Application of PCT, CRP and white blood cell count for the rapid diagnosis of Clostridium difficile in patients with IBD

Abstract Background The incidence of Clostridium difficile infection (CDI) has increased in recent years in patients with inflammatory bowel disease (IBD). C. difficile is a toxin-producing bacterium, and CDI results in the worsening of the underlying IBD, increasing the risks of IBD treatment failure, surgery and hospitalization. Since the symptoms of CDI overlap with those of IBD, it is challenging to make a differential diagnosis. Therefore, early, rapid and reliable diagnostic tools that can identify CDI in IBD patients would be valuable to clinicians. Methods This study enrolled 135 patients with IBD. Among them, 44 patients were diagnosed with CDI, and 42 patients were diagnosed with viral or fungal infections; 49 patients without infections were enrolled in the control group. The diagnostic values of procalcitonin (PCT), C-reactive protein (CRP) and the white blood cell count (WBC) in the peripheral blood were examined. A receiver operating characteristic (ROC) curve was used to analyse the diagnostic value of these parameters. Results In this study, the PCT and CRP levels were significantly higher in patients with CDI than in non-CDI patients (including patients with viral/fungal infections and the control group; p < 0.001 and p < 0.05, respectively). In the ROC curve analysis of the IBD-CDI group and the control group, PCT and CRP predicted IBD-CDI with an area under the curve (AUC) of 0.826 [95% confidence interval (CI) 0.743–0.909, p = 0.000] and 0.663 [95% confidence interval (CI) 0.551–0.774, p = 0.007], respectively. The WBC count was inferior as diagnostic tool for CDI. The sensitivity was 56.82% (95% CI: 41.03–71.65%), the specificity was 91.84% (95% CI: 80.40–97.73%), and the LR (+) was 6.96 for PCT for the diagnosis of CDI. Conclusions The present study demonstrated the superiority of PCT over CRP and the WBC for the rapid diagnosis of CDI in IBD patients. Additionally, PCT can be used to predict the clinical outcomes.