title: Automated five-part white blood cell differential counts. Efficiency of software-generated white blood cell suspect flags of the hematology analyzers Sysmex SE-9000, Sysmex NE-8000, and Coulter STKS.
abstract: OBJECTIVE
  The present study evaluates the efficiency of software-generated white blood cell (WBC) "suspect flags" of the hematology analyzers Sysmex SE-9000, Sysmex NE-8000, and Coulter STKS.
  
  
  METHODS
  Automated WBC differential counts were considered positive if they contained any suspect WBC flag indicating the presence of blasts, myeloid precursor cells, or abnormal lymphocytes. Reference differential counts were performed by microscopic examination of 400 WBCs per sample. After comparison to the reference method, automated differential counts were classified as true-positive, true-negative, false-positive, and false-negative. The flagging efficiency of analyzers was expressed as a percentage of subjects correctly classified.
  
  
  METHODS
  Four hundred sixty-seven blood samples were randomly chosen for comparison analysis from various inpatient and outpatient departments of the Vienna university hospital, Austria.
  
  
  RESULTS
  The efficiency rates of flagging for the presence of > or = 1% abnormal WBCs were 78% (SE-9000), 77% (NE-8000), and 72% (Coulter STKS). The flagging efficiencies were best for samples with normal WBC counts. With regard to the specific suspect flags, the flagging of blast cells was most efficient on all analyzers.
  
  
  CONCLUSIONS
  Our results demonstrate the comparable overall performance of three analyzers, SE-9000, NE-8000, and Coulter STKS. They further underscore the importance of critical interpretation of automated differential counts, because at a detection limit of > or = 1% abnormal WBCs > 20% of samples were not correctly flagged by either analyzer.
authors.affiliation: Department of Laboratory Medicine, University of Vienna, Austria.
authors.forename: R
authors.initials: R
authors.lastname: Thalhammer-Scherrer
authors.forename: P
authors.initials: P
authors.lastname: Knöbl
authors.forename: L
authors.initials: L
authors.lastname: Korninger
authors.forename: I
authors.initials: I
authors.lastname: Schwarzinger
mesh_terms: D001317:Austria; D001322:Autoanalysis / Q000592:standards*; D001800:Blood Specimen Collection; D003936:Diagnosis, Computer-Assisted / Q000592:standards*; D004526:Efficiency; D005069:Evaluation Studies as Topic; D006405:Hematology / Q000295:instrumentation* / Q000592:standards*; D006801:Humans; D007958:Leukocyte Count / Q000379:methods*; D011237:Predictive Value of Tests; D011897:Random Allocation; D012016:Reference Values; D015203:Reproducibility of Results; D012984:Software