Literature DB >> 29655959

The efficient workflow to decrease the manual microscopic examination of urine sediment using on-screen review of images.

Eun-Jung Cho1, Dae-Hyun Ko2, Woochang Lee2, Sail Chun2, Hae Kyung Lee1, Won-Ki Min3.   

Abstract

BACKGROUND: The manual microscopic examination (MME) of urine sediment is labor-intensive, time-consuming, and imprecise. Therefore, automated urinalysis systems based on flow cytometry or digital imaging techniques could replace MME. The purpose of this study was to evaluate the rate of MME using two automated urine sediment analyzers, alone and in combination.
METHODS: This study was conducted using the freshly collected urine specimens of 1055 in-patients and 1119 out-patients. All samples were analyzed using UF-1000i (Sysmex Corporation) and Cobas 6500 instrument (Roche Diagnostics International). The rate of MME was evaluated using two analyzers, both individually and in combination.
RESULTS: Using the UF-1000i alone, 34.2% and 16.8%, respectively, of in- and out-patient samples were analyzed by MME, compared to 15.6% and 3.7%, respectively, using the Cobas 6500. In combined assay using the UF-1000i followed by the Cobas 6500, 27.9% and 11.3% in-patient samples required on-screen review and MME, respectively. And the respective rates were 10.3% and 2.7% of out-patient. Samples using the Cobas 6500 followed by the UF-1000i, 42.3% and 11.3% in-patient needed on-screen review and MME, respectively. And the respective rates were 18.9% and 2.7% of out-patient samples.
CONCLUSIONS: Use of the Cobas 6500 compared to the UF-1000i resulted in decreases in the rate of MME from 34.2% to 15.6% for in-patient samples, and from 16.8% to 3.7% for out-patient samples. Use of the Cobas 6500 reduced the rate of MME, and compared to use of only the Cobas 6500, the combined use resulted in a reduction in the rate of on-screen review.
Copyright © 2018 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Automated urinalysis; Image analysis; Microscopy; Urine sediment

Mesh:

Year:  2018        PMID: 29655959     DOI: 10.1016/j.clinbiochem.2018.04.008

Source DB:  PubMed          Journal:  Clin Biochem        ISSN: 0009-9120            Impact factor:   3.281


  6 in total

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2.  An ensemble approach of urine sediment image analysis and NMP22 test for detection of bladder cancer cells.

Authors:  Eun-Jung Cho; Chang Kwon Bang; Hyunjung Kim; Hae Kyung Lee
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4.  Consistency analysis of the Sysmex UF-5000 and Atellica UAS 800 urine sedimentation analyzers.

Authors:  Hai Liu; Qing Li; Yiduo Zhang; Dongyue Huang; Fan Yu
Journal:  J Clin Lab Anal       Date:  2022-08-16       Impact factor: 3.124

5.  A Microfluidic Detection System for Bladder Cancer Tumor Cells.

Authors:  Shuxing Lv; Jinwei Yu; Yan Zhao; Hongxiang Li; Fang Zheng; Ning Liu; Dahua Li; Xuguo Sun
Journal:  Micromachines (Basel)       Date:  2019-12-11       Impact factor: 2.891

6.  Automated urine sediment analyzers underestimate the severity of hematuria in glomerular diseases.

Authors:  Won Seok Yang
Journal:  Sci Rep       Date:  2021-10-25       Impact factor: 4.379

  6 in total

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