BACKGROUND: Classic risk factors for candidemia include use of total parenteral nutrition (TPN), hospital location, use of central venous catheter, and others. Unfortunately, most of these variables are now also risk factors for antibiotic-resistant bacteria. Thus, use of these risk factors to identify patients at high risk for candidemia is difficult. The purpose of this study was to compare these classic risk factors for candidemia in patients with bloodstream infections to determine the relative strength of these predictors in differentiating patients with candidemia and bacteremia. METHODS: Clinical data were collected from the medical charts of patients who had been hospitalized between 2002 and 2004. Patients with their first episode of candidemia or bacteremia during their hospital stays were included. Risk factors were assessed using a multivariate logistic regression model and internally validated using a bootstrap analysis. A p-value < 0.05 was considered significant. RESULTS: A total of 164 patients (82 with candidemia) were evaluated. According to the logistic analysis, patients who had stayed in the intensive care unit (ICU) (OR = 6.24; 95% CI: 2.58-15.09) or had been using TPN (OR = 4.69; 95% CI: 1.76-12.48) were more likely to have candidemia than bacteremia. While patients with pulmonary (OR = 0.15; 95% CI: 0.055-0.39) or cardiac disease (OR = 0.21; 95% CI: 0.086-0.51) had a greater chance to have bacteremia than candidemia (p < 0.01 for all variables). These results were further validated using bootstrap analysis. CONCLUSION: Among classic risk factors for candidemia, the ICU location at the time of culture and TPN use were most predictive of candidemia while certain medical disorders predicted patients at the highest risk for bacteremia. These results can be used to help identify patients most likely to benefit from empiric antifungal therapy.
BACKGROUND: Classic risk factors for candidemia include use of total parenteral nutrition (TPN), hospital location, use of central venous catheter, and others. Unfortunately, most of these variables are now also risk factors for antibiotic-resistant bacteria. Thus, use of these risk factors to identify patients at high risk for candidemia is difficult. The purpose of this study was to compare these classic risk factors for candidemia in patients with bloodstream infections to determine the relative strength of these predictors in differentiating patients with candidemia and bacteremia. METHODS: Clinical data were collected from the medical charts of patients who had been hospitalized between 2002 and 2004. Patients with their first episode of candidemia or bacteremia during their hospital stays were included. Risk factors were assessed using a multivariate logistic regression model and internally validated using a bootstrap analysis. A p-value < 0.05 was considered significant. RESULTS: A total of 164 patients (82 with candidemia) were evaluated. According to the logistic analysis, patients who had stayed in the intensive care unit (ICU) (OR = 6.24; 95% CI: 2.58-15.09) or had been using TPN (OR = 4.69; 95% CI: 1.76-12.48) were more likely to have candidemia than bacteremia. While patients with pulmonary (OR = 0.15; 95% CI: 0.055-0.39) or cardiac disease (OR = 0.21; 95% CI: 0.086-0.51) had a greater chance to have bacteremia than candidemia (p < 0.01 for all variables). These results were further validated using bootstrap analysis. CONCLUSION: Among classic risk factors for candidemia, the ICU location at the time of culture and TPN use were most predictive of candidemia while certain medical disorders predicted patients at the highest risk for bacteremia. These results can be used to help identify patients most likely to benefit from empiric antifungal therapy.
Authors: Cheguevara Afaneh; Deborah Gerszberg; Eoin Slattery; David S Seres; John A Chabot; Michael D Kluger Journal: Hepatobiliary Surg Nutr Date: 2015-02 Impact factor: 7.293
Authors: Andrew F Shorr; Ying P Tabak; Richard S Johannes; Xiaowu Sun; James Spalding; Marin H Kollef Journal: Crit Care Date: 2009-09-29 Impact factor: 9.097