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Blast flagging of the Sysmex XN-10 hematology analyzer with supervised cell image analysis: Impact on quality
Jessica Petrone1, Ronald Jackups1, Charles S Eby1
1Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri.
Introduction:
The Sysmex XN-10 automated hematology analyzer (Sysmex Corporation) is routinely used in hematology laboratories to perform complete blood cell count with differential (CBC w/ diff). The sensitivity of this system for blast detection is unclear, since many prior studies evaluating the blast flagging capabilities of Sysmex XN series used the white precursor cell (WPC) channel, which is not cleared for use in the United States.
Methods:
We assessed the blast flagging capabilities of the Sysmex XN-10 compared with CellaVision (a cell image analyzer)-assisted visual hematology results. We evaluated the following flags: "blasts?/abnormal lymph?" and "immature granulocytes present" and compared differences in turnaround time between methods.
Results:
We collected data on 2239 CBC w/ diff Sysmex automated analyzer differential and CellaVision-assisted visual differential from the inpatient hematology-oncology population of a tertiary care medical center. Solely analyzing the first CBC/diff from each unique patient, both flags had a combined sensitivity of 100%, specificity of 50.2%, PPV of 21.7%, and NPV of 100%. The mean turnaround time for the automated differential was 19.5 minutes (SD 35.9 minutes) compared with 66.4 minutes for the CellaVision-assisted visual differential (SD 68.5 minutes; P < 0.001; Figure 1).
Conclusion:
The Sysmex XN-10 abnormal lymphocyte/blast and immature granulocytes flags had excellent sensitivity and acceptable specificity in detecting circulating blasts with shorter turnaround time than the CellaVision-assisted visual differential. Our study suggests that automated differentials performed on Sysmex XN-10 can replace visual differentials as a first-line screening method for blast detection with improved turnaround time in hematology-oncology populations.
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