Microbiological Diagnosis Algorithm for Chronic Lung Infection in Patients with Cystic Fibrosis

Clinical Microbiology and Antimicrobial Chemotherapy. 2014; 16(4):312-324

Journal article


The objective of this study was to develop algorithm of microbiological diagnosis for chronic lung infection in patients with cystic fibrosis and implement it for monitoring of chronic infection in children and adults. Data from our own studies performed during the 2008—2013 and published data were used in the algorithm development. A total of 251 children and 26 adults with cystic fibrosis were examined over the two years. Pathogen identification was performed by culture, biochemical, and DNA-based methods. Microorganisms associations were found to be responsible for ⅔ cases of infection. The most prevalent pathogens in patients with severe course of the disease were the following: Pseudomonas aeruginosa (30.5%), Burkholderia cepacia complex (28.7%), Staphylococcus aureus (53.3%), Achromobacter xylosoxidans (19%), and Candida spp. (57.5%). Microbiological monitoring (at intervals of 3 months to 4 years) using this algorithm in 24 children with cystic fibrosis revealed chronic infection due to Burkholderia cepacia complex (18 patients), A. xylosoxidans (6 patients), P. aeruginosa (5 patients), and S. aureus (7 patients).

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