Minjeong Nam , M.D., Ph.D., Sumi Yoon , M.D., Mina Hur , M.D., Ph.D., Gun Hyuk Lee , M.D., Hanah Kim , M.D., Ph.D., Mikyoung Park , M.D., Ph.D., and Hyeong Nyeon Kim , M.D.. Ann Lab Med 2022;42:398-405. https://doi.org/10.3343/alm.2022.42.4.398

Digital morphology (DM) analyzers are widely applied in clinical practice. It is necessary to evaluate performances of DM analyzers by focusing on leukopenic samples. We evaluated the analytical performance, including precision, of a Sysmex DI-60 system (Sysmex, Kobe, Japan) on white blood cell (WBC) differentials in leukopenic samples. In a total of 40 peripheral blood smears divided into four groups according to WBC count (normal, mild, moderate, and severe leukopenia; each group n = 10), we evaluated precision of WBC preclassificaiton by DI-60. %coefficients of variation (%CVs) of precision varied for each sample and for each cell class; the fewer cells per slide, the higher %CV. The overall specificity and efficiency were high for all cell classes except plasma cells (95.9–99.9% and 90.0–99.4%, respectively). The largest absolute value of mean difference between DI-60 and manual count in each group was: 10.77, normal; 10.22, mild leukopenia; 19.09, moderate leukopenia; 47.74, severe leukopenia. This is the first study that evaluated the analytical performance of DI-60 on WBC differentials in leukopenic samples as the main subject. DI-60 showed significantly different performance depending on WBC count. DM analyzers should be evaluated separately in leukopenic samples, even if the overall performance was acceptable.

Objectives: CellaVision DC-1 (DC-1, Sysmex, Kobe, Japan) is a newly launched digital morphology analyzer that was developed mainly for small to medium-volume laboratories. We evaluated the precision, qualitative performance, comparison of cell counts between DC-1 and manual counting, and turnaround time (TAT) of DC-1. Methods: Using five peripheral blood smear (PBS) slides spanning normal white blood cell (WBC) range, precision and qualitative performance of DC-1 were evaluated according to the Clinical and Laboratory Standards Institute (CLSI) EP15-A3, EP15-Ed3-IG1, and EP12-A2 guidelines. Cell counts of DC-1 and manual counting were compared according to the CLSI EP 09C-ED3 guidelines, and TAT of DC-1 was also compared with TAT of manual counting. Results: DC-1 showed excellent precision (%CV, 0.0–3.5%), high specificity (98.9–100.0%), and high negative predictive value (98.4–100.0%) in 18 cell classes (12 WBC classes and six non-WBC classes). However, DC-1 showed 0% of positive predictive value in seven cell classes (metamyelocytes, myelocytes, promyelocytes, blasts, plasma cells, nucleated red blood cells, and unidentified). The largest absolute mean differences (%) of DC-1 vs. manual counting was 2.74. Total TAT (min:s) was comparable between DC-1 (8:55) and manual counting (8:55). Conclusions: This is the first study that comprehensively evaluated the performance of DC-1 including its TAT. DC-1 has a reliable performance that can be used in small to medium-volume laboratories for assisting PBS review. However, DC-1 may make unnecessary workload for cell verification in some cell classes.

The performance of platelet (PLT) counting in thrombocytopenic samples is crucial for transfusion decisions. We compared PLT counting and its reproducibility between Mindray BC-6800Plus (BC-6800P, Mindray, Shenzhen, China) and Sysmex XN-9000 (XN, Sysmex, Kobe, Japan), especially focused on thrombocytopenic samples. We analyzed the correlation and agreement of PLT-I channels in both analyzers and BC-6800P PLT-O mode and XN PLT-F channel in 516 samples regarding PLT counts. Ten thrombocytopenic samples (≤2.0 × 10⁹/L by XN PLT-F) were measured 10 times to investigate the reproducibility with the desirable precision criterion, 7.6%. The correlation of BC-6800P PLT-I and XN PLT-I was arranged moderate to very high; but the correlation of BC-6800P PLT-O and XN PLT-F was arranged high to very high. Both BC-6800P PLT-I vs. XN PLT-I and BC-6800P PLT-O vs. XN PLT-F showed very good agreement (κ = 0.93 and κ = 0.94). In 41 discordant samples between BC-6800P PLT-O and XN PLT-F at transfusion thresholds, BC-6800P PLT-O showed higher PLT counts than XN-PLT-F, except the one case. BC-6800P PLT-O exceeded the precision criterion in one of 10 samples; but XN PLT-F exceeded it in six of 10 samples. BC-6800P would be a reliable option for PLT counting in thrombocytopenic samples with good reproducibility.

The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation is the most commonly used equation for estimated glomerular filtration rate (eGFR). Recently, the European Kidney Function Consortium (EKFC) announced a full-age spectrum equation, and the CKD-EPI announced the CKD-EPI refit equations (CKD-EPI-R). We compared CKD-EPI, EKFC, and CKD-EPI-R equations in a large-scale Korean population and investigated their potential implications for CKD prevalence. In a total of 106,021 individuals who received annual check-ups from 2018 to 2020, we compared the eGFR equations according to the Clinical and Laboratory Standards Institute guidelines. Weighted kappa (κ) agreement was used to compare the potential implications for CKD prevalence across the equations. The median value of eGFR tended to increase in the order of EKFC, CKD-EPI, and CKD-EPI-R equations (92.4 mL/min/1.73 m², 96.0 mL/min/1.73 m², and 100.0 mL/min/1.73 m², respectively). The EKFC and CKD-EPI-R equations showed a very high correlation of eGFR and good agreement for CKD prevalence with CKD-EPI equation (r = 0.98 and 1.00; κ = 0.80 and 0.82, respectively). Compared with the CKD-EPI equation, the EFKC equation overestimated CKD prevalence (3.5%), and the CKD-EPI-R equation underestimated it (1.5%). This is the first study comparing CKD-EPI, EKFC, and CKD-EPI-R equations simultaneously. The EKFC and CKD-EPI-R equations were statistically interchangeable with CKD-EPI equations in this large-scale Korean population. The transition of eGFR equations, however, would lead to sizable changes in the CKD prevalence. To improve kidney health, in-depth discussion considering various clinical aspects is imperative for the transition of eGFR equations.

Background and Objectives: The European Kidney Function Consortium (EKFC) equation has been newly proposed for estimating glomerular filtration rate (eGFR) across the spectrum of age. We compared the EKFC equation with the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations in a large-scale Korean population. Materials and Methods: Using the representative Korean health examination data, the Korea National Health and Nutrition Examination Survey (KNHANES 2008–2021), the records of 91,928 subjects (including 9917 children) were analyzed. We compared the EKFC equation with CKiD, CKD-EPI 2009, and CKD-EPI 2021 equations and investigated their agreement across GFR categories. Results: In the total population, the CKD-EPI 2021 equation yielded the highest eGFR value, followed by the CKD-EPI 2009 and EKFC equations. In children, the distribution of eGFR differed significantly between the EKFC and CKiD equations (p < 0.001), with a wider range of eGFR values found with the CKiD equation. Each equation showed weak or moderate agreement on the frequency of the GFR category (κ = 0.54 between EKFC and CKD-EPI 2021; κ = 0.77 between EKFC and CKD-EPI 2009). The eGFR values found by the EKFC equation showed high or very high correlations with those by the CKiD, CKD-EPI 2009, and CKD-EPI 2021 equations (r = 0.85, 0.97, and 0.97, respectively). As eGFR values increased, bigger differences were observed between equations. Conclusions: This large-scale study demonstrates that the EKFC equation would be applicable across the entire age spectrum in Asian populations. It also underscores that national kidney health would be highly affected by an eGFR equation being implemented. Additional investigation and more caution would be warranted for the transition of eGFR equations.