Comparison of Automated Hematology Analyzer (XN 1000) Flags & Peripheral Blood Smear Examination: An Experience from a Tertiary Care Hospital

Abstract

Background: In the era of new automated hematology analysers, they analyze blood samples and highlight the abnormal results of complete blood abnormal count with flags. If these abnormal flags are accurate and reliable, the workload of a hematopathologist would decrease, and turnaround time would reduce significantly, besides aiding in the early diagnosis of certain disorders. Objective: To correlate abnormal flags of a six-part differential automated hematology analyzer with a peripheral smear study by a hematologist/pathologist. This study aims to determine the diagnostic accuracy of peripheral blood smears and automated hematology analyzers with abnormal flagging. Methodology: This retrospective cross‑sectional study was conducted in the hematology department of CHK Central Laboratory Dr Ruth KM Pfau Civil Hospital Karachi, from July 2022 to December 2022. Samples of 158 patients were included which showed flagging messages by automated hematology analyzer XN-1000. The flagging messages were analyzed with their respective PBS findings. Pearson’s Chi‑square test was used for the statistical analysis. Venous blood samples were collected in an EDTA tube for Complete blood count and were processed by the six-part differential automated hematology analyzer-Sysmex XN 1000. All age groups and genders were included. Results: Peripheral smears were reviewed in 158 samples from different departments; 112 were inpatient, and 46 were outpatient samples. In 129/158, the findings of the XN 1000 analyser correlated with the peripheral smear review. Flags identified included Anemia in 97(61%), leukocytosis 27(17%) immature white blood Cell/blast (WBC) 16(10.1%), thrombocytopenia 73(46.2%), and malaria 20(12.6%). Peripheral smear examination: Anemia in 102, Leukocytosis in 28, thrombocytopenia in 91, and malaria in 29 cases. Comparison of XN-1000 with peripheral blood smear findings shown in table 1. 17 False positive cases of platelet clumps were detected on XN analyzer, and smear detected only 07 cases of platelet clumps. Peripheral smear examination was found to be a more accurate and sensitive technique for the detection of morphological abnormalities. In 10.7% of the cases, the analyzer missed important findings. Conclusion: This study depicts that the flagging of abnormal findings is accurate but it should always be correlated with the PBS verified by a hematopathologist. We should analyze the suspect flags and use it as a screening tool to pick up pathological samples quickly.