Journal articles: 'Automated urinalysis'

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Carlson, Desiree A., and Bernard E. Statland. "Automated Urinalysis." Clinics in Laboratory Medicine 8, no. 3 (1988): 449–61. http://dx.doi.org/10.1016/s0272-2712(18)30667-x.

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Okada, Hiroshi, Yutaka Sakai, Gaku Kawabata, et al. "Automated Urinalysis." American Journal of Clinical Pathology 115, no. 4 (2001): 605–10. http://dx.doi.org/10.1309/rt7x-emgf-g8av-tgj8.

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Oyaert, Matthijs, and Joris Delanghe. "Progress in Automated Urinalysis." Annals of Laboratory Medicine 39, no. 1 (2019): 15–22. http://dx.doi.org/10.3343/alm.2019.39.1.15.

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Gautam, K., and D. Pyakurel. "Automated urinalysis: First experiences and comparison of automated urinalysis system and manual microscopy." Journal of Pathology of Nepal 4, no. 7 (2014): 576–79. http://dx.doi.org/10.3126/jpn.v4i7.10316.

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Background: Urinary tract infection is a common condition which needs laboratory evaluation of urine to substantiate the clinical diagnosis and initiate treatment. The conventional urinalysis consists of using a test strip for chemical examination to identify the various urine sediments after which visual microscopy is done. We evaluate the analytical performance of automated microscopic technique (UF 500i) and compare results with those from manual microscopy. Materials and Methods: A total of 382 urine specimens were collected during a period of one month out of which 128 samples which had abnormal cell counts were analyzed for cells and particles by manual and automated microscopy by UF-500i flow cytometer. Results: The concordance of UF 500i and the manual microscopy which is considered to be the gold standard for urine microscopic examination was 90.6% for white blood cells, red blood cell, epithelial cells, cast and bacterial count. Conclusion: Automated urine sediment analyzer, UF 500i was considered reliable in the measurement of white blood cells, red blood cells, epithelial cells, cast and bacteria. Automation will surely reduce the work load, increase accuracy and reliability, and increase the throughput and turn-around time of the laboratory DOI: http://dx.doi.org/10.3126/jpn.v4i7.10316 Journal of Pathology of Nepal (2014) Vol. 4, 576-579

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Kayalp, Damla, Kubra Dogan, Gozde Ceylan, Mehmet Senes, and Dogan Yucel. "Can routine automated urinalysis reduce culture requests?" Clinical Biochemistry 46, no. 13-14 (2013): 1285–89. http://dx.doi.org/10.1016/j.clinbiochem.2013.06.015.

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İnce, Fatma Demet, Hamit Yaşar Ellidağ, Mehmet Koseoğlu, Neşe Şimşek, Hülya Yalçın, and Mustafa Osman Zengin. "The comparison of automated urine analyzers with manual microscopic examination for urinalysis automated urine analyzers and manual urinalysis." Practical Laboratory Medicine 5 (August 2016): 14–20. http://dx.doi.org/10.1016/j.plabm.2016.03.002.

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Deindoerfer, F. H., J. R. Gangwer, C. W. Laird, and R. R. Ringold. ""The Yellow IRIS" urinalysis workstation--the first commercial application of "automated intelligent microscopy"." Clinical Chemistry 31, no. 9 (1985): 1491–99. http://dx.doi.org/10.1093/clinchem/31.9.1491.

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Abstract Since 1982, "automated intelligence microscopy" (AIM) has been refined and adapted to perform the portion of the urinalysis profile traditionally done by a microscope. AIM and analytical subsystems measuring relative density and performing dipstick chemistry compose the main elements of "The Yellow IRIS" urinalysis workstation, an attended system for automation and standardization of routine urinalysis. Performance data gathered at three laboratory test sites show AIM to be analytically consistent over the required range of particulate enumeration, and show that it detects 20% more abnormalities than by conventional microscopy, and with greater precision (CVs 5 to 20%). Complete urinalysis, including the microscopic examination, requires little more than 1 min for normal specimens, 3 min for most abnormal specimens. Actual throughput rate varies with the particulate composition of specimens; typically, it averages greater than 30 specimens per hour, a 300% improvement in urinalysis productivity by CAP standards and an almost 500% improvement when typical emergency-use demands are taken into account.

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Langlois, Michel R., Joris R. Delanghe, Sophia R. Steyaert, Karel C. Everaert, and Marc L. De Buyzere. "Automated Flow Cytometry Compared with an Automated Dipstick Reader for Urinalysis." Clinical Chemistry 45, no. 1 (1999): 118–22. http://dx.doi.org/10.1093/clinchem/45.1.118.

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Abstract Recently, the Sysmex UF-100 flow cytometer was developed to automate urinalysis. We compared UF-100 test results with those of an automated dipstick reader. A cross-check of UF-100, dipstick, and microscopic sediment data was performed in 1001 urine samples. Good agreements (P &lt;0.001) were obtained between UF-100 and dipstick data for erythrocytes (r = 0.636) and leukocytes (r = 0.785). Even in urine with low conductivity, the UF-100 could detect lysed erythrocytes. The UF-100 bacterial count was higher among nitrite-positive urine samples (P &lt;0.0001) and was positively correlated with the UF-100 leukocyte count (r = 0.745; P &lt;0.001). In stored urine (24 h), bacterial counts increased, whereas the forward light scatter of leukocytes decreased (P &lt;0.01). Casts and yeast cells reported by the UF-100 should be confirmed by microscopic review because false positives occurred. We suggest that a computer-assisted cross-check of UF-100 and dipstick data allows a clinically acceptable sieving system to reduce the workload of microscopic sediment urinalysis.

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Elin, Ronald J., Jeanette M. Hosseini, Jane Kestner, Michael Rawe, Mark Ruddel, and H. Harold Nishi. "Comparison of Automated and Manual Methods for Urinalysis." American Journal of Clinical Pathology 86, no. 6 (1986): 731–37. http://dx.doi.org/10.1093/ajcp/86.6.731.

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Tworek, Joseph A., David S. Wilkinson, and Molly K. Walsh. "The Rate of Manual Microscopic Examination of Urine Sediment: A College of American Pathologists Q-Probes Study of 11 243 Urinalysis Tests From 88 Institutions." Archives of Pathology & Laboratory Medicine 132, no. 12 (2008): 1868–73. http://dx.doi.org/10.5858/132.12.1868.

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Abstract Context.—The manual microscopic examination (MME) of the urine sediment is an imprecise and labor-intensive procedure. Many laboratories have developed rules from clinical parameters or urinalysis results to limit the number of these examinations. Objective.—To determine the rate of urinalysis specimens on which an MME of the urine sediment was performed, document how various rules influence this rate, and determine whether any new information was learned from the MME. Design.—Participants selected 10 random urinalysis tests received during each traditional shift and determined if an MME was performed until a total of 50 urinalysis tests with an MME were reviewed. Participants recorded the rules that elicited an MME and any new information learned from such an examination. Results.—The MME rate for the median institution was 62.5%. An MME of urine was most frequently done for an abnormal urinalysis result and often resulted in new information being learned, irrespective of the rule that elicited the MME. The median institution learned new information as a result of the manual examination 66% of the time. The use of an automated microscopic analyzer was associated with fewer manual examinations (P = .005), whereas the ability of a clinician to order a manual examination was associated with more manual examinations (P = .004). Conclusions.—The use of an automated microscopic analyzer may decrease the number of MMEs. An MME when triggered by an abnormal macroscopic appearance of urine, a physician request, or virtually any positive urinalysis result often resulted in new information.

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Ben-Ezra, Jonathan, Linda Bork, and Richard A. McPherson. "Evaluation of the Sysmex UF-100 automated urinalysis analyzer." Clinical Chemistry 44, no. 1 (1998): 92–95. http://dx.doi.org/10.1093/clinchem/44.1.92.

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Abstract Urinalysis is a high-volume procedure that currently requires significant labor to examine microscopic sediment. We evaluated the Sysmex UF-100 automated urinalysis analyzer for performing this task. Instrument accuracy was assessed by comparing continuous counts of microscopic elements from the UF-100 with ranges of cells (per low-power field or high-power field) from manual microscopy performed on centrifuged urines. Counts showed good agreement between methods (gamma statistic: 0.880–0.970) for all microscopic elements in 252 urine samples. Within-run imprecision of cell counts expressed as CV (mean cell count/μL) was for erythrocytes (RBC) 31% (5), 18% (50), 2.4% (800); for leukocytes (WBC) 14% (10), 11% (100), 8.5% (400); for squamous epithelial cells (SEC) 18% (5), 12% (30), 7.0% (100); for casts 45% (1), 17% (4); for bacteria 2–12% (entire range of 40–2500). Between-run imprecision on quality-control cell suspensions expressed as CV (mean cell count/μL) was for RBC 6.1% (50), 2.7% (256); for WBC 26.9% (54), 4.9% (228). Cells counted on dilution were 99.1% of expected for RBC, 102.0% for WBC, and 121.8% for bacteria. Carryover was &lt;0.04% for RBC, &lt;0.03% for WBC, &lt;0.14% for SEC, &lt;0.29% for bacteria. We conclude that the UF-100 can automatically perform reliable quantitative microscopic urinalysis in batches without operator interaction.

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Kim, Namhee, Sun Min Lee, and Chulhun L. Chang. "Evaluation of an Automated Dipstick Device for Urinalysis-UriDoctor." Journal of Laboratory Medicine and Quality Assurance 36, no. 4 (2014): 190–95. http://dx.doi.org/10.15263/jlmqa.2014.36.4.190.

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Evans, Samantha J. M., Julia L. Sharp, and Linda M. Vap. "Optimizing the u411 automated urinalysis instrument for veterinary use." Veterinary Clinical Pathology 49, no. 1 (2020): 106–11. http://dx.doi.org/10.1111/vcp.12818.

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Yusuf, Erlangga, Bruno Van Herendael, and Jef van Schaeren. "Performance of urinalysis tests and their ability in predicting results of urine cultures: a comparison between automated test strip analyser and flow cytometry in various subpopulations and types of samples." Journal of Clinical Pathology 70, no. 7 (2016): 631–36. http://dx.doi.org/10.1136/jclinpath-2016-204108.

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AimsResults of urinalysis are available earlier than urine culture results. If urinalysis can predict results of culture, early decision can be made on treatment and whether urine samples should be cultured. This study sought to compare the performance of urinalysis tests by automated test strip analyser (nitrite and leucocyte esterase) with flow cytometry (bacteria and white cell count) in different subpopulations and types of samples.MethodsConsecutive urine samples (n=2351) from a population with a median age of 45 years, 37.2% men, were tested. Sensitivity, specificity, positive predictive value and negative predictive value (NPV) of the tests were calculated using contingency tables. The gold standard was positive urine culture with cut-off >105 CFU/mL.Results14% of the cultures were positive (95.6% monomicrobial, 74.7% Enterobacteriaceae). Overall, nitrite test was the most specific (98.7%) but the least sensitive (43.2%). Bacteria count was the most sensitive (91.7%) and highly specific (87.5%). In infants <24 months, the sensitivity of bacteria count was reduced (86.1%), but specificity was high (95.9%). The specificity of nitrite was reduced in urine from the in-and-out procedure (81.9%). The sensitivity of bacteria count was reduced in bag specimens urine (83.3%) and in urine from indwelling catheter (84.7%). All tests showed a high NPV. The NPV of the combined flow cytometry tests was higher than those of automated test strip analyser (99.1% vs 97.4%).ConclusionsOverall, the performance of urinalysis is excellent. Flow cytometry tests performed better than automated test strip analyser in ruling out urine to be cultured.

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Powless, Amy J., Sandra P. Prieto, Madison R. Gramling, Roxanna J. Conley, Gregory G. Holley, and Timothy J. Muldoon. "Evaluation of Acridine Orange Staining for a Semi-Automated Urinalysis Microscopic Examination at the Point-of-Care." Diagnostics 9, no. 3 (2019): 122. http://dx.doi.org/10.3390/diagnostics9030122.

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A urinary tract infection (UTI) can be diagnosed via urinalysis, consisting of a dipstick test and manual microscopic examination. Point-of-care (POC) image-based systems have been designed to automate the microscopic examination for low-volume laboratories or low-resource clinics. In this pilot study, acridine orange (AO) was evaluated as a fluorescence-based contrast agent to aid in detecting and enumerating urine sediment specific for diagnosing a UTI. Acridine orange staining of epithelial cells, leukocytes, and bacteria provided sufficient contrast to successfully implement image segmentation techniques, which enabled the extraction of classifiable morphologic features. Surface area bounded by each cell border was used to differentiate the sediment; epithelial cells were larger than 500μm2, bacteria were less than 30μm2, and leukocytes in between. This image-based semi-automated technique using AO resulted in similar cell counts to the clinical results, which demonstrates the feasibility of AO as an aid for POC urinalysis systems.

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Young, Jennifer L., and David E. Soper. "Urinalysis and Urinary Tract Infection: Update for Clinicians." Infectious Diseases in Obstetrics and Gynecology 9, no. 4 (2001): 249–55. http://dx.doi.org/10.1155/s1064744901000412.

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Dysuria is a common presenting complaint of women and urinalysis is a valuable tool in the initial evaluation of this presentation. Clinicians need to be aware that pyuria is the best determinate of bacteriuria requiring therapy and that values significant for infection differ depending on the method of analysis. A hemocytometer yields a value of ≥ 10 WBC/ mm3significant for bacteriuria, while manual microscopy studies show ≥ 8 WBC/high-power field reliably predicts a positive urine culture. In cases of uncomplicated symptomatic urinary tract infection, a positive value for nitrites and leukocyte esterase by urine dipstick can be treated without the need for a urine culture. Automated urinalysis used widely in large volume laboratories provides more sensitive detection of leukocytes and bacteria in the urine.With automated microscopy, a value of > 2 WBC/hpf is significant pyuria indicative of inflammation of the urinary tract. In complicated cases such as pregnancy, recurrent infection or renal involvement, further evaluation is necessary including manual microscopy and urine culture with sensitivities.

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Cho, Sun Young, and Mina Hur. "Advances in Automated Urinalysis Systems, Flow Cytometry and Digitized Microscopy." Annals of Laboratory Medicine 39, no. 1 (2019): 1–2. http://dx.doi.org/10.3343/alm.2019.39.1.1.

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Sullivan, Michele G. "Automated Urinalysis Beats Bacterial Count As UTI Screen in Kids." Family Practice News 38, no. 14 (2008): 46. http://dx.doi.org/10.1016/s0300-7073(08)70919-8.

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Okada, Hiroshi, Yutaka Sakai, Shigenori Miyazaki, Soichi Arakawa, Yukio Hamaguchi, and Sadao Kamidono. "Detection of Significant Bacteriuria by Automated Urinalysis Using Flow Cytometry." Journal of Clinical Microbiology 38, no. 8 (2000): 2870–72. http://dx.doi.org/10.1128/jcm.38.8.2870-2872.2000.

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A new flow cytometry-based automated urine analyzer, the UF-50, was evaluated for its ability to screen urine samples for significant bacteriuria. One hundred eighty-six urine specimens from patients attending an outpatient clinic of a university-based hospital were examined. The results obtained with the UF-50 were compared with those obtained by conventional quantitative urine culture. The UF-50 detected significant bacteriuria with a sensitivity of 83.1%, a specificity of 76.4%, a positive predictive value of 62.0%, a negative predictive value of 90.7%, and an accuracy of 78.5%. These results are comparable to those obtained by previously reported screening procedures. Besides detecting significant bacteriuria, the UF-50 can also perform routine urinalysis, including measurement of concentrations of red blood cells, white blood cells, epithelial cells, and casts, within 70 s. This capability renders this new flow cytometry-based urine analyzer superior to previously reported rapid screening methods.

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Palsson, Ragnar, Anand Srivastava, and Sushrut S. Waikar. "Performance of the Automated Urinalysis in Diagnosis of Proliferative Glomerulonephritis." Kidney International Reports 4, no. 5 (2019): 723–27. http://dx.doi.org/10.1016/j.ekir.2019.02.001.

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Gai, Massimo, Giorgina B. Piccoli, Giuseppe P. Segoloni, and Giacomo Lanfranco. "Microscopic Urinalysis and Automated Flow Cytometry in a Nephrology Laboratory." Clinical Chemistry 49, no. 9 (2003): 1559–60. http://dx.doi.org/10.1373/49.9.1559.

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Xiang, Jiwen, Yong Zhang, Ziliang Cai, Wanjun Wang, and Caifeng Wang. "A 3D printed centrifugal microfluidic platform for automated colorimetric urinalysis." Microsystem Technologies 26, no. 2 (2019): 291–99. http://dx.doi.org/10.1007/s00542-019-04709-4.

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Messing, Edward. "Automated Urinalysis Machines: Potential Impact on the Diagnosis of Bladder Cancer." Bladder Cancer 5, no. 3 (2019): 249–50. http://dx.doi.org/10.3233/blc-199007.

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Poropatich, Cary O., Salome M. Mendoza, Jeanne J. Hitlan, and David S. Wilkinson. "Inconsistent Detection of Bacteriuria With the Yellow IRIS Automated Urinalysis Workstation." Laboratory Medicine 19, no. 8 (1988): 499–501. http://dx.doi.org/10.1093/labmed/19.8.499.

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Roe, Carlos E., Desiree A. Carlson, Robert W. Daigneault, and Bernard E. Statland. "Evaluation of the Yellow IRIS®: An Automated Method for Urinalysis." American Journal of Clinical Pathology 86, no. 5 (1986): 661–65. http://dx.doi.org/10.1093/ajcp/86.5.661.

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Mendes, M. E., L. B. Avallone, B. V. Antunes, C. G. C. D. N. Freire, R. M. Pavloff, and N. M. Sumita. "Analytical and clinical performance evaluation and comparison of automated urinalysis analyzers." Clinica Chimica Acta 493 (June 2019): S17—S18. http://dx.doi.org/10.1016/j.cca.2019.03.046.

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Lamsal, Madhab. "Urinalysis: Extract the Relevant Information Before Throwing it into the Drain." Annals of Clinical Chemistry and Laboratory Medicine 4, no. 1 (2021): 1–3. http://dx.doi.org/10.3126/acclm.v4i1.42672.

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From ancient time urine has been considered as a substance of importance and examination for physical wellbeing. Evidences from the ancient civilizations including the Egyptian, Sumerian, Babylonian and Eastern Civilizations such as Vedic cultures support the use of urine as an index of physical and mental well-being. Classified as coloured, black, frothy, cloudy and sweet, urine used to be correlated with different disease conditions such as jaundice, kidney diseases, diabetes etc. These practices have been carried on even by the alchemists and have now formed as an integral constituent of clinical laboratory diagnostics. Modern approach to urinalysis can be credited to Dr. Richard Bright, MD, who in 1827 by performing urine examinations related to vol-ume, colour, pH, protein (but not cast) corre-lated his findings to several diseases and clini-cal picture including edema, proteinuria etc. Urinalysis combines the expertise from vari-ous disciplines including biochemistry, pa-thology, microbiology, cytology etc. Urinalysis may be used for screening, diagnosis, monitoring and prognosis due to the ease of collection in any settings. Modern day tech-niques such as molecular biology, immunolo-gy, and mass spectrometry with high resolu-tion microscopy have taken up urinalysis to explore the genetic predisposition to inherited diseases and tumor studies besides the routine diagnostics. So, variation occurs in urinalysis from the simple routine analysis, microscopic examination to highly sophisticated and ad-vanced automated analytical techniques. Uri-nalysis therefore, forms a key component of personalized medicine also integrating with proteomics, genomics, metabolomics approaches.

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Penders, Joris, Tom Fiers, and Joris R. Delanghe. "Quantitative Evaluation of Urinalysis Test Strips." Clinical Chemistry 48, no. 12 (2002): 2236–41. http://dx.doi.org/10.1093/clinchem/48.12.2236.

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Abstract Background: Urine test strip results are generally reported in categories (i.e., ordinal scaled), but automated strip readers are now available that can report quantitative data. We investigated the possible use of these meters to complement flow cytometry of urine and compared reflectance readings with quantitative determinations of urinary glucose and microalbumin. Methods: We compared URISYS 2400 (Roche) quantitative reflectance data with data from the UF-100 (Sysmex) and biochemical data for 436 nonpathologic and pathologic urine samples. Results: Reproducibility of the reflectance signal was good for high- and low-concentration urine pools for protein (0.8% and 0.9% and 1.5% and 2.2% within and between runs, respectively), leukocyte esterase (1.1% and 1.0%; 5.1% and 1.2%), hemoglobin (1.7% and 1.1%; 8.9% and 1.1%) and glucose (2.1% and 0.5%; 6.5% and 2.3%). Fair agreement was obtained between UF-100 and test strip reflectance data for erythrocytes and hemoglobin (r = −0.680) and leukocytes and leukocyte esterase (r = −0.688). Higher correlations were observed for biochemical and test strip data comparing protein and albumin (r = −0.825) and glucose data (r = −0.851). The lower limits of detection for erythrocytes and leukocytes were 8 × 106/L and 19 × 106/L, respectively. The protein test (n = 220) detected 86% (95% confidence interval, 78–92%) of samples with &lt;30 mg/L albumin with a specificity of 84% (95% confidence interval, 76–91%). Conclusions: In urine test strip analysis, quantitative hemoglobin and leukocyte esterase reflectance data are complementary with flow cytometric results and glucose and albumin results.

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Chien, Tzu-I., Jau-Tsuen Kao, Hui-Lan Liu, et al. "Urine sediment examination: A comparison of automated urinalysis systems and manual microscopy." Clinica Chimica Acta 384, no. 1-2 (2007): 28–34. http://dx.doi.org/10.1016/j.cca.2007.05.012.

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Chaudhari, Pradip P., Michael C. Monuteaux, and Richard G. Bachur. "Microscopic Bacteriuria Detected by Automated Urinalysis for the Diagnosis of Urinary Tract Infection." Journal of Pediatrics 202 (November 2018): 238–44. http://dx.doi.org/10.1016/j.jpeds.2018.07.007.

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Dimech, Wayne, and Kris Roney. "Evaluation of an automated urinalysis system for testing urine chemistry, microscopy and culture." Pathology 34, no. 2 (2002): 170–77. http://dx.doi.org/10.1080/003130201201117990.

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Kanegaye, J. T., J. M. Jacob, and D. Malicki. "Automated Urinalysis and Urine Dipstick in the Emergency Evaluation of Young Febrile Children." PEDIATRICS 134, no. 3 (2014): 523–29. http://dx.doi.org/10.1542/peds.2013-4222.

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Khejonnit, Varanya, Busadee Pratumvinit, Kanit Reesukumal, Suriya Meepanya, Chanutchaya Pattanavin, and Preechaya Wongkrajang. "Optimal criteria for microscopic review of urinalysis following use of automated urine analyzer." Clinica Chimica Acta 439 (January 2015): 1–4. http://dx.doi.org/10.1016/j.cca.2014.09.027.

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Froom, Paul, Barbara Bieganiec, Zahava Ehrenrich, and Mira Barak. "Stability of Common Analytes in Urine Refrigerated for 24 h before Automated Analysis by Test Strips." Clinical Chemistry 46, no. 9 (2000): 1384–86. http://dx.doi.org/10.1093/clinchem/46.9.1384.

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Abstract Background: Central outpatient laboratories might find processing large numbers of urinary samples that arrive in the late afternoon inconvenient and refrigerate them overnight before testing. Furthermore, in certain settings clinics might have difficulty assuring that the urine arrives at the laboratory during the same day as the collection. Because the stability of urine samples for delayed automated dipstick analysis (Supertron) is unknown, after defining precision, we retested urines refrigerated for 24 h to determine stability. Methods: Urinalysis was done twice on the same day and repeated after the sample was refrigerated for 24 h. Combur-10S (Roche Diagnostics) dipsticks were read automatically by a Supertron analyzer. Repeat tests on the same day were compared with tests after storage. Results: Leukocyte esterase had high precision, but after storage ∼25% of the positive samples were less reactive (P &lt;0.005). Precision of hemoglobin retests was also high but declined significantly after storage for 24 h. Urine protein values increased after storage. The precision and stability were excellent for nitrites, glucose, and ketones. Conclusions: The stability of the automated dipstick urinalysis varies with the substance tested. After refrigeration for 24 h, there is a risk of false-positive results for protein, false-negative results for leukocytes and erythrocytes, and little effect on glucose, nitrite, and ketone values.

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van Delft, Sanne, Annelijn Goedhart, Mark Spigt, Bart van Pinxteren, Niek de Wit, and Rogier Hopstaken. "Prospective, observational study comparing automated and visual point-of-care urinalysis in general practice." BMJ Open 6, no. 8 (2016): e011230. http://dx.doi.org/10.1136/bmjopen-2016-011230.

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Tetrault, Gregory A. "Automated Reagent Strip Urinalysis: Utility in Reducing Work Load of Urine Microscopy and Culture." Laboratory Medicine 25, no. 3 (1994): 162–67. http://dx.doi.org/10.1093/labmed/25.3.162.

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Hertz, Alexandria M., Deo S. Perez, Mark I. Anderson, and Timothy C. Brand. "Automated Urinalysis for Evaluation of Microscopic Hematuria: Current Options and Revising the Gold Standard." Urology Practice 7, no. 3 (2020): 199–204. http://dx.doi.org/10.1097/upj.0000000000000083.

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Skitek, Milan. "Imprecision and instability of common analytes in urine analysed by semi-automated dipstick urinalysis." Accreditation and Quality Assurance 9, no. 11-12 (2004): 700–703. http://dx.doi.org/10.1007/s00769-004-0883-1.

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von Wulffen, H. "P1149 Evaluation of a new automated urine cell analyser (Sysmex UF-1000i) for bacteriological urinalysis." International Journal of Antimicrobial Agents 29 (March 2007): S312. http://dx.doi.org/10.1016/s0924-8579(07)70989-5.

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Phelan, Lorna K., Mark A. Brown, Gregory K. Davis, and George Mangos. "A Prospective Study of the Impact of Automated Dipstick Urinalysis on the Diagnosis of Preeclampsia." Hypertension in Pregnancy 23, no. 2 (2004): 135–42. http://dx.doi.org/10.1081/prg-120028289.

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Wesarachkitti, Bongkot, Varanya Khejonnit, Busadee Pratumvinit, et al. "Performance Evaluation and Comparison of the Fully Automated Urinalysis Analyzers UX-2000 and Cobas 6500." Laboratory Medicine 47, no. 2 (2016): 124–33. http://dx.doi.org/10.1093/labmed/lmw002.

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Middelkoop, S. J. M., L. J. van Pelt, G. A. Kampinga, J. C. ter Maaten, and C. A. Stegeman. "Routine tests and automated urinalysis in patients with suspected urinary tract infection at the ED." American Journal of Emergency Medicine 34, no. 8 (2016): 1528–34. http://dx.doi.org/10.1016/j.ajem.2016.05.005.

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Van Acker, Jos T., Joris R. Delanghe, Michel R. Langlois, Youri E. Taes, Marc L. De Buyzere, and Alain G. Verstraete. "Automated Flow Cytometric Analysis of Cerebrospinal Fluid." Clinical Chemistry 47, no. 3 (2001): 556–60. http://dx.doi.org/10.1093/clinchem/47.3.556.

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Abstract Background: Recently, the UF-100 (Sysmex Corporation) flow cytometer was developed to automate urinalysis. We evaluated the use of flow cytometry in the analysis of cerebrospinal fluid (CSF). Methods: UF-100 data were correlated with microscopy and biochemical data for 256 CSF samples. Microbiological analysis was performed in 144 suspected cases of meningitis. Results: Good agreement was obtained between UF-100 and microscopy data for erythrocytes (r = 0.919) and leukocytes (r = 0.886). In some cases, however, incorrect classification of lymphocytes by the UF-100 led to underestimation of the leukocyte count. UF-100 bacterial count positively correlated (P &lt;0.001) with UF-100 leukocyte count (r = 0.666), CSF total protein (r = 0.754), and CSF lactate concentrations (r = 0.641), and negatively correlated with CSF glucose concentration (r = −0.405; P &lt;0.001). UF-100 bacterial counts were unreliable in hemorrhagic samples and in samples collected by ventricular drainage where interference by blood platelets and cell debris was observed. Another major problem was the UF-100 “bacterial” background signal in sterile CSF samples. Cryptococcus neoformans yeast cells and cholesterol crystals in craniopharyngioma were detected by the flow cytometer. Conclusions: Flow cytometry of CSF with the UF-100 offers a rapid and reliable leukocytes and erythrocyte count. Additional settings offered by the instrument may be useful in the diagnosis of neurological disorders.

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Mayo, S., D. Acevedo, C. Quiñones‐Torrelo, I. Canós, and M. Sancho. "Clinical laboratory automated urinalysis: comparison among automated microscopy, flow cytometry, two test strips analyzers, and manual microscopic examination of the urine sediments." Journal of Clinical Laboratory Analysis 22, no. 4 (2008): 262–70. http://dx.doi.org/10.1002/jcla.20257.

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Chen, Yung-Liang, Mao-Kuei Chang, Yu-Jen Chen, and Bao-Chy Chang. "Comparing Neubauer Hemacytometer, SY Conventional, SY Located, and Automated Flow Cytometer F–100 Methods for Urinalysis." Laboratory Medicine 40, no. 4 (2009): 227–31. http://dx.doi.org/10.1309/lm8poktmiqxsstho.

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Shah, Ami P., Benjamin T. Cobb, Darla R. Lower, et al. "Enhanced Versus Automated Urinalysis for Screening of Urinary Tract Infections in Children in the Emergency Department." Pediatric Infectious Disease Journal 33, no. 3 (2014): 272–75. http://dx.doi.org/10.1097/inf.0000000000000215.

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Kucukgergin, Canan, Evin Ademoglu, Beyhan Omer, and Sema Genc. "Performance of automated urine analyzers using flow cytometric and digital image-based technology in routine urinalysis." Scandinavian Journal of Clinical and Laboratory Investigation 79, no. 7 (2019): 468–74. http://dx.doi.org/10.1080/00365513.2019.1658894.

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Falbo, Rosanna, Maria Roberta Sala, Marco Bussetti, et al. "Performance evaluation of a new and improved cuvette-based automated urinalysis analyzer with phase contrast microscopy." Clinica Chimica Acta 491 (April 2019): 126–31. http://dx.doi.org/10.1016/j.cca.2019.01.025.

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Du, Juan, Jia Xu, Fei Wang, et al. "Establishment and development of the personalized criteria for microscopic review following multiple automated routine urinalysis systems." Clinica Chimica Acta 444 (April 2015): 221–28. http://dx.doi.org/10.1016/j.cca.2015.02.022.

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Accorsi, Antonio, Anna Barbieri, Giovanni Raffi, and Francesco Violante. "Biomonitoring of exposure to nitrous oxide, sevoflurane, isoflurane and halothane by automated GC/MS headspace urinalysis." International Archives of Occupational and Environmental Health 74, no. 8 (2001): 541–48. http://dx.doi.org/10.1007/s004200100263.

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Journal articles on the topic 'Automated urinalysis'

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