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Background: In analogy with other areas of laboratory diagnostics, the pre-analytical phase is the leading source of variability also in urinalysis. We carried out a multicentric study for comparing results obtained from first-voided and mid-stream urine samples. Methods: Each of the six hospital-based clinical laboratories participating to this study recruited 50 healthy subjects among laboratory staff and/or their relatives. Two consecutive samples of the first morning micturition were collected by vacuum system, the first from the first-void and the second from the mid-stream. Routine urinalysis was performed using dip-stick automated analyzers for chemical examination and automated analyzers for formed particle examination (Sysmex UF-100, Sysmex UF-1000i and Iris iQ-200). Results: Counts of epithelial cells (EC), erythrocytes (ERY) and leukocytes (LEU) but not for cylinders (CAS) were significantly higher in the first-voided samples. A significantly higher count of EC, ERY and LEU was also observed between females and males in first-voided samples, whereas no significant difference could be found in mid-stream samples. Health related analyzer specific upper reference limits (URL) were CAS≤1, EC≤5, ERY≤19, Leu≤13 for UF-100; CAS≤1, EC≤4, ERY≤15, Leu≤11 for UF-1000i; CAS≤1, EC≤4, ERY≤18, Leu≤10 for iQ200. The overall prevalence of subjects with cellular elements count exceeding URL was also higher in first-voided than in mid-stream samples. Conclusions: Mid-stream urine was confirmed as the most appropriate sample, since the presence of contaminating elements, such as bacteria, analytes and formed particles are minimized. [ABSTRACT FROM AUTHOR]

Background: The study of urine particles plays a key role in the diagnosis of kidney diseases. In this study, the authors evaluated the correlation between the UF-1000 i and quantitative manual microscopy. Methods: A total of 214 untreated urine samples were studied using the Sysmex UF-1000 i and compared with results obtained from quantitative manual microscopy using the Fuchs-Rosenthal counting chamber. Results: Using Pearson statistics, we observed satisfactory correlation between the UF-1000 i and quantitative microscopy: for red blood cells (RBCs) r was 0.98, for white blood cells (WBCs) r was 1.00, for epithelial cells (EC) r was 0.96, and for casts r was 0.69. Using linear regression statistics, we also observed satisfactory correlation between the UF-1000 i and quantitative microscopy: for RBCs R2 was 0.95, for WBCs R2 was 0.99, for EC R2 was 0.92, and for casts R2 was 0.48. Conclusions: In our experience, automated urine particle analysis performed using the Sysmex UF-1000 i analyzer is sufficiently precise and improves the workflow in a routine laboratory. Precision was satisfactory and concordance with the reference method is good for RBC, WBC and EC; for casts microscopic observation is required for flagged samples to discriminate hyaline from pathologic casts. Clin Chem Lab Med 2010;48:1107–11. [ABSTRACT FROM AUTHOR]

In spite of the introduction of automated systems for urinary sediment analysis, microscopy examination remains the gold standard, and it is more than ever important to perform it with a good and reliable quality. External Quality Assessment (EQA) programs on urinary sediment are rare. The present paper provides an analysis of results from 2001 to date of the EQA Italian program which involves today 230 laboratories. The program includes four surveys per year. Participants are asked the identification and clinical associations of urinary sediment particles, shown as phase contrast microscopy images in the website of the Center of Biomedical Research (CRB) (2 surveys), and the diagnosis of clinical cases presented by both images and a short clinical history (2 surveys). The results of each survey are then scored and commented. In 20 years, 298 images were presented: 90 cells (9 types), 23 lipids (5 types), 87 casts (21 types), 53 crystals (14 types), 22 microorganisms (5 types), and 23 contaminants (9 types). Moreover, 27 clinical cases, covering a wide spectrum of conditions with different degrees of complexity, were presented to participants. Identification: among urinary particle categories, the correct identification rate (obtained for each particle from the sum of correct + partially correct answers) was very high for micro-organisms (mean ± SD: 96.2 ± 3.5%), high for lipids (88.0 ± 11.8%) and crystals (87.0 ± 16.5%) followed, in decreasing order, by cells (82.1 ± 15.9%), casts (81.8 ± 14.8%), and contaminants (76.7 ± 22.1%). Clinical associations (n=67): the rate of correct answers was 93.5 ± 5.7% ranging from 75.0 to 100% for all but one clinical association (i.e., acute glomerulonephritis: 55.4%). Clinical cases: throughout surveys, due to the overall rate of particle misidentification, only 59.8 ± 17.1%, (range 32.5–88.7%) of participants achieved access to clinical diagnosis. Of these, 88.7 ± 10.6% (range 59.9–99.3%) were able to indicate the correct diagnosis. Our program can be used as a tool to improve the identification of urine particles and the knowledge of their clinical meaning and to encourage specialists of laboratory medicine to correlate urinary findings with other laboratory data and the clinical history, an aspect that improves the value of the day by day work. [ABSTRACT FROM AUTHOR]

Background: Manual microscopy still represents the gold standard for urinary sediment (US) examination. We report the results obtained in the period 2012-2015 by the EQA Italian program on US, which today involves about 260 laboratories. Methods: The program includes four surveys per year. In two surveys, participants are asked to supply identification and clinical association of US particles. In two other surveys, they are asked to supply the diagnosis of clinical cases, presented with images, some key laboratory findings and a short clinical history. Sixty-six images of US particles (21 cells, 2 lipids, 21 casts, 10 crystals, 3 microorganisms, 15 contaminants) and seven clinical cases were presented. Results: The correct identification rate for each category of particles, in decreasing order, was: micro-organisms (mean±SD: 92.4%±4.5%), lipids (92.0%±1.8%), casts (82.8%±8.8%), crystals (79.4%±29.8%), cells (77.3%±13.5%), and contaminants (70.9%±22.2%). For 13 particles, a correct clinical association was indicated by 91.5%±11.7% of participants, while it was 52.7% for particles associated with urinary tract infection. For clinical cases, due to a high rate of particles misidentification, only 44.3%±10.1% of participants achieved access to clinical diagnosis, which was then correctly indicated by 92.5%±5.3% of them. Conclusions: The results of the EQA program confirm that, while some US particles are well known in terms of identification, clinical association and clinical meaning, others particles still are not, and this represents an important reason to encourage EQA programs on US. [ABSTRACT FROM AUTHOR]