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KMID : 0985420200420010026
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Laboratory Medicine and Quality Assurance
2020 Volume.42 No. 1 p.26 ~ p.32
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Comparison of Body Fluid Differential Counts Using a Manual Counting Method or an Automated Hematology Analyzer
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Lee Ji-Won
Jeon Ki-Bum
Lee Ji-Soo
Kim Mi-Young
Kim Han-Sung
Kang Hee-Jung
Lee Young-Kyung
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Abstract
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Background: Two methods of counting cells in body fluids were compared; manual counting using a Neubauer chamber, and automated cell counting using an XN-350 hematology analyzer.
Methods: Cells from 32 body fluid samples were counted by manual examination and by an automated analyzer. Total cells (TC), white blood cells (WBC), red blood cells (RBC), polymorphonuclear leukocytes (PMN), mononuclear leukocytes (MN), neutrophils, lymphocytes, monocytes, and eosinophils were each counted by both methods. The results were compared using the Pearson correlation test, Bland-Altman regression analysis, and Passing-Bablok regression analysis.
Results: The two methods showed very strong correlation in TC, WBC, RBC, PMN, and MN counts, strong correlation in % neutrophils, and % lymphocytes, and weak correlation in % monocytes and % eosinophils. Using Bland-Altman regression analysis, the mean biases for TC, WBC, and RBC were -270, -257.4, and -1,256.09, respectively, and 0.15 for PMN and MN. Research parameters were compared as well: mean biases were -1.31, -2.46, -5.16, and -3.58 for % neutrophils, % monocytes, % lymphocytes, and % eosinophils, respectively. Passing-Bablok regression equations were y=1.039x+20, y=1.037x+19, y=1.259x+0.0, y=0.983x+1.541, and y=0.983x+0.125 for TC, WBC, RBC, PMN, and MN, respectively. The equations were y=0.955x+2.194 for % neutrophils, y=0.965x+1.184 for % monocytes, y=1.003x+0.161 for % lymphocytes, and y=x+0.75 for % eosinophils.
Conclusions: WBC differential count results performed by an automated hematology analyzer generally show good correlation with our reference method, Neubauer chamber counting.
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KEYWORD
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Body fluids, Differential count, Automated hematology analyzer
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