Objectives: To identify characteristics associated with particular groups of uropathogens in catheter-associated urinary tract infection (CA-UTI) and to develop clinical prediction rules for identifying these groups.
Methods: Demographic, clinical and microbiological data were analysed from patients with CA-UTI. Infections were categorized into enteric Gram-negative rods, nonfermenters, Gram-positive cocci and fungal. Variables were analysed using univariate and multiple logistic regression analyses, and were used to develop clinical prediction rules.
Results: A total of 492 patients were included in the study. Candida species were the most common uropathogens (30.7%), followed by enterococci (17.3%), Escherichia coli (12.0%), Pseudomonas spp. (10.8%), Klebsiella spp. (7.9%) and staphylococci (6.5%). Clinical prediction rules for the bacterial uropathogenic groups showed poor-to-fair discriminatory power, with sensitivities of <40% and specificities of >90%. However, clinical prediction rules showed good discriminatory power for fungal infections, with a sensitivity of 67.3% and a specificity of 78.1%.
Conclusions: Clinical prediction rules developed for identifying specific groups of bacterial uropathogens in patients with CA-UTI had a low sensitivity, whereas those for fungal infections showed good discriminatory power. Further studies to develop more refined and sensitive tools for predicting specific bacterial uropathogens in CA-UTI are warranted.
Keywords: Catheter-associated urinary tract infection; aetiology; prediction model; risk factor; sensitivity; urinary catheterization.
© The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.