Design and Validation of a Protocol that Speeds Up the Diagnosis of Urinary Tract Infections

 A study led by Dr. Jordi Vila, director of the Antibiotic Resistance Inititiative at ISGlobal, shows that is it possible to accelerate the diagnosis of urinary infections by applying two techniques directly on urine samples. The results, published in Clinical Microbiology and Infection, will permit an earlier and more adequate treatment of the patient.

Urinary tract infections are the second most common cause of infection and a common cause of sepsis. In order to initiate treatment, urine cultures, that take 18-48 hours, must be performed, followed by a susceptibility test that takes an additional 24 hours. Therefore, a rapid urine sample processing would greatly improve the management of patients, particularly those with sepsis.    

The aim of the study was to develop a protocol to shorten the bacteriological identification and susceptibility testing times. To do so, the researchers used flow cytometry to identify those samples with sufficient bacterial concentration, followed by a mass spectrometry technique (MALDI-TOF-MS) for bacterial identification and a “disc-diffusion” test to determine antibiotic susceptibility directly from the urine.  

The results show that MALDI-TOF-MS correctly identified all those samples with one single type of bacteria, in less than one hour. In addition, it allowed the direct detection of Clostridium perfringes, an anaerobic bacterium that does not grow in standard culture conditions. The direct susceptibility test was also concordant in the case of monomicrobial infections and, overall, the sample processing time was shortened by 48h. 

Although the procedure requires dedicated personnel, the authors conclude that it represents a valuable tool that can be reserved for patients with severe and/or complicated infections.

Reference

Zboromyrska Y, Rubio E, Alejo I, et. al. Development of a new protocol for rapid bacterial identification and susceptibility testing directly from urine samples. Clin Microbiol Infect. 2016 Feb 16. pii: S1198-743X(16)00105-1