Abstract

To compare two manual methods for estimating platelet counts from Wright's stained peripheral blood smears regarding their correlation with each other and with automated platelet counts. This correlation was examined in relation to whether the platelet count was high, low, or normal and in relation to whether the hemoglobin value was low versus normal or high. Peripheral blood smears were Wright's stained and both platelet count estimation methodologies were performed on each slide. The traditional estimation method was the average number of platelets per oil immersion field (OIF) multiplied by 20,000 to yield a platelet count estimate per uL. The alternate estimation method was the average number of platelets per OIF multiplied by the patient's hemoglobin value in g/dL and then multiplied by 1,000 to yield a platelet count estimation per uL. The platelet count estimates were performed without the technologists having prior knowledge of the automated platelet counts which were produced on a Coulter LH750 analyzer. The agreement between the two manual methodologies with each other and each method with the automated count was assessed using the paired T-test and correlation coefficient analyses. These analyses were performed for the whole dataset as well as for subsets based on the automated platelet count and the hemoglobin value. East Carolina University's Clinical Laboratory Science program in collaboration with the Clinical Pathology/Laboratory at Pitt County Memorial Hospital (PCMH) in Greenville NC. One hundred eighty-four blood samples in EDTA-anticoagulant VacutainerI tubes were used to conduct this study. Each blood sample had two peripheral blood smears made and stained on an automatic slide stainer. The blood samples were obtained from the Clinical Pathology/Laboratory of Pitt County Memorial Hospital in October and November of 2004. Each sample was given a unique numeric identifier with no personal identifying information from any sample being recorded. Platelet counts by two slide estimation methods and by an automated reference method. The traditional platelet count estimation method had a mean for the sample of 269,000/uL, while the alternate estimation method had a mean of 155,000/uL. The mean for the automated platelet counts was 268,000/uL. The traditional estimation method showed no statistically significant difference in mean from the automated platelet counts based on the paired T-test (p = 0.87). The traditional estimation method counts and automated counts had a high Pearson Product Moment correlation coefficient of r = .90 and a minimally dispersed scatterplot, thus showing strong agreement. The alternate platelet count estimation method had a mean for the sample of 155,000/uL which, based on the paired T-test, was highly significantly different from the automated count mean (p < 0.0001) and the traditional estimation method mean (p < 0.0001). The alternate estimation method and automated counts had a lower r value of .81 and greater dispersion in the scatterplot. In comparing the estimation methods with each other and with the automated method, the differences and similarities in agreement observed for the whole dataset were also observed with each platelet count and hemoglobin subset of data. Though the alternate platelet count estimation method has been recommended for use particularly with patients with low hemoglobin values, this study found that the traditional estimation method provided more agreement with automated counts than did the alternate estimation method for all samples as well as for the subset of samples with low hemoglobin values. For the present, the traditional method of estimating platelet counts from blood smears to evaluate automated results appears to provide adequate quality assurance.

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