Detection of Significant Bacteriuria by Use of the iQ200 Automated Urine Microscope

Abstract

cIn the microbiology laboratory, there is an augmented need for rapid screening methods for the detection of bacteria in urine samples, since about two-thirds of these samples will not yield any bacteria or will yield insignificant growth when cultured. Thus, a reliable screening method can free up laboratory resources and can speed up the reporting of a negative urine result. In this study, we have evaluated the detection of leukocytes, bacteria, and a new sediment indicator, the "all small particles" (ASP), by an automated instrument, the iQ200 urine analyzer, to detect negative urine samples that can be excluded from culture. A coupled automated strip reader (iChem Velocity), enabling the detection of nitrite and leukocyte esterase, was tested in parallel. In total, 963 urine samples were processed through both conventional urine culture and the iQ200/iChem Velocity workstation. Using the data, a multivariate regression model was established, and the predicted specificity and the possible reduction in urine cultures were calculated for the indicators and their respective combinations (leukocytes plus bacteria plus ASP and leukocyte esterase plus nitrite). Among all options, diagnostic performance was best using the whole microscopic content of the sample (leukocytes plus bacteria plus ASP). By using a cutoff value of >10 4 CFU/ml for defining a positive culture, a given sensitivity of 95% resulted in a specificity of 61% and a reduction in urine cultures of 35%. By considering the indicators alone, specificity and the culture savings were both much less satisfactory. The regression model was also used to determine possible cutoff values for running the instrument as part of daily routine. By using a graphical representation of all combinations possible, we derived cutoff values for leukocyte, bacterial, and ASP count, which should enable the iQ200 microscope to screen out approximately one-third of the urine samples, significantly reducing the workload in the microbiology laboratory.

Interlaboratory Collaboration for Optimized Screening for Urinary Tract Infection

“…Negative predictive values are dependent on the prevalence of UTI in the study population (24.8% in our study), and the prevalence is very much dependent on the study population and the definition of a positive culture as has been illustrated by previous studies (7,10,13). Considering this, our results are quite comparable to those of previous studies, although our patient population differs.…”

“…Earlier studies show promising results with regard to the reduction of culture workload when automated urinalysis systems are used for screening before culturing (1,(5)(6)(7)(8)(9)(10). However, the results vary depending on the proportion of negative cultures in the laboratory and are, to a large extent, influenced by the patient population from which the laboratory receives its specimens.…”

L’automatisation en bactériologie: c’est maintenant !

“…D'autres automates, de découverte plus tardive (Iris® IQ200, Sysmex® UF500/1000, Urised®)(www.beckmancoulter.com/, www.biomerieux.fr/, www.i2a-diagnostics.fr), permettent une cytologie urinaire basée soit sur l'analyse d'images, soit sur la cytométrie en flux (Stürenburg, 2014 ;Inigo, 2016). L'examen cyto-bactériologique des urines est, en effet, un examen tellement banal en médecine qu'il nécessite l'automation, car souvent négatif.…”

Diagnosis of Urinary Tract Infections in Children

“…However, the difference between the commonly employed thresholds for significant bacteriuria in adults compared to children, i.e., Ն10 5 CFU/ml versus Ն50 ϫ 10 4 CFU/ml or lower, respectively, means that the available technologies must be evaluated for children at a lower threshold. Currently available systems use flow cytometry followed by fluorescent staining or digital imagery analysis for recognition of bacteria, WBCs, red blood cells (RBCs), and other particles (18,19). Most published studies to date are in predominantly adult populations, and some have reported good negative predictive values for the diagnosis of UTI.…”

“…Two of these studies used the Iris iQ200 Elite or Iris iQ Elite systems (digital imagery followed by Auto-Particle Recognition software analysis; Iris Diagnostics) (19,20). In the study by Shah et al (20), automated urinalysis (UA) for pyuria and bacteriuria was compared to "enhanced UA" (Ն10 WBCs/mm 3 and any bacteria per 10 oil immersion fields on Gram stain) using a threshold of Ն5 ϫ 10 4 CFU/ml of a single uropathogen as a positive urine culture (20).…”