Technology and new fluorescence flow cytometry parameters in hematological analyzers

Neutrophil Reactivity Intensity and misclassification of immature granulocytes

INTRODUCTION

Immature granulocyte percentage (IG%) is an important biomarker for infection control. We observed spurious cases where the IG% was dramatically underestimated on the automated Sysmex XN-series hehmatology analyzer compared with manual differential. These cases were associated with high values of "Neutrophil Reactivity Intensity" (NEUT-RI), which should reflect the metabolic activity of the neutrophils.

METHODS

We conducted a three-stage study to evaluate whether NEUT-RI could be utilized to screen for misclassified IG% results defined as the manual differential estimating a 10 percentage points higher IG% compared with the automated Sysmex differential. First, 124 patient samples were selected for 800-cell manual smear analysis based on their NEUT-RI values and compared with the automatic Sysmex IG% results. Next, 11 098 routine 110-cell manual smear analyses were compared with the corresponding Sysmex IG% results. Finally, during a 19-day period 160 additional patient samples underwent smear based on NEUT-RI values ≥56 fluorescence intensity (FI) to screen for misclassified results beyond our current smear practice.

RESULTS

NEUT-RI ≥56 predicted IG% misclassification with 91% sensitivity and 88% specificity, but primarily when the internal Sysmex flag "Abnormal WBC Scattergram" was present. 90.1% of misclassified results were identified by this flag. Beyond our existing smear rules including this flag, NEUT-RI ≥56 FI had a positive predictive value below 1%.

CONCLUSION

Both NEUT-RI and the internal Sysmex flag "Abnormal WBC Scattergram" work well to identify cases of IG% misclassification. However, in our setting NEUT-RI ≥56 FI had no meaningful additional predictive capacity to identify misclassifications beyond our current smear rules.

Comprehensive quantitative analysis of erythrocytes and leukocytes using trace volume of human blood using microfluidic-image cytometry and machine learning

A diagnostic test based on microfluidic image cytometry and machine learning has been designed and applied for accurate classification of erythrocytes and leukocytes, including a unique fully-automated 5-part quantitative differentiation into neutrophils, lymphocytes, monocytes, eosinophils, and basophils, using minute amounts of whole blood in a single counting chamber. A low-cost disposable multilayer microdevice for microfluidic image cytometry was developed that comprises a 1 mm × 22 mm × 70 μm (w × l × h) rectangular microchannel, allowing the analysis of trace volume of blood (20 μL) for each assay. Automated analysis of digitized binary images applying a border following algorithm was performed allowing the qualitative analysis of erythrocytes. Bright-field imaging was used for the detection of erythrocytes and fluorescence imaging for 5-part differentiation of leukocytes after acridine orange staining, applying a convolutional neural network enabling unparalleled speed for identification and automated morphology classification yielding 98.57% accuracy. Blood samples were obtained from 30 volunteers and count values did not significantly differ from data obtained using a commercial automated hematology analyzer.

Cord blood neutropenia is an independent predictor of early sepsis

OBJECTIVE

The significance of cord blood neutropenia as a screening tool for early-onset sepsis (EOS) is unclear. The objectives were to define reference values for cord blood neutrophil count and to determine the sensitivity and positive likelihood ratio of cord neutropenia for the detection of EOS.

STUDY DESIGN

This retrospective observational cohort study included all mother-infant pairs with deliveries between 2009 and 2014 for whom cord neutrophil counts were routinely done. EOS cases were identified by interrogation of electronic charts. Maternal and perinatal factors were assessed to determine reference values of cord neutrophil. The diagnostic value of neutropenia for detecting EOS was assessed. A nested case-control design was used to measure the value of neutropenia in the detection of EOS in comparison with other risk factors.

RESULTS

A total of 8,590 mother-infant pairs were included. We identified 84 sepsis cases. The neutrophil count was strongly associated with gestational age. Neutropenia adjusted for gestational age was strongly associated with EOS and had good specificity but poor sensitivity. The addition of neutropenia to other EOS risk factors increased sensitivity without decreasing specificity.

CONCLUSION

Cord blood neutropenia was significantly associated with EOS and the addition of cord neutropenia to current EOS risk factors increased the detection rate of EOS.

Evaluation of the Flagging Performance of the Hematology Analyzer Sysmex XN Series on the Basis of “Q Values”

Context.—

In the XN series of hematology analyzers (Sysmex, Kobe, Japan), the probability of the presence of abnormal cells is indicated by flags based on Q values.

Objective.—

To evaluate the Q value performance of the Sysmex XN-20 modular analyzer.

Design.—

The interinstrumental concordance, intrainstrumental precision, and diagnostic accuracy of Q values, with tested flags of “blasts/abnormal lymphocytes,” “atypical lymphocytes,” and “blasts,” were investigated.

Results.—

Absolute concordance rates in flagging between 2 analyzers ranged from 69.8% to 80.8%, and κ values ranged from 0.43 to 0.61. In samples with absolute related cell counts lower than 100/μL, the values ranged from 0.31 to 0.52. For intrainstrumental precision, standard deviations ranged from 4.8 to 23.9 for the blasts/abnormal lymphocytes, from 18.7 to 59.1 for the blasts, and from 11.0 to 23.0 for the atypical lymphocytes. Using a default Q value cutoff, diagnostic accuracy values based on the area under the curve, sensitivity, and specificity were, respectively, 0.910, 90.9%, and 72.2% for blasts/abnormal lymphocytes; 0.927, 84.9%, and 89.8% for blasts; and 0.865, 74.4%, and 84.9% for atypical lymphocytes. The diagnostic accuracy of Q values was much lower in samples with absolute related cell counts lower than 100/μL than in those 100/μL or higher.

Conclusions.—

Q values of the Sysmex XN-20 analyzer were found to be imprecise and irreproducible, especially with samples containing a small number of pathologic cells. Adjustments in the Q value threshold may help in the detection of these cells.

Clinical chorioamnionitis at term VII: the amniotic fluid cellular immune response

OBJECTIVES

1) To characterize the cellular composition of the amniotic fluid of patients diagnosed with clinical chorioamnionitis at term, as a function of the presence or absence of microorganisms determined by cultivation techniques, and 2) to characterize the cytokine production by white blood cells present in the amniotic fluid using flow cytometry-based techniques.

MATERIALS AND METHODS

Amniotic fluid samples from 20 women who had the diagnosis of clinical chorioamnionitis at term were analyzed using cultivation techniques (for aerobic and anaerobic bacteria as well as genital Mycoplasmas). Amniotic fluid IL-6 concentrations were determined by an enzyme-linked immunosorbent assay. Amniotic fluid leukocytes were visualized by using hematoxylin and eosin staining and immunofluorescence. Immunophenotyping of surface markers and cytokines was performed in amniotic fluid leukocytes using flow cytometry.

RESULTS

1) Neutrophils (CD45+CD15+ cells) were the most common leukocyte subset found in the amniotic fluid, followed by monocytes (CD45+CD14+ cells); other white blood cells (such as lymphocytes and natural killer cells) were scarce in the amniotic fluid; 2) the absolute counts of neutrophils and monocytes were significantly higher in patients with microorganisms found in the amniotic fluid than in those without detectable microorganisms, using cultivation techniques; 3) there was a significant correlation between the absolute counts of neutrophils and monocytes determined by flow cytometry (Spearman's correlation=0.97; P<0.001); 4) there was a significant correlation between the absolute white blood cell count determined with a hemocytometer chamber and by flow cytometric analysis (Spearman's correlation=0.88; P<0.001); and 5) the profile of cytokine expression differed between monocytes and neutrophils; while neutrophils predominantly produced TNF-α and MIP-1β, monocytes expressed higher levels of IL-1β and IL-1α.

CONCLUSION

Flow cytometry analysis of the amniotic fluid of patients with intra-amniotic infection and clinical chorioamnionitis at term demonstrated that neutrophils and monocytes are the most common cells participating in the inflammatory process. We have characterized, for the first time, the differential cytokine expression by these cells in this important complication of pregnancy.

Assessment of the Reliability of the Sysmex XE-5000 Analyzer to Detect Platelet Clumps

OBJECTIVE

Platelet counts generated by automated analyzers on blood specimens that contain platelet clumps are often inaccurate and require verification by blood-smear review. In this study, we assessed the reliability of the Sysmex XE-5000 instrument to detect platelet clumps.

METHOD

We reviewed automated complete blood count (CBC) results and the findings of the microscopic review of corresponding blood smears of 600 blood specimens specifically selected from the routine laboratory workload. The sensitivity, specificity, efficiency, positive predictive value (PPV), and negative predictive value (NPV) of its 2 platelet-associated flags (abnormal platelet-size distribution [PAD] flag and platelet-clumps [CLP] flag) were determined.

RESULTS

The respective values for the sensitivity, specificity, efficiency, and PPV were 42%, 83%, 63%, and 1% for the PAD flag and 57%, 99%, 78%, and 37% for the CLP flag. The NPV was 100%.

CONCLUSION

The overall reliability of the CLP flag is superior than that of the PAD flag but there is room for further improvement.