Evaluation of the IRIS 939 UDx flow microscope as a screening system for urinary tract infection

Validation and verification of automated urine particle analysers

There is often uncertainty on how validation and verification of newly introduced tests should be conducted, and there is a real risk of verification becoming a meaningless ritual, rather than a useful exercise. This article reviews the literature and makes recommendations regarding the validation and verification of automated urine particles analysers. A generic practical approach to verification is also recommended. For many analysers, the accuracy of white blood cells, epithelial cells and bacterial counts is corroborated by a number of independent evaluations; thus, any verification laboratory work could be significantly scaled down. Conversely, in the scenario that automated urine microscopy is used as a screening test to reduce the number of urines cultured, the extremely variable performance reported in the literature requires a full-scale verification to define the optimal cut-off values that give a sensitivity of >98% with the local settings and circumstances. With some analysers, the risk of carry-over also needs to be assessed, as part of the verification process, and exclusion criteria (urines requiring culture regardless of the microscopy results) need to be well defined, as there are patients or specimen types for which the performance of microscopy as a screening test may not be adequate.

Can routine automated urinalysis reduce culture requests?

OBJECTIVES

There are a substantial number of unnecessary urine culture requests. We aimed to investigate whether urine dipstick and microscopy results could accurately rule out urinary tract infection (UTI) without urine culture.

DESIGN AND METHODS

The study included a total of 32,998 patients (11,928 men and 21,070 women, mean age: 39 ± 32 years) with a preliminary diagnosis of UTI and both urinalysis and urinary culture were requested. All urine cultures were retrospectively reviewed; association of culture positivity with a positive urinalysis result for leukocyte esterase (LE) and nitrite in chemical analysis and pyuria (WBC) and bacteriuria in microscopy was determined. Diagnostic performance of urinalysis parameters for detection of UTI was evaluated.

RESULTS

In total, 758 (2.3%) patients were positive by urine culture. Out of these culture positive samples, ratios of positive dipstick results for LE and nitrite were 71.0% (n=538) and 17.7% (n=134), respectively. The positive microscopy results for WBC and bacteria were 68.2% (n=517) and 78.8% (n=597), respectively. Negative predictive values for LE, nitrite, bacteriuria and WBC were very close to 100%.

CONCLUSIONS

Most of the samples have no or insignificant bacterial growth. Urine dipstick and microscopy can accurately rule out UTI. Automated urinalysis is a practicable and faster screening test which may prevent unnecessary culture requests for majority of patients.

Bacteriuria screening by automated whole-field-image-based microscopy reduces the number of necessary urine cultures

We evaluated a new automated urine sediment analyzer that provides whole-field images for the screening of urine samples prior to bacterial culture. Sterile urine samples from 1,011 male and female outpatients and inpatients (mean age 54.7) with a urinary tract infection prevalence of 18.3% were studied. Screening rapidly provides negative results.

Development of a score based on urinalysis to improve the management of urinary tract infection in children

BACKGROUND

The need for reducing unnecessary antibiotic treatment is being emphasized in the management of urinary tract infections (UTI), a disease frequent in childhood. An ideal test should provide early diagnosis without the waiting times of urine culture, but even a simple test of exclusion could significantly improve patient management.

METHODS

We evaluated the sensitivity, specificity, negative and positive predictive value of automated microscopy IRIS iQ200 combined with the dipstick analyses in children with suspected UTI. Multivariable logistic regression analysis was used to identify the set of variables that best predict positive culture results and develop a numerical risk score.

RESULTS

Of 474 consecutive urine samples retrospectively analyzed, 69 were positive at urine culture with prevalence of infection of 14.6%. Parameters significantly associated with the presence of infection in multivariable analysis were age <1 year (p<0.001), leukocyte esterase ≥ 15×10^6/L (p<0.001), number of small particles (ASP) ≥ 5500 × 10^6/L (p<0.001) and bacteria ≥ 3 × 10^6/L (p=0.01). The derived score ranged from 0 to 10, with higher values indicating higher risk of UTI. The area under the score ROC curve was 79% (95% CI 0.72-0.85), and was better than those of the individual urinary chemical and microscopic analyses.

CONCLUSIONS

This routine method could improve the management of UTI in children by early identifying patients with low probability of infection, for whom antibiotic treatment can be withheld until the results of urine culture become available.

Automated urinalysis: first experiences and a comparison between the Iris iQ200 urine microscopy system, the Sysmex UF-100 flow cytometer and manual microscopic particle counting

BACKGROUND

Automated analysis of insoluble urine components can reduce the workload of conventional microscopic examination of urine sediment and is possibly helpful for standardization. We compared the diagnostic performance of two automated urine sediment analyzers and combined dipstick/automated urine analysis with that of the traditional dipstick/microscopy algorithm.

METHODS

A total of 332 specimens were collected and analyzed for insoluble urine components by microscopy and automated analyzers, namely the Iris iQ200 (Iris Diagnostics) and the UF-100 flow cytometer (Sysmex).

RESULTS

The coefficients of variation for day-to-day quality control of the iQ200 and UF-100 analyzers were 6.5% and 5.5%, respectively, for red blood cells. We reached accuracy ranging from 68% (bacteria) to 97% (yeast) for the iQ200 and from 42% (bacteria) to 93% (yeast) for the UF-100. The combination of dipstick and automated urine sediment analysis increased the sensitivity of screening to approximately 98%.

CONCLUSIONS

We conclude that automated urine sediment analysis is sufficiently precise and improves the workflow in a routine laboratory. In addition, it allows sediment analysis of all urine samples and thereby helps to detect pathological samples that would have been missed in the conventional two-step procedure according to the European guidelines. Although it is not a substitute for microscopic sediment examination, it can, when combined with dipstick testing, reduce the number of specimens submitted to microscopy. Visual microscopy is still required for some samples, namely, dysmorphic erythrocytes, yeasts, Trichomonas, oval fat bodies, differentiation of casts and certain crystals.

Urine sediment examination: A comparison between the manual method and the iQ200 automated urine microscopy analyzer

BACKGROUND

Microscopic examination of the urine sediment is an essential part in the evaluation of renal and urinary tract diseases. Traditionally, manual microscopic techniques have several methodological steps that may contribute to imprecision, inaccuracy, and are time-consuming. Recently, the iQ200 automated urine microscopy analyzer has been introduced to analyze the unspun urine, thereby improving accuracy, precision and throughput.

METHODS

In this study, we compared its performance with manual routine slide and chamber counts. Fresh urine samples were obtained from 400 subjects.

RESULTS

The reference values of white blood cells, red blood cells and squamous epithelial cells obtained by the above methods were not significant difference when the results reported as cells per high-power field. For the specimens of patients (n=280), a significant correlation was found when the iQ200 results of cellular elements were compared with those obtained from manual microscopy. No significant difference was found when the post-review results of the iQ200 were compared with the chamber count. However, the presence of casts, crystals, bacteria, and budding yeast needs further characterization under the microscope.

CONCLUSIONS

There is substantial agreement between the iQ200 and manual microscopic methods. The iQ200 provides for a rapid turnaround time.