BACKGROUND: Carbapenemase-producing Enterobacteriaceae (CPE) have become a major public health issue. The objective of the present study was to prospectively assess the analytical performance of a CPE detection algorithm based on phenotypic tests (the screening test) and MALDI-ToF hydrolysis (the confirmatory test). METHODS: Over a 6-month period and based on a disk diffusion method, 74 carbapenem-resistant strains were included in this study. RESULTS: Of the collected isolates, 54 turned out to be negative after phenotypic tests. Hence, 20 strains (including all of the CPEs) were checked with the confirmation test. Seven strains were positive. After molecular biology assessments in a reference center, three of the seven were found to be false positives. The algorithm had a negative predictive value and a sensitivity of 100%, a specificity of 77%, and a positive predictive value of 20%. CONCLUSION: The algorithm has a 24-hour turnaround time and helps to avoid using expensive molecular biology tests; we consider that it can be used on a routine basis for screening clinical strains.
BACKGROUND: Carbapenemase-producing Enterobacteriaceae (CPE) have become a major public health issue. The objective of the present study was to prospectively assess the analytical performance of a CPE detection algorithm based on phenotypic tests (the screening test) and MALDI-ToF hydrolysis (the confirmatory test). METHODS: Over a 6-month period and based on a disk diffusion method, 74 carbapenem-resistant strains were included in this study. RESULTS: Of the collected isolates, 54 turned out to be negative after phenotypic tests. Hence, 20 strains (including all of the CPEs) were checked with the confirmation test. Seven strains were positive. After molecular biology assessments in a reference center, three of the seven were found to be false positives. The algorithm had a negative predictive value and a sensitivity of 100%, a specificity of 77%, and a positive predictive value of 20%. CONCLUSION: The algorithm has a 24-hour turnaround time and helps to avoid using expensive molecular biology tests; we consider that it can be used on a routine basis for screening clinical strains.
Authors: Silke Polsfuss; Guido V Bloemberg; Jacqueline Giger; Vera Meyer; Erik C Böttger; Michael Hombach Journal: J Clin Microbiol Date: 2011-06-01 Impact factor: 5.948
Authors: V Miriagou; G Cornaglia; M Edelstein; I Galani; C G Giske; M Gniadkowski; E Malamou-Lada; L Martinez-Martinez; F Navarro; P Nordmann; L Peixe; S Pournaras; G M Rossolini; A Tsakris; A Vatopoulos; R Cantón Journal: Clin Microbiol Infect Date: 2010-02 Impact factor: 8.067
Authors: M Choquet; R Guiheneuf; S Castelain; V Cattoir; M Auzou; E Pluquet; V Decroix Journal: Eur J Clin Microbiol Infect Dis Date: 2017-10-04 Impact factor: 3.267