Application of the Fluorescence Method on Sysmex XN9000 Hematology Analyzer for Correcting Platelet Count in Individuals with Microcytosis.

OBJECTIVE: Although small red blood cells are a well-known analytical pitfall that could cause artifactual increase of the platelet count, limited information is available on the accuracy of impedance platelet counting in cases with microcytosis. The aim of this study is to assess the accuracy of impedance platelet counting in the presence of small red blood cells, and to establish the optimal mean corpuscular volume (MCV) cutoff to endorse fluorescence platelet counting. METHODS: In this study, platelet counts estimated by the impedance method on the Sysmex XN9000 analyzer (Sysmex, Kobe, Japan) were compared with those provided by the fluorescence method. The accuracy of impedance platelet counting was assessed. Receiver operating characteristic curve was used to evaluate the performance of MCV in predicting falsely increased platelet counts. RESULTS: There was a tendency for the impedance method to overestimate the platelet count in samples with 70 fL < MCV ≤ 80 fL, 60 fL < MCV ≤ 70 fL, MCV ≤ 60 fL. Receiver operating characteristic curve analysis showed that a 73.5fL cutoff of MCV was highly sensitive in predicting falsely increased platelet counts. CONCLUSION: In cases with MCV < 73.5 fL, we strongly suggest that the platelet counts obtained by the impedance method on the Sysmex XN9000 analyzer should be checked and corrected by fluorescence counting.

Interchangeability of multiple Sysmex XN10 and XN20 modules for six types of leukocytes.

INTRODUCTION: Differential counts of leukocytes are frequent, and often several automated blood cell counters are needed in contemporary laboratories. However, these modules are often individually quality assured. Our aim was therefore to validate the interchangeability of five hematology modules in a large modern laboratory and to compare them with our gold standard (GS) manual white blood cell differential count. METHODS: At Copenhagen University Hospital, we compared five Sysmex XN-modules for neutrophils, lymphocytes, monocytes, eosinophils, basophils, and immature granulocytes (IG). We analyzed control samples in three levels to evaluate intra- and intermodular precision. Bias between modules was evaluated by analyzing 93 random patient samples within reference intervals. XN-modules' mean counts were compared with GS. RESULTS: We found acceptable intramodular CV% (0.92%-8.76%), only neutrophils and eosinophils exceeded state-of-the-art imprecision or desirable specifications for medium control levels. Intermodular CV% showed significance difference for only monocytes (ANOVA, P < .0001). For patient samples, there were significant differences between XN-modules regarding four WBC types (ANOVA); however, proportional bias ranged from 1.7% to 3.8%, being within desirable specifications except basophils and IG (bias = 13.3% and 24.9%, respectively). Comparisons with GS, XN-modules exceeded desirable bias for basophils (lower than GS); monocytes and IG (higher than GS). CONCLUSION: This multimodule comparison shows acceptable intermodular imprecision and bias for clinical purposes, which is important for patient safety. Similar multimodule study should be performed with samples out of reference range in large-scale laboratories to confirm the interchangeability.

Vivax malaria detection using a parasitic red blood cell flag generated by the Sysmex XN-9000 hematology analyzer.

INTRODUCTION: A Sysmex XN-series hematology analyzer (Sysmex), the next generation up from the Sysmex XE-series, can provide information regarding malaria infection in the form of a parasitic red blood cell (pRBC) flag. This study aimed to determine the usefulness of the pRBC flag for early detection and follow-up in patients infected with Plasmodium vivax. METHODS: A total of 221 patients with fever for whom CBC and malaria microscopy had been requested were analyzed. Sixty-seven individuals were diagnosed with P vivax infection, and 154 were diagnosed with other febrile diseases. The sensitivity and specificity of the pRBC flag for malaria parasite detection and the relationship between parasite density and presence of the pRBC flag were determined. The concordance rate between malaria microscopy and pRBC flag in 147 follow-up cases was calculated. RESULTS: The pRBC flag was detected in 56 of 67 malaria patients (sensitivity, 83.6%; specificity, 100%). The patients with the pRBC flag at initial diagnosis revealed significantly higher parasite density than the patients without the pRBC flag (P < .05). The concordance rate between malaria microscopy and pRBC flag in the follow-up cases was 53.1%. CONCLUSION: Considering its high sensitivity in malaria-suspicious patients, unexpected vivax malaria cases can be detected with the pRBC flag when CBC is done in a routine laboratory setting. The pRBC flag provided by the Sysmex XN series is a valuable tool for vivax malaria detection.

Use of the reticulocyte channel warmed to 41 °C of the XN-9000 analyzer in samples with the presence of cold agglutinins

ABSTRACT Objectives The purpose of this study was to compare data obtained from the reticulocyte channel (RET channel) heated to 41 °C with those obtained from impedance channel (I-Channel) at room temperature in the samples with the mean corpuscular hemoglobin concentration (MCHC) < 370 g/L and in samples with the MCHC > 370 g/L, in the presence of cold agglutinins. Methods In this study, 60 blood samples (group 1) with the MCHC < 370 g/L (without cold agglutinins) and 78 blood samples (group 2) with the MCHC > 370 g/L (with cold agglutinins) were used to compare the two analytical channels of the XN-9000 analyzer in different preanalytical conditions. The parameters evaluated in both groups were the following: red blood cell (RBC), hemoglobin (HGB), hematocrit (HCT), mean cell volume (MCV), RBC-most frequent volume (R-MFV), mean hemoglobin concentration (MCH) and mean cellular hemoglobin concentration (MCHC). Results The results of this study showed an excellent correlation with both channels of the XN-9000 analyzer in samples with and without cold agglutinins, except for the MCHC. The bias between the values obtained in the I-channel and those obtained in the RET channel of both groups was insignificant and remained within the limits of acceptability, as reported by Ricos et al. for all considered parameters, except for MCHC. Conclusions The presence of cold agglutinins in blood samples can be detected by a spurious lowering of the RBC count and by a spurious increase in the MCHC. The RET channel represents a great opportunity to correct the RBC count in a rapid manner without preheating. However, neither methodology can completely solve the residual presence of cold agglutinins in all samples, despite the MCHC values being < 370 g/L.

Use of the reticulocyte channel warmed to 41°C of the XN-9000 analyzer in samples with the presence of cold agglutinins.

OBJECTIVES: The purpose of this study was to compare data obtained from the reticulocyte channel (RET channel) heated to 41°C with those obtained from impedance channel (I-Channel) at room temperature in the samples with the mean corpuscular hemoglobin concentration (MCHC)<370g/L and in samples with the MCHC>370g/L, in the presence of cold agglutinins. METHODS: In this study, 60 blood samples (group 1) with the MCHC<370g/L (without cold agglutinins) and 78 blood samples (group 2) with the MCHC>370g/L (with cold agglutinins) were used to compare the two analytical channels of the XN-9000 analyzer in different preanalytical conditions. The parameters evaluated in both groups were the following: red blood cell (RBC), hemoglobin (HGB), hematocrit (HCT), mean cell volume (MCV), RBC-most frequent volume (R-MFV), mean hemoglobin concentration (MCH) and mean cellular hemoglobin concentration (MCHC). RESULTS: The results of this study showed an excellent correlation with both channels of the XN-9000 analyzer in samples with and without cold agglutinins, except for the MCHC. The bias between the values obtained in the I-channel and those obtained in the RET channel of both groups was insignificant and remained within the limits of acceptability, as reported by Ricos et al. for all considered parameters, except for MCHC. CONCLUSIONS: The presence of cold agglutinins in blood samples can be detected by a spurious lowering of the RBC count and by a spurious increase in the MCHC. The RET channel represents a great opportunity to correct the RBC count in a rapid manner without preheating. However, neither methodology can completely solve the residual presence of cold agglutinins in all samples, despite the MCHC values being < 370g/L.

Performance of Platelet Counting in Thrombocytopenic Samples: Comparison between Mindray BC-6800Plus and Sysmex XN-9000.

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.

Performance evaluation of platelet counting of Abbott Alinity hq and Sysmex XN-9000 automated hematology analyzer compared with international reference method.

INTRODUCTION: Accurate platelet counting is essential for risk assessment of bleeding and thrombosis. Abbott Alinity hq hematology analyzer was recently introduced, and its performance in platelet counting has yet to be evaluated comprehensively. In this study, we evaluated the performance of the optical platelet counting of Abbott Alinity hq (Alinity-PLT) and the impedance and fluorescent platelet counting of Sysmex XN-9000 (XN-PLT-I and XN-PLT-F) compared with the international reference method. METHODS: Blood samples were analyzed via Alinity hq and XN-9000 with PLT-F channel. Immuno-platelet (ImmnoPLT) reference method was performed with CD41/CD61 antibodies using FACSLyricTM flow cytometer (BD). Precision was determined using 10 replicates in a single run, and the platelet counts of Alinity-PLT, XN-PLT-I, XN-PLT-F, and ImmnoPLT were compared. RESULTS: At a platelet count of 13 × 109 /L, the CVs of Alinity-PLT, XN-PLT-I, and XN-PLT-F were 4.2%, 6.7%, and 4.3%, respectively, and at a platelet count of 44 × 109 /L, all showed a CV of less than 3%. For the total 210 samples, all three methods showed a very strong correlation with ImmunoPLT (r > 0.99). For platelet levels below 20 × 109 /L, XN-PLT-F showed the strongest correlation with ImmunoPLT (r = 0.975), and for platelet levels of 20-100 × 109 /L, Alinity-PLT and XN-PLT-I were comparable to ImmunoPLT. For platelet levels of 100-450 × 109 /L, XN-PLT-I was the most comparable to ImmunoPLT, and for platelet levels above 450 × 109 /L, Alinity-PLT was comparable to ImmunoPLT. CONCLUSIONS: All three methods were highly correlated with ImmunoPLT, and each method had different performance advantages according to the platelet levels.

Abnormal dot plots on current automated blood cell analyzer helped to yeast detection.

Compromised data are usually flagged by instruments. This is the first report of yeast detection using the new launched Sysmex XN analyzer.

Performance evaluation of the new measurement channels on the automated Sysmex XN-9000 hematology analyzer.

BACKGROUND: The automated Sysmex XN-9000 hematology system has been designed to meet the throughput and efficiency requirements of high volume laboratories with predominantly abnormal samples. New measurement channels have been introduced namely the white cell nucleated (WNR), white cell differential (WDF), white cell precursor (WPC) and fluorescent platelet (PLT-F) channels. METHODS: The performance of the new measurement channels was evaluated with regards to precision, accuracy, linearity, carryover, throughput and stability. 275 slides were assessed for morphology flagging. Adult and pediatric samples with normal and abnormal hematology profiles were included. RESULTS: The XN-9000 demonstrated acceptable imprecision, good linearity for high and low ranges and no carryover. The full blood count and reticulocyte on the XN-9000 correlated well with the reference ADVIA(2)120. The PLT-F (127±84×109/l) compared with the optical platelet count (131±76×109/l) (r=0.97) and the imprecision was <4% on thrombocytopenic samples. The low white blood cell (WBC) mode reported accurate differentials for samples with a WBC count<0.5×109/l (r=0.93). The nucleated red blood cell count from the WNR (1.22±3.96%) showed an excellent correlation with the manual method (1.12±4.79%) (r=0.99). The WPC channel showed 100% sensitivity for the detection of blasts and abnormal lymphocytes. Further, the WPC correctly suppressed the initial blast/abnormal lymphocyte flag in 34% of the reflexed samples. CONCLUSION: The XN-9000 showed enhanced analytical performance and workflow efficiency for a wide range of patient samples which can be attributed to the incorporation of new measurement channels.

Analytical comparison between two hematological analyzer systems: CAL-8000 vs. XN-9000.

INTRODUCTION: This study was aimed to compare the analytical performance of traditional and new parameters and morphological flags of CAL-8000 and XN-9000. The automated differential leukocyte count (DIFF profile) and morphological flags were compared with optical microscopy (OM). METHODS: A total of 1025 peripheral blood samples, collected in K3 EDTA tubes, were analyzed by CAL-8000, by XN-9000, and by OM. Within-run imprecision was performed in low cellularity samples. The comparison was made using Spearman's correlation, Passing-Bablok regression, Bland-Altman bias, and Cohen's K test. RESULTS: Within-run imprecision in low cellularity samples yielded reproducible data between the instruments (imprecision was higher than 10% on samples with platelet count <21 × 109 /L using impedance technology). Passing-Bablok regression (CAL-8000 vs. XN-9000) yielded slopes ranging between 0.2 to 1.16 and intercepts from -6.54 to 21.63. The bias for leukocytes parameters ranged from -1.8% to -82.2%, the red blood cell parameters from -2.9% to 3.1%, platelets parameters from -27.8% to 26%, and reticulocyte parameters from -115.3% to 4.5%. The comparison of morphological flags yielded a K value always <0.55. The DIFF profile vs. OM had a Passing-Bablok regression with slopes ranging between 0.34 to 1.00 and intercepts from -0.01% to 0.11 and bias ranging from -42.9% to 2.6% for XN-9000 parameters and from -2.7% to 35.0% for CAL-8000 parameters. The comparison of morphological flags showed a K value ranging from 0.35 to 0.77 for XN-9000 and from 0.17 to 0.54 for CAL-8000. CONCLUSION: Differences exist between the two analyzers, especially in the generation of morphology flags, thus emphasizing the need of pursuing a major degree of harmonization and/or adopting instrument-specific reference ranges.

Assessment of blood sample stability for complete blood count using the Sysmex XN-9000 and Mindray BC-6800 analyzers.

BACKGROUND: Different hematological analyzers have different analytical performances that are often reflected in the criteria for sample stability of the complete blood count. This study aimed to assess the stability of several hematological parameters using the XN-9000 Sysmex and BC-6800 Mindray analyzers. METHODS: The impact of storage at room temperature and 4°C was evaluated after 2, 4, 6, 8, 24, 36 and 48h using ten normal and 40 abnormal blood samples. The variation from the baseline measurement was evaluated by the Steel-Dwass-Critchlow-Fligner test and by Bland-Altman plots, using quality specifications and critical difference as the total allowable variation. RESULTS: Red blood cells and reticulocyte parameters (i.e. hematocrit, mean corpuscular volume, mean corpuscular hemoglobin concentration, red blood cell distribution width, immature reticulocyte fractions, low-fluorescence reticulocytes, middle-fluorescence reticulocytes, high fluorescence mononuclear cells) showed less stability compared to leukocyte and platelet parameters (except for monocyte count and mean platelet volume). The bias for hematocrit, mean corpuscular volume, mean corpuscular hemoglobin concentration and red blood cell distribution width coefficient of variation was higher than the critical difference after 8h using both analyzers. CONCLUSION: Blood samples measured with both analyzers do not show analytically significant changes in up to 2h of storage at room temperature and 4°C. However, the maximum time for analysis can be extended for up to 8h when the bias is compared to the critical difference.

Assessment of blood sample stability for complete blood count using the Sysmex XN-9000 and Mindray BC-6800 analyzers

Background: Different hematological analyzers have different analytical performances that are often reflected in the criteria for sample stability of the complete blood count. This study aimed to assess the stability of several hematological parameters using the XN-9000 Sysmex and BC-6800 Mindray analyzers. Methods: The impact of storage at room temperature and 4 ◦C was evaluated after 2, 4, 6, 8, 24, 36 and 48h using ten normal and 40 abnormal blood samples. The variation from the baseline measurement was evaluated by the Steel­Dwass­Critchlow­Fligner test and by Bland­Altman plots, using quality specifications and critical difference as the total allowable variation. Results: Red blood cells and reticulocyte parameters (i.e. hematocrit, mean corpuscular volume, mean corpuscular hemoglobin concentration, red blood cell distribution width, immature reticulocyte fractions, low-fluorescence reticulocytes, middle-fluorescence reticulocytes, high fluorescence mononuclear cells) showed less stability compared to leukocyte and platelet parameters (except for monocyte count and mean platelet volume). The bias for hematocrit, mean corpuscular volume, mean corpuscular hemoglobin concentration and red blood cell distribution width coefficient of variation was higher than the critical difference after 8h using both analyzers. Conclusion: Blood samples measured with both analyzers do not show analytically signifi- cant changes in up to 2h of storage at room temperature and 4 ◦C. However, the maximum time for analysis can be extended for up to 8h when the bias is compared to the critical difference