ERADICATING PSEUDOMONAS PERSISTENCE IN ADULT PATIENTS WITH CYSTIC FIBROSIS WITH A NEW ALGORITHM OF ANTIBIOTIC SELECTION

TOPIC: Chest Infections TYPE: Original Investigations PURPOSE: Pseudomonas aeruginosa is a common pathogen, causing chronic and life-threatening infections in airways of patients with cystic fibrosis (CF). Multidrug-resistant P.aeruginosa (MDR-PA), an important cause persistent due to its ability form biofilms which display tolerance high resistance antimicrobial agents Traditional antibiotic selection tests take days fail select effective antibiotics against MDR-PA because not accounting for critical characteristics “real-life” infections. AtbFinder – novel culture-based test system addresses these realities by using principle selection, named “populational response”, has previously proved be highly selecting even MDR bacteria biofilms, delivering results 4 hours. Here we present findings from 3-y long microbiological monitoring persistence CF, that underwent treatment selected AtbFinder. METHODS: 30 CF aged between 18 63, confirmed infection, receiving prophylactic therapy based on were monitored over 2 years. Sputum was obtained during yearly check-up hospitalisations the presence assessed (i)AtbFinder or (ii) standard media. RESULTS: First analyzed effect eradication P.aeruginosa. By year 1 after switch use AtbFinder, noted 16 (53%) 22 (73%) out subjects who had infection respectively (p<0.001). We next studied how affected sputum load still having infection. The mean density following methods those baseline (year 0) decreased 3.2 4.1 log10 CFU/g at 2, respectively. Moreover able narrow-spectrum than 50% patients. CONCLUSIONS: Our represent first study evaluate performance account polymicrobial nature within routine diagnostic setting. Antibiotic optimization progressive CF. CLINICAL IMPLICATIONS: have demonstrated among more same ASTs. significantly improved clinical parameters, allowing reduction unnecessary broad-spectrum use. DISCLOSURES: No relevant relationships Christina Kardava, source=Web Response George Tetz, Victor Maria Vecherkovskaya,