In the microbiology laboratory, there is an augmented need for rapid screening methods for the detection of bacteria in urines since about two thirds of these samples will not yield any bacteria or 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 leucocytes, bacteria, and a new sediment indicator, the 'all small particles' (ASP), by an automated instrument, the iQ200 urine analyser, to detect negative urine samples that can be excluded from being cultured. A coupled automated strip reader (iChem Velocity), enabling the detection of nitrite and leucocyte esterase, was tested in parallel. In total, 963 urine samples were processed through both, conventional urine culture and the iQ200 / iChem Velocity work station. Using the data, a multivariate regression model was established and for the indicators and their respective combinations (leucocytes + bacteria + ASP; leucocyte esterase + nitrite) the predicted percentage of specificity and the possible reduction in urine cultures were calculated. Among all options, diagnostic performance was best using the whole microscopic content of the sample (leucocytes + bacteria + ASP). By using a cut-off 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 cut-off values for running the instrument in daily routine. By using a graphical representation of all combinations possible, we derived cut-off values for leukocytes, bacteria and the 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.
