Background: Measurement of reticulocyte hemoglobin equivalent (RET-He) is rapid, convenient, and cost-effective. Yet, researches on its performance in diagnosing iron deficiency with concurrent inflammation are limited. Hence, this study investigated RET-He value in various states, including inflammation, and evaluated its diagnostic performance in iron status assessment.Methods: Retrospectively, 953 clinical data and laboratory results-complete blood count, reticulocyte count, RET-He, and serum ferritin-were reviewed. Patients on iron therapy were excluded. Iron status was defined by serum ferritin as the reference method. RET-He among populations was investigated. Its diagnostic performance and optimal cutoff were determined by ROC analysis.Results: Three population groups were classified: healthy control, iron deficiency anemia (IDA), and non-ID anemia. Significantly, RET-He value in IDA was lower than that of healthy control, anemia of inflammation, and chronic kidney disease (P < .0001).Low RET-He was also observed in IDA with concomitant inflammation despite normal-to-high serum ferritin levels. No significant difference was observed between RET-He values in pure IDA and thalassemia (P = .57). ROC curve analysis revealed AUC of 0.876 (P < .0001) at cutoff 30 pg, by which IDA was discriminated with 74.2% sensitivity and 97.4% specificity. Applying cutoff ≤30 pg, IDA can be diagnosed with 96% sensitivity, 97.4% specificity, 80% PPV, and 99.6% NPV. Hence, RET-He >30 pg signifies a non-IDA state. Conclusion:In addition to convenience and cost-effectiveness, RET-He cutoff >30 pg can be potentially used to exclude IDA due to its excellent diagnostic sensitivity and specificity.

No abstract

Background: The manual differential count has been recognized for its disadvantages, including large interobserver variability and labor-intensiveness. In this light, automated digital cell morphology analyzers have been increasingly adopted in hematology laboratories for their robustness and convenience. This study aims to evaluate the white blood cell differential performance of the Mindray MC-80, the new automated digital cell morphology analyzer. Materials and Methods:The cell identification performance of Mindray MC-80 was evaluated for sensitivity and specificity using preclassification and post-classification of each cell class. The method comparison study used manual differentials as the gold standard for calculating Pearson correlation, Passing-Bablok regression, and Bland-Altman analysis. In addition, the precision study was performed and evaluated.Results: Overall, the accuracy and specificity of cell identification were higher than 95% for all cell classes. The sensitivity was greater for 95% for most cell classes except for blast cells (86.1%), immature granulocytes (83.1%), reactive lymphocytes (79.6%), and plasma cells (25.0%). Preclassification and postclassification results correlated well with the manual differential results for all the cell types investigated. The regression coefficients were greater than 0.9 for most cell classes except for basophils and reactive lymphocytes. The precision of all normal WBC and abnormal cell classes were within the acceptable limit. Conclusion:The performance of Mindray MC-80 for WBC differentials is reliable and seems to be acceptable. However, the sensitivity is less than 90% for the certain abnormal cell types so the user should be aware of this limitation where the presence of such cells is suspected.