Abstract

Introduction: Clostridium difficile infection (CDI) has emerged as a major healthcare-associated infection. The incidence of this infection, related hospitalizations and mortality rates seem to be increasing every year. Certain established risk factors and comorbid conditions are thought to have a prognostic impact on the outcomes of patients with CDI. We studied the significance of Charlson Comorbidity Index (CCI) as an independent tool to predict the outcomes in these patients. Methods: We conducted a retrospective observational study at our institution between July 1st, 2014 and June 30th, 2017. We included all individual admitted to our institution whose stool tested positive for Glutamate Dehydrogenase (GDH) and was confirmed by Nucleic Acid Amplification Test (NAAT). Demographic, clinical, laboratory and pharmacological data was abstracted from our EHR (Electronic Health Records). The data was analyzed using standard statistical methods and JMP14 software. We divided patients into two groups based on in-hospital mortality. Results: In our study we included a total of 314 individual who met the inclusion criteria. We observed no difference in the outcomes of the patients based on their gender. The mean age of patients who died was 64.5 years while the mean age of those who survived was 57.5 (p value = 0.016). Furthermore, the mean CCI of the patients who died was 7.37 while of those who survived was 4.4 (p value = 0.0001 ) (Table 1).We also compared the Charlson Comorbidity Index(CCI) in mild-moderate, severe and complicated CDI which corresponded with disease severity (6.20, 5.70 and 4.06 respectively (p value = Conclusion: Current CDI outcome prediction models are based on disease severity. Our study sheds light into a new area of CCI and mortality in individuals with CDI. We observed known risk factors like age, severity of disease correlated with mortality. However, we noticed higher CCI score in relation to mortality during hospitalization. As CCI is a quick and readily available tool, we hope this finding will help healthcare professionals to predict outcomes in patients with CDI to manage them more efficiently for better outcomes.2743 Figure 1 No Caption available.

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