Identification of population at risk for future Clostridium difficile infection following hospital discharge to be targeted for vaccine trials

Abstract

Background: Efforts to develop a Clostridium difficile vaccine are underway; identification of patients at risk for C. difficile infection (CDI) is critical to inform vaccine trials. We identified groups at high risk of CDI ≥ 2 8 days after hospital discharge.

Methods: Hospital discharge data and pharmacy data from two large academic centers, in New York and Connecticut, were linked to active population-based CDI surveillance data from the Emerging Infections Program (EIP). Adult residents of the EIP surveillance area were included if they had an inpatient stay at a study hospital without prior history of CDI. The primary outcome was CDI by either toxin or molecular assay ≥ 28 days after an index hospitalization. Important predictors of CDI ≥ 28 days post discharge were initially identified through a Cox proportional hazards model (stepwise backward selection) using a derivation cohort; final model parameters were used to develop a risk score evaluated in the validation cohort.

Results: Of the 35,186 index hospitalizations, 288 (0.82%) had CDI ≥ 28 days post discharge. After parameter selection, age, number of hospitalizations in the prior 90 days, admission diagnosis, and the use of 3rd/4th generation cephalosporin, clindamycin or fluoroquinolone antibiotic classes remained in the model. Using the validation cohort, the risk score was predictive (p<0.001) with a c-score of 0.75. Based on the distribution of scores in the derivation cohort, we divided the patients into low and high risk groups. In the high risk group, 1.6% experienced CDI ≥ 28 days post discharge compared to 0.3% among our low risk group.

Conclusions: Our study identified specific parameters for a risk score that can be applied at discharge to identify a patient population whose risk of CDI ≥ 28 days following an acute care hospitalization was 5 times greater than other patients.

Keywords: Administrative data; Anti-bacterial agents; Clostridium difficile infection; Health care-associated infections; Vaccines.

Figure 1

In order to determine the feasibility of a vaccine trial, we estimated the required sample size and proportion of patients at high risk available to be included in a vaccine trial for a range of risk scores based on the final risk score developed in our model. For our example, we assumed a hospital with 20,000 annual patient index visits, and a vaccine efficacy of 50%, and we then plotted the necessary sample size and the estimated number at high risk for each risk score. For risk index scores up to 7, the number expected to be at high risk was greater than the estimated sample size.