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.
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.
Authors: Daniel D Rhoads; Blaine A Mathison; Henry S Bishop; Alexandre J da Silva; Liron Pantanowitz Journal: Arch Pathol Lab Med Date: 2015-08-28 Impact factor: 5.534
Authors: Isaac E Hall; Steven G Coca; Mark A Perazella; Umo U Eko; Randy L Luciano; Patricia R Peter; Won K Han; Chirag R Parikh Journal: Clin J Am Soc Nephrol Date: 2011-10-27 Impact factor: 8.237
Authors: Mark A Perazella; Steven G Coca; Isaac E Hall; Umo Iyanam; Madiha Koraishy; Chirag R Parikh Journal: Clin J Am Soc Nephrol Date: 2010-01-14 Impact factor: 8.237
Authors: Dimard E Foudraine; Martijn P Bauer; Anne Russcher; Elske Kusters; Christa M Cobbaert; Martha T van der Beek; Janneke E Stalenhoef Journal: J Clin Microbiol Date: 2018-05-25 Impact factor: 5.948