Poor accuracy of the eosinophil count of hematology instruments limits the use of eosinopenia as a marker of bacterial infection or increased mortality

Sir, Over the last few years, there has been interest in using eosinopenia, that is, a low absolute eosinophil count (AEC), as a marker of bacterial infection or high risk of mortality [1–6]. To be able to use eosinopenia as a reliable marker in clinical practice, an accurate counting of low numbers of eosinophils is necessary. A commonly used lower reference limit for the AEC in peripheral blood is 0.05 9 10/L [7]. Previously, there is scarce data about the trueness and precision at low AECs. From statistical calculations and previous publications, it is known that the imprecision of leukocyte counts is increased when the number of counted leukocytes is low [8, 9]. The aim of this study was to evaluate the trueness and precision of the AEC in patient samples with low numbers of eosinophils. We compared AECs from 106 patients samples obtained from the hematology instruments Advia 2120i and Sysmex XE-2100 with a flow cytometric (FCM) eosinophil count using fluorescentlabeled antibodies for classification of cells. Residuals from 106 patient samples submitted for white blood cell differential count (K2EDTA-anticoagulated tubes, Med-kjemi, Asker, Norway) at Oslo University Hospital, Ullevaal, with an absolute neutrophil count (ANC) <2.0 9 10/L were collected in the period January–April 2011. This study was originally designed to evaluate the analytical quality of the ANC in samples with low neutrophil counts [9], but many of the samples also had low AECs. The project was approved by the regional ethical committee. The reagents used in the study have been previously described in our study on the performance of hematology instrument ANCs [9]. The AEC was performed in duplicate within 8 h from blood collection as part of the 5-part differential count on Advia 2120i (Siemens healthcare diagnostics, Deerfield, IL, USA) and Sysmex XE-2100 (Sysmex Corporation, Kobe, Japan). The lower limits of the analytical range for the instruments as stated by the manufactures were 0.02 9 10/L and 0.00 9 10/L, respectively. For the FCM analysis, whole blood (50 lL) was (within 10 h from blood collection) added to a freshly made antibody mixture (9.5 lL) and incubated in dark at room temperature (RT) for 30 min. Erythrocytes were then lysed using 500 lL ammonium chloride lysis buffer (15 min, RT). To enable absolute cell counts, Countbright beads (50 lL) were added to the samples and then the tubes were placed on ice and analyzed within 1 h. The samples were acquired on a Cyan ADP flow cytometer (Beckman Coulter, Fullerton, CA, USA). At startup, the instrument was checked with Sphero Ultra rainbow particles and photomultiplier tube settings (PMTs) were standardized using Flow set pro fluorospheres. Excitation was by 405 nm (UV laser), 488 nm (Argon laser), and 635 nm (red laser). BD CompBeads were acquired with the same PMT settings as the samples, and compensation was calculated automatically. Forward Scatter and Side Scatter (SS) were acquired in linear mode, and the fluorescence parameters were acquired in logarithmic mode. The samples were acquired with an acquisition trigger on CD45 APC at a flow rate of maximum 500 events per second. The data were acquired and analyzed using SUMMIT software v4.3 (Summit software, Little Rock, AR, USA). Eosinophils were identified as CD45+/CD193+/ CD16 and high SS as previously described [9]. The International Council for Standardization in Hematology (ICSH) is currently developing a FCM reference method for the leukocyte differential count and has recently published an article comparing three candidate methods [10]. All three methods identified eosinophils as cells with high SS and high CD45 expression after exclusion of CD16+ mature neutrophils. In this study, we compared the ICSH gating strategy with our gating strategy that also included CD193 as an eosinophil marker. Statistical analysis was performed with GRAPHPAD PRISM 6.02 software (La Jolla, CA, USA). Correlation coefficients were determined using two-tailed Pearson test. Bias between the hematology instruments and FCM was examined using paired t-test. The within-run coefficient of variation (CV) were calculated using the results from