| Abstract|| |
Among the blood counts, platelet count is most often reported with inconsistency. Many of the analyzers work on electrical impedance principle for red blood cell (RBC) and platelet counting. However, with this technology, factors such as fragmented RBCs, microcytes, cytoplasmic fragments of leukemic cells, lipid particles, fungal yeast forms, and bacteria are known to interfere with platelet count and give spuriously elevated platelet counts. A 72-year-old male was admitted for the treatment of dengue infection who had serial platelet count monitoring. He had an initial platelet count of 48,000/cumm which suddenly improved to 2.6 lakhs within 6 h without any platelet transfusion. Peripheral smear however did not correlate with the machine-derived count. Repeat test after 6 h yielded a result of 56,000/cumm which correlated well with the peripheral smear. This falsely elevated count was due to the presence of lipid particles as the sample was drawn in the postprandial state.
Keywords: Electrical impedance analyser, microparticles, platelet count
|How to cite this article:|
Krishnamurthy V, Shivamurthy A, Kumar PV. Platelet count in impedance-based hematology analyzer: Beware of trap!. Asian J Transfus Sci 2023;17:131-2
|How to cite this URL:|
Krishnamurthy V, Shivamurthy A, Kumar PV. Platelet count in impedance-based hematology analyzer: Beware of trap!. Asian J Transfus Sci [serial online] 2023 [cited 2023 Mar 27];17:131-2. Available from: https://www.ajts.org/text.asp?2023/17/1/131/356894
| Introduction|| |
This communication is to highlight the importance of technology interference in platelet counting.
Chances of obtaining spurious results of blood counts are rare, if well-maintained modern autoanalyzers with regular quality control procedures are in service.
Among the blood counts, platelet count is most often reported with inconsistency. Small size and multiple interfering factors are reported to be responsible for this inconsistency.
Many of the analyzers work on electrical impedance principle for red blood cell (RBC) and platelet counting. Cells are primarily identified based on their size with automatic discriminators used to determine RBC and platelet counts. However, with this technology, factors such as fragmented RBCs, microcytes, cytoplasmic fragments of leukemic cells, lipid particles, fungal yeast forms, and bacteria are known to interfere with platelet count and give spuriously elevated platelet counts.,,,, Many analyzers do flag such an interference to alert the lab physicians.
| Case Report|| |
We report an interesting scenario of variable platelet counts in an elderly patient with viral fever in a tertiary care center. He is a 72-year-old male, admitted to our hospital for evaluation and treatment of suspected viral fever. Investigations suggested dengue with NS1 antigen positivity. Complete blood counts were done on Sysmex XN–1000 and his initial platelet count was 64,000/cumm. Platelet count had reduced to 48,000/cumm on repeat counting after 24 h. There was correlation of low platelet count on smear upon cross verification. Due to drop in platelet count, repeat count was requested after 6 h in the afternoon.
Estimated platelet count on this repeat sample was 2.6 lakhs/cumm. The laboratory information system detected this result to be crossing the set delta values and flagged the same. The sudden rise in the platelet count was cross verified with smear examination. It was both interesting and surprising to see platelets of the smear correlating with low platelet count reported in the morning and not with the present value. Hence, the sample was rerun in the same analyzer only to get similar spuriously high count of 2.78 lakh/cumm without any change in the smear. The sample was stored for root cause analysis, and the clinician was informed about the spurious result. Fresh sample was requested. A repeat sample was obtained in the evening about 4 h later. Platelet count on this fresh sample had dropped back to 56,000/cumm with good correlation on smear examination.
As a part of root-cause analysis, this issue was discussed with a hematology expert, and peripheral smear of the sample with spuriously elevated platelet count was re-examined. Good number of lipid droplets was found both in singles and in clumps [Figure 1]. On enquiring about the time of drawing of this sample and its relation to patients feed, it was realized that sampling was done couple of hours after the lunch.
|Figure 1: Peripheral smear showing lipid droplets (Enlarged in the inset). Leishman stain ×200|
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| Discussion|| |
There are several scientific reports regarding lipid particles interfering with the platelet counting. However, probably, it is first of its kind experienced and reported by a NABL-accredited laboratory of a tertiary care center during the root-cause analysis procedure of the spurious platelet counts in a single day, of a single patient, with discrepancy between analyzer values and that of smear examination.
Modern analyzers with inbuilt fluorescent flow cytometry techniques commonly employed for reticulocyte and platelet counting will not be affected by elements which are known to interfere platelet counting of impedance technology., Whenever such interference is suspected, platelet counting done with this principle may give a reliable and more accurate results than that with impedance technique. However, many laboratories may not have modern analyzer and still depend on impedance principle for platelet counts. This mandates the pathologist to go through the smear before reporting in order to ensure accuracy of the report.
Declaration of patient consent
The authors certify that they have obtained all appropriate patient consent forms. In the form, the patient has given his consent for his images and other clinical information to be reported in the journal. The patient understands that name and initials will not be published and due efforts will be made to conceal identity, but anonymity cannot be guaranteed.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Kim SY, Kim JE, Kim HK, Han KS, Toh CH. Accuracy of platelet counting by automated hematologic analyzers in acute leukemia and disseminated intravascular coagulation: Potential effects of platelet activation. Am J Clin Pathol 2010;134:634-47.
Baccini V, Geneviève F, Jacqmin H, Chatelain B, Girard S, Wuilleme S, et al
. Platelet counting: Ugly traps and good advice. Proposals from the French-Speaking Cellular Hematology Group (GFHC). J Clin Med 2020;9:808.
Balakrishnan A, Shetty A, Vijaya C. Estimation of platelet counts: Auto analyzer versus counts from peripheral blood smear based on traditional and platelet: Red blood cell ratio method. Trop J Path Micro 2018;4:389-95.
Frotscher B, Salignac S, Muller M, Latger-Cannard V, Feugier P, Lesesve JF. Interference of blast cell fragments with automated platelet counting. Int J Lab Hematol 2015;37:613-9.
Zandecki M, Genevieve F, Gerard J, Godon A. Spurious counts and spurious results on haematology analysers: A review. Part I: Platelets. Int J Lab Hematol 2007;29:4-20.
Harrison P, Ault KA, Chapman S, Charie L, Davis B, Fujimoto K, et al.
An interlaboratory study of a candidate reference method for platelet counting. Am J Clin Pathol 2001;115:448-59.
Tantanate C, Khowawisetsut L, Pattanapanyasat K. Performance evaluation of automated impedance and optical fluorescence platelet counts compared with international reference method in patients with thalassemia. Arch Pathol Lab Med 2017;141:830-6.
#70, Prakruthi, BEML 2nd Stage, Rajarajeshwari Nagara, Mysuru - 570 022, Karnataka
Source of Support: None, Conflict of Interest: None
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