk scores in a multicenter cohort of patients with CDI. Methods We conducted a retrospective study on four separate inpatient cohorts with CDI from three distinct sites: the Universities of Michigan (2010–2012 and 2016), Chicago (2012), and Wisconsin (2012). The primary composite outcome was admission to an intensive care unit, colectomy, and/or death attributed to CDI within 30 days of positive test. Structured query and manual chart review abstracted data from the medical record at each site. Published CDI severity scores were assessed and compared with each other and the IDSA guideline definition of severe CDI. Sensitivity, specificity, area under the receiver operator characteristic curve (AuROC), precision-recall curves, and net reclassification index (NRI) were calculated to compare models. Results We included 3,775 patients from the four cohorts (Table 1) and evaluated eight severity scores (Table 2). The IDSA (baseline comparator) model showed poor performance across cohorts(Table 3). Of the binary classification models, including those that were most predictive of the primary composite outcome, Jardin, performed poorly with minimal to no NRI improvement compared with IDSA. The continuous score models, Toro and ATLAS, performed better, but the AuROC varied by site by up to 17% (Table 3). The Gujja model varied the most: from most predictive in the University of Michigan 2010–2012 cohort to having no predictive value in the 2016 cohort (Table 3). Conclusion No published CDI severity score showed stable, acceptable predictive ability across multiple cohorts/institutions. To maximize performance and clinical utility, future efforts should focus on a multicenter-derived and validated scoring system, and/or incorporate novel biomarkers. Disclosures All authors: No reported disclosures.

• Publisher: Oxford University Press
• Subject: Abstracts / Biofilms / Diarrhea / Epidemics / Epidemiology / Hospitals / Infections / Microbiota / Mortality / Toxins / Trends / Virulence