OBJECTIVE Estimating the risk of a complicated course of Clostridium difficile 
infection (CDI) might help doctors guide treatment. We aimed to validate 3 
published prediction models: Hensgens (2014), Na (2015), and Welfare (2011). 
METHODS The validation cohort comprised 148 patients diagnosed with CDI between 
May 2013 and March 2014. During this period, 70 endemic cases of CDI occurred as 
well as 78 cases of CDI related to an outbreak of C. difficile ribotype 027. 
Model calibration and discrimination were assessed for the 3 prediction rules. 
RESULTS A complicated course (ie, death, colectomy, or ICU admission due to CDI) 
was observed in 31 patients (21%), and 23 patients (16%) died within 30 days of 
CDI diagnosis. The performance of all 3 prediction models was poor when applied 
to the total validation cohort with an estimated area under the curve (AUC) of 
0.68 for the Hensgens model, 0.54 for the Na model, and 0.61 for the Welfare 
model. For those patients diagnosed with CDI due to non-outbreak strains, the 
prediction model developed by Hensgens performed the best, with an AUC of 0.78. 
CONCLUSION All 3 prediction models performed poorly when using our total cohort, 
which included CDI cases from an outbreak as well as endemic cases. The 
prediction model of Hensgens performed relatively well for patients diagnosed 
with CDI due to non-outbreak strains, and this model may be useful in endemic 
settings. Infect Control Hosp Epidemiol 2017;38:897-905.