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.
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.
Authors: Fatma Demet İnce; Hamit Yaşar Ellidağ; Mehmet Koseoğlu; Neşe Şimşek; Hülya Yalçın; Mustafa Osman Zengin Journal: Pract Lab Med Date: 2016-03-11