scholarly journals Iodine containing contrast media and urinary flow cytometry: an unknown interference in automated urine sediment analysis

Author(s):  
Matthijs N. Oyaert ◽  
Marc L. De Buyzere ◽  
Koenraad L. Verstraete ◽  
Marijn M. Speeckaert ◽  
Joris R. Delanghe
Author(s):  
Dae-Hyun Ko ◽  
Misuk JI ◽  
Sollip Kim ◽  
Eun-Jung Cho ◽  
Woochang Lee ◽  
...  

2003 ◽  
Vol 49 (4) ◽  
pp. 617-623 ◽  
Author(s):  
Cornelia Ottiger ◽  
Andreas R Huber

Abstract Background: Automated systems have enabled the counting of particles in urine to be standardized. Their superiority over traditional sediment analysis has been well documented, but they have not gained wide acceptance. The reasons for this are that sediment analysis has been performed and interpreted for decades. Additionally, pathologic casts and other unknown particles still must be confirmed under the microscope. Furthermore, comparison between the methods has revealed outliers and thus decreased confidence in automation. Methods: We used the standardized KOVA cell chamber system to count particles and compared the results with UF-100 flow cytometry as an alternative to traditional sediment analysis. Results: We compared 252 randomly selected urine samples and obtained a review rate of 33%. Microscopic verification was necessary because of the presence of casts, yeast, sperm, dysmorphic erythrocytes, and some misclassified erythrocytes or leukocytes that were detected by incongruent dipstick results and abnormal scattergrams. We obtained correlation coefficients of 0.966 for erythrocytes and 0.935 for leukocytes. Criteria for an algorithm to identify samples that needed microscopic review were derived from comparisons between the number of particles from UF-100, dipstick results, cell chamber counting, and sediment analysis. Conclusions: Automated cell counting combined with microscopic counting with a standardized cell chamber system is useful. An objective algorithm for review criteria can be developed via systematic comparison of UF-100 flow cytometry and microscopy. Only urine samples that meet these criteria need to be confirmed microscopically.


2010 ◽  
Vol 411 (3-4) ◽  
pp. 147-154 ◽  
Author(s):  
Zahur Zaman ◽  
Giovanni Battista Fogazzi ◽  
Giuseppe Garigali ◽  
Maria Daniela Croci ◽  
Gabor Bayer ◽  
...  

2019 ◽  
Vol 4 (1) ◽  
pp. 40-50
Author(s):  
Muhamed Katica ◽  
Nasreldin Hassan Ahmed ◽  
Alen Salkić ◽  
Adis Mukača ◽  
Ajdin Bašić ◽  
...  

2018 ◽  
Vol 43 (2) ◽  
pp. 606-615 ◽  
Author(s):  
Davide Viggiano ◽  
Giuseppe Gigliotti ◽  
Gianfranco Vallone ◽  
Anna Giammarino ◽  
Michelangelo Nigro ◽  
...  

2021 ◽  
pp. 104063872110389
Author(s):  
Elisabeth Neubert ◽  
Karin Weber

We analyzed urine samples from 191 cats for bacteriuria with an automated urine sediment analyzer (Idexx SediVue Dx), combined with image review by an observer, and compared to bacteriologic culture results. Sixty-nine samples were unambiguously assigned to be free of bacteria by the instrument and the observer, and no bacterial growth was detected. Twenty-seven samples were unambiguously assigned to have bacteriuria; 24 of these 27 samples were culture-positive. For these samples, bacteriuria was predicted with a sensitivity of 100% and a specificity of 96%. A clear assignment was not possible for 95 samples, 81 of which were culture-negative. Specificity dropped to 45% when all samples were considered. Using the automated leukocyte count to predict bacteriuria, sensitivity was 82% and specificity was 75%. Automated sediment analysis is faster and less observer-dependent than sediment analysis under a microscope, but accurate detection of bacteriuria remains difficult in a large proportion of samples. Bacteriuria was significantly associated with leukocyte count; the leukocyte count was >5/high power field in 82% of culture-positive samples.


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