Performance evaluation of automated cell counts compared with reference methods for body fluid analysis.

OBJECTIVES: Cellular analysis of body fluids (BFs) can assist clinicians for the diagnosis of many medical conditions. The aim of this work is the evaluation of the analytical performance of the UF-5000 body fluid mode (UF-BF) analyzer compared to the gold standard method (optical microscopy, OM) and to XN-1000 (XN-BF), another analyzer produced by the same manufacturer (Sysmex) and with a similar technology for BF analysis. METHODS: One hundred BF samples collected in K3EDTA tubes were analyzed by UF-BF, XN-BF and OM. The agreement was evaluated using Passing and Bablok regression and Bland-Altman plot analysis. The receiver operating characteristic (ROC) curves were selected for evaluating the diagnostic agreement between OM classification and UF-BF parameters. RESULTS: Comparison between UF-BF and OM, in all BF types, showed Passing and Bablok's slope comprised between 0.99 (polymorphonuclear cells count, PMN-BF) and 1.39 (mononuclear cells count, MN-BF), the intercepts ranged between 26.47 (PMN-BF parameter) and 226.80 (white blood cell count). Bland-Altman bias was comprised between 7.3% (total cell count, TC-BF) and 52.9% (MN-BF). Comparison between UF-BF and XN-BF in all BF showed slopes ranged between 1.07 (TC-BF and PMN-BF) and 1.16 (MN-BF), intercepts ranged between 8.30 (PMN) and 64.78 (WBC-BF). Bland-Altman bias ranged between 5.8 (TC-BF) and 21.1% (MN-BF). The ROC curve analysis showed an area under the curve ranged between 0.9664 and 1.000. CONCLUSIONS: UF-BF shows very good performance for the differential counts of cells in ascitic, pleural and synovial fluids and therefore it is useful to screen and count cells in this type of BF.

What is the normal composition of pericardial fluid?

OBJECTIVE: Biochemical and cytological pericardial fluid (PF) analysis is essentially based on the knowledge of pleural fluid composition. The aim of the present study is to identify reference intervals (RIs) for PF according to state-of-art methodological standards. METHODS: We prospectively collected and analysed the PF and venous blood of consecutive subjects undergoing elective open-heart surgery from July 2017 to October 2018. Exclusion criteria for study enrolment were evidence of pericardial diseases at preoperatory workup or at intraoperatory assessment, or any other condition that could affect PF analysis. RESULTS: The final study sample included 120 patients (median age 69 years, 83 men, 69.1%). The main findings were (1) High levels of proteins, albumin and lactate dehydrogenase (LDH), but not of glucose and cholesterol (2) High cellularity, mainly represented by mesothelial cells. RIs for pericardial biochemistry were: protein content 1.7-4.6 g/dL PF/serum protein ratio 0.29-0.83, albumin 1.19-3.06 g/dL, pericardium-to-serum albumin gradient 0.18-2.37 g/dL, LDH 141-2613 U/L, PF/serum LDH ratio 0.40-2.99, glucose 80-134 mg/dL, total cholesterol 12-69 mg/dL, PF/serum cholesterol ratio 0.07-0.51. RIs for pericardial cells by optic microscopy were: 278-5608 × 106 nucleated cells/L, 40-3790 × 106 mesothelial cells/L, 35-2210 × 106 leucocytes/L, 19-1634 × 106 lymphocytes/L. CONCLUSIONS: PF is rich in nucleated cells, protein, albumin, LDH, at levels consistent with inflammatory exudates in other biological fluids. Physicians should stop to interpret PF as exudate or transudate according to tools not validated for this setting.

Preliminary evaluation of a new flow cytometry method for the routine hematology workflow.

Background In a generalist laboratory, the integration of the data obtained from hematology analyzers (HAs) with those from multiparametric flow cytometry (FMC) could increase the specificity and sensitivity of first level screening to identify the pathological samples. The aim of this study was to perform a preliminary evaluation of a new simple hybrid method (HM). The method was obtained by integration between HAs reagents into FCM, with a basic monoclonal antibodies panel for the leukocytes differential count. Methods Eighty-one peripheral blood samples, collected in K3EDTA tubes, were analyzed by XN-module, and CyFlow Space System, using both standard MoAbs and HM method analysis, and with the optical microscopy (OM). Within-run imprecision was carried out using normal samples, the carryover was evaluated, data comparison was performed with Passing-Bablok regression and Bland-Altman plots. Results The within-run imprecision of HM methods ranged between 1.4% for neutrophils (NE) and 10.1% for monocytes (MO) always equal or lower to the OM. The comparison between HM methods vs. OM shows Passing-Bablok regression slopes comprised between 0.83 for lymphocyte (LY) and 1.14 for MO, whilst the intercepts ranged between -0.18 for NE and 0.25 for LY. Bland-Altman relative bias was comprised between -12.43% for NE, and 19.77% for eosinophils. In all 11 pathological samples the agreement between the methods was 100%. Conclusions The new hybrid method generates a leukocytes differential count suitable for routine clinical use and it is also useful for identifying morphological abnormalities with a reduction in cost and improvement of screening for first level hematology workflow.

Comparison between optical microscopy and automation for cytometric analysis of pericardial fluids in a cohort of adult subjects undergoing cardiac surgery.

AIMS: Limited information is available on number and type of cells present in the pericardial fluid (PF). Current evidence and has been garnered with inaccurate application of guidelines for analysis of body fluids. This study was aimed at investigating the performance of automate cytometric analysis of PF in adult subjects. METHODS: Seventy-four consecutive PF samples were analysed with Sysmex XN with a module for body fluid analysis (XN-BF) and optical microscopy (OM). The study also encompassed the assessment of limit of blank, limit of detection and limit of quantitation (LoQ), imprecision, carryover and linearity of XN-BF module. RESULTS: XN-BF parameters were compared with OM for the following cell classes: total cells (TC), leucocytes (white blood cell [WBC]), polymorphonuclear (PMN) and mononuclear (MN) cells. The relative bias were -4.5%, 71.2%, 108.2% and -47.7%, respectively. Passing and Bablok regression yielded slope comprised between 0.06 for MN and 5.8 for PMN, and intercept between 0.7 for PMN and 220.3 for MN. LoQ was comprised between 3.8×106 and 6.0×106 cells/L for WBC and PMN. Linearity was acceptable and carryover negligible. CONCLUSIONS: PF has a specific cellular composition. Overall, automated cell counting can only be suggested for total number of cells, whereas OM seems still the most reliable option for cell differentiation.

Lack of harmonization in high fluorescent cell automated counts with body fluids mode in ascitic, pleural, synovial, and cerebrospinal fluids.

INTRODUCTION: Cellular analysis in body fluids (BFs) provides important diagnostic information in various pathological settings. This study was hence aimed at comparing automated cell count obtained with Mindray BC-6800 (BC-BF) vs Sysmex XN-series (XN-BF) and evaluating other quantitative and qualitative information provided by these analyzers in ascitic (AF), pleural (PF), synovial (SF), and cerebrospinal (CSF) fluids. METHODS: Three hundred and fifty-one samples (99 AFs, 45 PFs, 75 SFs, and 132 CSFs) were analyzed in parallel with BC-BF, XN-BF, and optical microscopy (OM). The study also included the assessment of diagnostic agreement among BC-BF, XN-BF, and OM. RESULTS: The comparison of BC-BF vs XN-BF yielded slopes of Passing and Bablok regression always comprised between 0.9 and 1.0 except for EO-BF and HF-BF, whilst the intercepts ranged from -0.4 for MN-BF and 12.0 for PMN-BF. The bias was comprised between -103.3% and 67.1% for HF-BF and EO-BF, respectively. A significant bias was found for TC-BF, WBC-BF, HF-BF (negative bias) and for PMN-BF and EO-BF (positive bias). The agreement (Cohen's kappa) between XN-BF and BC-BF was always ≥0.7, ranging between 0.87 in CSFs and 0.94 in AFs, and that with OM was similar (ie, 0.85 and 0.96). CONCLUSION: The cytometric analysis of BF samples using BC-BF and XN-BF is clinically favorable when appropriately combined with OM. Quantitative and qualitative parameters displayed optimal agreement, whilst instrument-specific cut-offs should be defined and implemented for HF-BF and EO-BF. Further efforts should be made for achieving better harmonization in cytometric analysis of BF samples.

A Preliminary Proposal for Quality Control Assessment and Harmonization of Leukocytes Morphology-structural Parameters (cell Population Data Parameters).

BACKGROUND: The cell population data (CPD) measured by Sysmex XN-9000 can be used for screening many hematological and non-hematological disorders. Since little information is available on harmonization of CPD among different instrumentation and clinical laboratories, this study aimed at assessing the current degree of CPD harmonization between separate Sysmex XN modules allocated to the same laboratory. METHODS: A total number of 78291 data were used for verification of within-run imprecision, analyzers harmonization, reference ranges and assessment of blood sample stability of CPD parameters, including results of daily quality control testing and those generated in samples collected from blood donors and healthy volunteers. RESULTS: Within-run imprecision of CPD parameters ranged between 0.4 and 14.1%. Good agreement was found among five different XN-modules, especially when values were adjusted after calculation of instrument-specific alignment factors. The bias of all parameters remained always lower than the reference change values in samples stored for up to 8 hours, regardless of storage temperature. CONCLUSIONS: The imprecision of CPD parameters was acceptable, except for those reflecting the dispersion of cellular clusters. Due to the lack of reference control materials, we showed that the use of data generated on a large number of normal routine samples (i.e., a Moving Average population) may be a reliable approach for testing analyzers harmonization. Nevertheless, availability of both calibration and quality control materials for these parameters is highly advisable in the future. We finally showed that whole blood samples may be stable for up to 2-4 hours for most CPD parameters.