Comparison of five automated urine sediment analyzers with manual microscopy for accurate identification of urine sediment
Background While the introduction of automated urine analyzers is expected to reduce the labor involved, turnaround time and potential assay variations, microscopic examination remains the "gold standard" for the analysis of urine sediments. In this study, we evaluated the analytical and d...
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Veröffentlicht in: | Clinical chemistry and laboratory medicine 2019-10, Vol.57 (11), p.1744-1753 |
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description | Background While the introduction of automated urine analyzers is expected to reduce the labor involved, turnaround time and potential assay variations, microscopic examination remains the "gold standard" for the analysis of urine sediments. In this study, we evaluated the analytical and diagnostic performance of five recently introduced automated urine sediment analyzers. Methods A total of 1016 samples were examined using five automated urine sediment analyzers and manual microscopy. Concordance of results from each automated analyzer and manual microscopy were evaluated. In addition, image and microscopic review rates of each system were investigated. Results The proportional bias for red blood cells (RBCs), white blood cells (WBCs) and squamous epithelial cells in the automated urine sediment analyzers were within ±20% of values obtained using the manual microscope, except in the cases of RBCs and WBCs analyzed using URiSCAN PlusScope and Iris iQ200SPRINT, respectively. The sensitivities of Roche Cobas® u 701 and Siemens UAS800 for pathologic casts (73.6% and 81.1%, respectively) and crystals (62.2% and 49.5%, respectively) were high, along with high image review rates (24.6% and 25.2%, respectively). The detection rates for crystals, casts and review rates can be changed for the Sysmex UF-5000 platform according to cut-off thresholds. Conclusions Each automated urine sediment analyzer has certain distinct features, in addition to the common advantages of reducing the burden of manual processing. Therefore, laboratory physicians are encouraged to understand these features, and to utilize each system in appropriate ways, considering clinical algorithms and laboratory workflow. |
doi_str_mv | 10.1515/cclm-2019-0211 |
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In this study, we evaluated the analytical and diagnostic performance of five recently introduced automated urine sediment analyzers. Methods A total of 1016 samples were examined using five automated urine sediment analyzers and manual microscopy. Concordance of results from each automated analyzer and manual microscopy were evaluated. In addition, image and microscopic review rates of each system were investigated. Results The proportional bias for red blood cells (RBCs), white blood cells (WBCs) and squamous epithelial cells in the automated urine sediment analyzers were within ±20% of values obtained using the manual microscope, except in the cases of RBCs and WBCs analyzed using URiSCAN PlusScope and Iris iQ200SPRINT, respectively. The sensitivities of Roche Cobas® u 701 and Siemens UAS800 for pathologic casts (73.6% and 81.1%, respectively) and crystals (62.2% and 49.5%, respectively) were high, along with high image review rates (24.6% and 25.2%, respectively). The detection rates for crystals, casts and review rates can be changed for the Sysmex UF-5000 platform according to cut-off thresholds. Conclusions Each automated urine sediment analyzer has certain distinct features, in addition to the common advantages of reducing the burden of manual processing. Therefore, laboratory physicians are encouraged to understand these features, and to utilize each system in appropriate ways, considering clinical algorithms and laboratory workflow.</description><identifier>ISSN: 1434-6621</identifier><identifier>EISSN: 1437-4331</identifier><identifier>DOI: 10.1515/cclm-2019-0211</identifier><identifier>PMID: 31280239</identifier><language>eng</language><publisher>Germany: De Gruyter</publisher><subject>Algorithms ; Analyzers ; automated urine sediment analyzer ; Automation ; Biological Assay - methods ; Cobas ; Crystals ; Diagnostic systems ; Epithelial cells ; Erythrocytes ; Humans ; Image detection ; Iris iQ200SPRINT ; Leukocytes ; Medical laboratories ; Medical personnel ; Microscopy ; Microscopy - methods ; Physicians ; Sediments ; Sensitivity analysis ; u 701 ; UAS800 ; UF-5000 ; Urinalysis - methods ; Urine ; URiSCAN PlusScope ; Workflow</subject><ispartof>Clinical chemistry and laboratory medicine, 2019-10, Vol.57 (11), p.1744-1753</ispartof><rights>2019 Walter de Gruyter GmbH, Berlin/Boston</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c378t-d601dcdd8ded55b5dd29bf200cbff862038d0ba2cd619e8841d7559e0616b1b93</citedby><cites>FETCH-LOGICAL-c378t-d601dcdd8ded55b5dd29bf200cbff862038d0ba2cd619e8841d7559e0616b1b93</cites><orcidid>0000-0002-9628-2334</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.degruyter.com/document/doi/10.1515/cclm-2019-0211/pdf$$EPDF$$P50$$Gwalterdegruyter$$H</linktopdf><linktohtml>$$Uhttps://www.degruyter.com/document/doi/10.1515/cclm-2019-0211/html$$EHTML$$P50$$Gwalterdegruyter$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,66754,68538</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31280239$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Cho, Jooyoung</creatorcontrib><creatorcontrib>Oh, Kyeong Jin</creatorcontrib><creatorcontrib>Jeon, Beom Chan</creatorcontrib><creatorcontrib>Lee, Sang-Guk</creatorcontrib><creatorcontrib>Kim, Jeong-Ho</creatorcontrib><title>Comparison of five automated urine sediment analyzers with manual microscopy for accurate identification of urine sediment</title><title>Clinical chemistry and laboratory medicine</title><addtitle>Clin Chem Lab Med</addtitle><description>Background While the introduction of automated urine analyzers is expected to reduce the labor involved, turnaround time and potential assay variations, microscopic examination remains the "gold standard" for the analysis of urine sediments. In this study, we evaluated the analytical and diagnostic performance of five recently introduced automated urine sediment analyzers. Methods A total of 1016 samples were examined using five automated urine sediment analyzers and manual microscopy. Concordance of results from each automated analyzer and manual microscopy were evaluated. In addition, image and microscopic review rates of each system were investigated. Results The proportional bias for red blood cells (RBCs), white blood cells (WBCs) and squamous epithelial cells in the automated urine sediment analyzers were within ±20% of values obtained using the manual microscope, except in the cases of RBCs and WBCs analyzed using URiSCAN PlusScope and Iris iQ200SPRINT, respectively. The sensitivities of Roche Cobas® u 701 and Siemens UAS800 for pathologic casts (73.6% and 81.1%, respectively) and crystals (62.2% and 49.5%, respectively) were high, along with high image review rates (24.6% and 25.2%, respectively). The detection rates for crystals, casts and review rates can be changed for the Sysmex UF-5000 platform according to cut-off thresholds. Conclusions Each automated urine sediment analyzer has certain distinct features, in addition to the common advantages of reducing the burden of manual processing. Therefore, laboratory physicians are encouraged to understand these features, and to utilize each system in appropriate ways, considering clinical algorithms and laboratory workflow.</description><subject>Algorithms</subject><subject>Analyzers</subject><subject>automated urine sediment analyzer</subject><subject>Automation</subject><subject>Biological Assay - methods</subject><subject>Cobas</subject><subject>Crystals</subject><subject>Diagnostic systems</subject><subject>Epithelial cells</subject><subject>Erythrocytes</subject><subject>Humans</subject><subject>Image detection</subject><subject>Iris iQ200SPRINT</subject><subject>Leukocytes</subject><subject>Medical laboratories</subject><subject>Medical personnel</subject><subject>Microscopy</subject><subject>Microscopy - methods</subject><subject>Physicians</subject><subject>Sediments</subject><subject>Sensitivity analysis</subject><subject>u 701</subject><subject>UAS800</subject><subject>UF-5000</subject><subject>Urinalysis - methods</subject><subject>Urine</subject><subject>URiSCAN PlusScope</subject><subject>Workflow</subject><issn>1434-6621</issn><issn>1437-4331</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNptkU1v1TAQRS0EoqVlyxJZYsMmxWPHibNBQk98SZXY0HXk2GNwFccPO6Z6_fV1eAUE6sqzOPdYM5eQF8AuQIJ8Y8wcGs5gaBgHeEROoRV90woBj3_NbdN1HE7Is5yvGQMp2_4pORHAFeNiOCW3uxj2OvkcFxoddf4nUl3WGPSKlpbkF6QZrQ-4rFQvej7cYsr0xq_fadBL0TMN3qSYTdwfqIuJamNKqmnqbc14541e_dH-r-6cPHF6zvj8_j0jVx_ef919ai6_fPy8e3fZGNGrtbEdA2usVRatlJO0lg-T44yZyTnVcSaUZZPmxnYwoFIt2F7KAVkH3QTTIM7I66N3n-KPgnkdg88G51kvGEseOZdC1YOptqKv_kOvY0l160qJemTZC8YqdXGktr1zQjfukw86HUZg49bKuLUybq2MWys18PJeW6aA9g_-u4YKvD0CN3peMVn8lsqhDn-_f9gsewDo21bcASU8nxc</recordid><startdate>20191025</startdate><enddate>20191025</enddate><creator>Cho, Jooyoung</creator><creator>Oh, Kyeong Jin</creator><creator>Jeon, Beom Chan</creator><creator>Lee, Sang-Guk</creator><creator>Kim, Jeong-Ho</creator><general>De Gruyter</general><general>Walter De Gruyter & Company</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7T7</scope><scope>7TK</scope><scope>7U7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>P64</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-9628-2334</orcidid></search><sort><creationdate>20191025</creationdate><title>Comparison of five automated urine sediment analyzers with manual microscopy for accurate identification of urine sediment</title><author>Cho, Jooyoung ; Oh, Kyeong Jin ; Jeon, Beom Chan ; Lee, Sang-Guk ; Kim, Jeong-Ho</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c378t-d601dcdd8ded55b5dd29bf200cbff862038d0ba2cd619e8841d7559e0616b1b93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Algorithms</topic><topic>Analyzers</topic><topic>automated urine sediment analyzer</topic><topic>Automation</topic><topic>Biological Assay - methods</topic><topic>Cobas</topic><topic>Crystals</topic><topic>Diagnostic systems</topic><topic>Epithelial cells</topic><topic>Erythrocytes</topic><topic>Humans</topic><topic>Image detection</topic><topic>Iris iQ200SPRINT</topic><topic>Leukocytes</topic><topic>Medical laboratories</topic><topic>Medical personnel</topic><topic>Microscopy</topic><topic>Microscopy - methods</topic><topic>Physicians</topic><topic>Sediments</topic><topic>Sensitivity analysis</topic><topic>u 701</topic><topic>UAS800</topic><topic>UF-5000</topic><topic>Urinalysis - methods</topic><topic>Urine</topic><topic>URiSCAN PlusScope</topic><topic>Workflow</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cho, Jooyoung</creatorcontrib><creatorcontrib>Oh, Kyeong Jin</creatorcontrib><creatorcontrib>Jeon, Beom Chan</creatorcontrib><creatorcontrib>Lee, Sang-Guk</creatorcontrib><creatorcontrib>Kim, Jeong-Ho</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Neurosciences Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Clinical chemistry and laboratory medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cho, Jooyoung</au><au>Oh, Kyeong Jin</au><au>Jeon, Beom Chan</au><au>Lee, Sang-Guk</au><au>Kim, Jeong-Ho</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comparison of five automated urine sediment analyzers with manual microscopy for accurate identification of urine sediment</atitle><jtitle>Clinical chemistry and laboratory medicine</jtitle><addtitle>Clin Chem Lab Med</addtitle><date>2019-10-25</date><risdate>2019</risdate><volume>57</volume><issue>11</issue><spage>1744</spage><epage>1753</epage><pages>1744-1753</pages><issn>1434-6621</issn><eissn>1437-4331</eissn><abstract>Background While the introduction of automated urine analyzers is expected to reduce the labor involved, turnaround time and potential assay variations, microscopic examination remains the "gold standard" for the analysis of urine sediments. In this study, we evaluated the analytical and diagnostic performance of five recently introduced automated urine sediment analyzers. Methods A total of 1016 samples were examined using five automated urine sediment analyzers and manual microscopy. Concordance of results from each automated analyzer and manual microscopy were evaluated. In addition, image and microscopic review rates of each system were investigated. Results The proportional bias for red blood cells (RBCs), white blood cells (WBCs) and squamous epithelial cells in the automated urine sediment analyzers were within ±20% of values obtained using the manual microscope, except in the cases of RBCs and WBCs analyzed using URiSCAN PlusScope and Iris iQ200SPRINT, respectively. The sensitivities of Roche Cobas® u 701 and Siemens UAS800 for pathologic casts (73.6% and 81.1%, respectively) and crystals (62.2% and 49.5%, respectively) were high, along with high image review rates (24.6% and 25.2%, respectively). The detection rates for crystals, casts and review rates can be changed for the Sysmex UF-5000 platform according to cut-off thresholds. Conclusions Each automated urine sediment analyzer has certain distinct features, in addition to the common advantages of reducing the burden of manual processing. Therefore, laboratory physicians are encouraged to understand these features, and to utilize each system in appropriate ways, considering clinical algorithms and laboratory workflow.</abstract><cop>Germany</cop><pub>De Gruyter</pub><pmid>31280239</pmid><doi>10.1515/cclm-2019-0211</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-9628-2334</orcidid></addata></record> |
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subjects | Algorithms Analyzers automated urine sediment analyzer Automation Biological Assay - methods Cobas Crystals Diagnostic systems Epithelial cells Erythrocytes Humans Image detection Iris iQ200SPRINT Leukocytes Medical laboratories Medical personnel Microscopy Microscopy - methods Physicians Sediments Sensitivity analysis u 701 UAS800 UF-5000 Urinalysis - methods Urine URiSCAN PlusScope Workflow |
title | Comparison of five automated urine sediment analyzers with manual microscopy for accurate identification of urine sediment |
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