A simple, widely available and inexpensive model for predicting Clostridium difficile infection severity and mortality and that identifies people who are at risk for C difficile at the time of their admission to the emergency department is presented in a study published in JAMA Surgery.
Using a cohort of 2065 patients admitted for C difficile infection through the emergency department of 2 tertiary referral centers from 2005 to 2015, investigators measured the primary and secondary outcomes of inpatient mortality and the need for a monitored care setting, need for vasopressors, and rates of inpatient colectomy. The model was built by stratifying the sample according to eosinophil count (0.0 cells/μL or >0.0 cells/μL) at admission and applying multivariable logistic regression to predict inpatient mortality and other disease-related outcomes.
Patients with undetectable eosinophil counts at admission experienced increased in-hospital mortality in both the training (odds ratio [OR] 2.01; 95% CI, 1.08-3.73; P =.03) and validation (OR 2.26; 95% CI, 1.33-3.83; P =.002) cohorts using both univariable and multivariable analysis. Undetectable counts were also associated with indicators of severe sepsis, including admission to monitored care settings (OR 1.40; 95% CI, 1.06-1.86), the need for vasopressors (OR 2.08; 95% CI, 1.32-3.28), and emergency total colectomy (OR 2.56; 95% CI, 1.12-5.87). Additional significant predictors of mortality at admission were increasing comorbidity burden (for each 1-unit increase: OR 1.13; 95% CI, 1.05-1.22) and lower systolic blood pressures (for each 1-mm Hg increase: OR .99; 95% CI, .98-1.00). In an analysis of a subgroup of patients who did not have initial tachycardia or hypotension when presenting to the emergency department, those with undetectable admission eosinophil counts, but not those with elevated white blood cell count, had significantly increased odds of inpatient mortality (OR 5.76; 95% CI, 1.99-16.64).
Several important study limitations were addressed by investigators. While the use of training and validation cohorts as well as the consistency of the data between 2 institutions suggests the data are generalizable, this may not be the case given potential strain difference may be affecting outcomes. Investigators also note that retrospective studies may introduce selection bias and that “prospective studies will be necessary to show that the information provided by our model would lead to improved outcomes in patients with C difficile infection as well as to answer questions regarding whether eosinopenia, or recovery of a detectable eosinophil count, at time points after admission are predictive of disease outcomes.” In addition, while there is an observed association between absence of peripheral eosinophils and increased virulence of C difficile, further work is needed to clarify the mechanism behind the association.
Research using these data is continuing and is presently underway. This further research will evaluate the prognostic value of eosinopenia and address whether improved prognostication at time of admission can guide treatment decisions and decrease mortality.
Kulaylat AS, Buonomo EL, Scully KW, et al. Development and validation of a prediction model for mortality and adverse outcomes among patients with peripheral eosinopenia on admission for Clostridium difficile infection [published online September 12, 2018]. JAMA Surg. doi: 10.1001/jamasurg.2018.3174