OBJECTIVE: To evaluate, in a prospective pilot study, the feasibility of identifying pathogens in urine using real-time polymerase chain reaction (PCR), and to compare the results with the conventional urine culture-based procedures. PATIENTS AND METHODS: Severe urinary tract infections (UTIs) are frequent in critically ill patients in the intensive-care unit (ICU) and in outpatients, and thus the reliable and fast identification of the bacteria is mandatory, but routine urine culture is time-consuming and the therapeutic regimen is often calculated and not culture-based. The study included 301 prospectively collected urine samples from 189 patients with suspected UTI, based in a university hospital in 2005, and included outpatients and those in the ICU. Urine culture with Cled-, MacConkey- and malt extract agar of all samples was followed by microbiological identification of the pathogens in 98 samples with visible growth. In parallel, all samples were assessed using qualitative real-time PCR-based DNA detection and identification by labelled hybridization probes. RESULTS: In all, 15 dipstick culture-negative samples showed positive pathogen DNA identification by PCR. By contrast, 17 PCR-negative samples showed detectable pathogens by culture, of which 10 were not detectable on PCR because the identified pathogens were not represented in the probe panel. The sensitivity and specificity for detecting contaminated samples was 0.90 and 0.87, respectively. Overall, 95% of the mono-infection pathogens and 57% of the multiple-infection pathogens were detected concordantly with both methods. CONCLUSION: In this prospective pilot study PCR-based identification of pathogens was feasible for supplementing conventional culture methods for the diagnosis of UTI. The main advantage is the time saved in identifying the pathogens. The limited pathogen detection in multiple-infection-samples by PCR might be explained by competitive PCR amplification conditions.
OBJECTIVE: To evaluate, in a prospective pilot study, the feasibility of identifying pathogens in urine using real-time polymerase chain reaction (PCR), and to compare the results with the conventional urine culture-based procedures. PATIENTS AND METHODS: Severe urinary tract infections (UTIs) are frequent in critically illpatients in the intensive-care unit (ICU) and in outpatients, and thus the reliable and fast identification of the bacteria is mandatory, but routine urine culture is time-consuming and the therapeutic regimen is often calculated and not culture-based. The study included 301 prospectively collected urine samples from 189 patients with suspected UTI, based in a university hospital in 2005, and included outpatients and those in the ICU. Urine culture with Cled-, MacConkey- and malt extract agar of all samples was followed by microbiological identification of the pathogens in 98 samples with visible growth. In parallel, all samples were assessed using qualitative real-time PCR-based DNA detection and identification by labelled hybridization probes. RESULTS: In all, 15 dipstick culture-negative samples showed positive pathogen DNA identification by PCR. By contrast, 17 PCR-negative samples showed detectable pathogens by culture, of which 10 were not detectable on PCR because the identified pathogens were not represented in the probe panel. The sensitivity and specificity for detecting contaminated samples was 0.90 and 0.87, respectively. Overall, 95% of the mono-infection pathogens and 57% of the multiple-infection pathogens were detected concordantly with both methods. CONCLUSION: In this prospective pilot study PCR-based identification of pathogens was feasible for supplementing conventional culture methods for the diagnosis of UTI. The main advantage is the time saved in identifying the pathogens. The limited pathogen detection in multiple-infection-samples by PCR might be explained by competitive PCR amplification conditions.
Authors: Ann E Stapleton; Marsha E Cox; Robert K DiNello; Mark Geisberg; April Abbott; Pacita L Roberts; Thomas M Hooton Journal: J Clin Microbiol Date: 2015-06-10 Impact factor: 5.948
Authors: Tom J Blodgett; Sue E Gardner; Nicole P Blodgett; Lisa V Peterson; Melissa Pietraszak Journal: Clin Nurs Res Date: 2014-09-22 Impact factor: 2.075
Authors: Wendy L J Hansen; Christina F M van der Donk; Cathrien A Bruggeman; Ellen E Stobberingh; Petra F G Wolffs Journal: PLoS One Date: 2013-04-23 Impact factor: 3.240
Authors: Lutz E Lehmann; Stefan Hauser; Thomas Malinka; Sven Klaschik; Stefan U Weber; Jens-Christian Schewe; Frank Stüber; Malte Book Journal: PLoS One Date: 2011-02-16 Impact factor: 3.240