Comparing Cell-Dyn Emerald 22 AL to Sysmex XN-1500 automated haematology analyser for full blood count estimation

doi:10.21203/rs.3.rs-3627482/v1

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Comparing Cell-Dyn Emerald 22 AL to Sysmex XN-1500 automated haematology analyser for full blood count estimation

https://doi.org/10.21203/rs.3.rs-3627482/v1

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Introduction

Modern haematology analysers provide an easy approach for enumerating the cellular components of blood in automated manner with improved turn-around-time. In our haematology laboratory, we have existing full blood count analyser, Sysmex XN-1500. We recently bought a backup full blood count analyser from Abbott Diagnostic, Cell Dyn Emerald 22 AL that enumerates cellular blood components using relatively similar measuring principles. As part of the method verification procedure required by ISO15189, we compared our newly purchased Cell Dyn Emerald 22 AL full blood count analyser to the existing verified Sysmex XN-1500 full blood count analyser. We further assessed the precision of both full blood count analysers. The residual EDTA blood samples were analysed using Sysmex XN-1500 (Sysmex Company Limited, Germany) as the reference analysers and CD Emerald 22 AL (Abbott, Abbott Park, Illinois, U.S.A) as newly purchased analysers.

Method and Results

We processed 120 residual blood samples for comparison study to improve the confidence interval in our statistical inference and incorporate the effects of unexpected interfering factors as reported in our previous study. Intra-run precision (repeatability) and inter-run precision (intermediate precision) were carried out using patient EDTA blood samples with sufficient volume to accommodate the runs. Using Pearson Product-Moment Correlation test, our data showed strong linear relationship between the two methods except for MCHC and PDW which generated moderate correlation coefficient (0.61, CI: 0.48–0.71) and weak correlation coefficient (0.228, CI: 0.469 − 0.395) respectively. The correlation results were supported by regression analysis scatterplot showing a weak linear relationship between the two analysers for only MCHC and PDW. Following linear relationship and regression analysis, we performed Bland-Altman analysis to determine agreement between the two analysers in a form of bias. The bias of all the tested full blood count parameters met the clinically acceptable bias range based on the 95% CI except for MCV, MCH, MCHC and MPV as they fall outside the clinically acceptable bias range.

Conclusion

From this study, we can confirm that Sysmex XN-1500 and Cell-Dyn Emerald 22 AL are comparable and interchangeable for all the clinically relevant full blood count parameters. However, MCV and HCHC as well as PLT derivatives (MPV and PDW) results should be treated with caution, preferably using a locally established equipment specific reference interval.

Laboratory Diagnostics

Hematology

Sysmex XN-1500

Cell-Dyn Emerald 22 AL

Full Blood Count

Method Verification

The full blood count is one of the most important and commonly requested tests in hematology laboratories across the globe because it is relatively inexpensive and is useful for routine screening, diagnosis, and monitoring of many different medical conditions. Our recent laboratory data have shown that full blood count accounts for 75% of the hematology laboratory requests from clinicians (1). The full blood count test provides preliminary information about the health status of patients and contributes to the diagnosis and management of disease conditions such as anemias, infection, haematological malignancy, and thrombocytopenia. Full blood count provides quantitative information about the levels of cellular components such as red blood cells, white blood cells, differentials, platelets, as well as hemoglobin levels(2).

Modern hematology analyzers provide an easy approach to enumerating the cellular components of blood in an automated manner with improved turn-around time. Despite having Sysmex XN-1500 as our main full blood count analyzer, we recently bought Cell Dyn Emerald 22 AL as a backup automated full blood count analyzer from Abbott Diagnostics that enumerates cellular blood components utilizing light scattering, electrical impedance, and hemoglobin spectrophotometry(3). Sysmex XN-1500 and Cell-Dyn Emerald 22 AL analyzers are both robust and provide both open and closed system modes for analyzing blood samples. The closed system is particularly of value in infection control since it reduces the personnel’s encounter with the blood sample. The Sysmex XN-1500 is part of the Sysmex XN series (Sysmex, Kobe, Japan), and it comprises an XN-10 plus SP-50 automated hematology slide preparation unit and a sampler SA-21. The series is the newest generation of automated hematology analyzers designed to improve both the accuracy for samples with low blood cell count and the specificity of the abnormal cell flags (4, 5).

Full blood count results obtained using automated analyzers should be comparable, reliable, and repeatable despite minute differences in measurement principles and technology. Comparing a newly purchased full blood count analyzer to the existing verified full blood count analyzer is part of the method verification procedure required by ISO15189 which is described as true by and International Council for Standardisation of Haematology (6–8). Measurement precision is another performance characteristic required by ISO15189, which describes precision in the form of repeatability and intermediate precision(7, 8). Despite many comparative studies between different hematology full blood count analyzers, no study has specifically compared Cell-Dyn Emerald 22 AL to Sysmex XN-1500 automated analyzers. From this study, we aim to assess the comparability and interchangeability of the existing Sysmex XN-1500 in our laboratory with the newly purchased Cell-Dyn Emerald 22 AL for a full blood count test.

Study setting

The study was conducted in Clinical Laboratories, Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine (MRCG) Routine Diagnostic Laboratory, hosted at the Kuyateh Building. The laboratory is in the Kanifing Municipality, greater Banjul area, the Gambia located in West Africa with a population of about 2.5 million and an area of 10,000 km2.

The clinical laboratories department composed of the Clinical Microbiology, Haematology, and Clinical Biochemistry laboratories, and attained ISO15189 accreditation in 2015. The laboratories provide services to the clinical services of the MRCG, projects, including clinical trials, as well as government and private hospitals. Annually, the haematology laboratory analyses more than thirty thousand full blood count samples.

Sample size, Study design, and Sample Processing

The residual EDTA blood samples were analyzed using Sysmex XN-series (Sysmex Company Limited, Germany) as the reference analyzer and CD Emerald 22 AL (Abbott, Abbott Park, Illinois, U.S.A) as the newly purchased analyzer. All the maintenance requirements recommended by the manufacturers as well as quality checks were performed for both analysers before running the blood samples for comparison as required by ISO15189:2012 standards and our internal quality management system. The blood samples with sufficient volume were further employed for imprecision study on both analyzers.

The CLSI recommends a minimum of 40 patient samples to establish the agreement between the existing analyzer and the newly purchased analyzer in the form of bias(9). We processed 120 residual blood samples for comparison study to improve the confidence interval in our statistical inference and incorporate the effects of unexpected interfering factors as reported in our previous study(10).

As part of the method verification procedure to determine performance characteristics when an unmodified and approved method is introduced, intra-run precision (repeatability) and inter-run precision (intermediate precision) were carried out using patient EDTA blood samples with sufficient volume to accommodate the runs. For repeatability, the sample was run for 6 times at short intervals (i.e. six runs). For Intermediate precision, the sample was run over six days, varying as many factors as possible over the six days: operator, reagent batches, and instrument.

Analytical methods

Sysmex XN-series (Sysmex, Germany) is a fully automated full blood count analyzer with one of the best technologies. The detection range includes blood cell count (Red Blood Cell, White Blood Cell, Platelet), white blood cell classification, hemoglobin concentration measurement as well as nucleated red blood cells and reticulocytes. For white blood cells and reticulocyte counting, fluorescence flow cytometry is used; while hydrodynamically focussed impedance is used for red blood cell and platelet counting. Hemoglobin concentration is accomplished utilizing the cyanide-free sodium lauryl sulfate method (4, 5).

Cell-Dyn Emerald 22 AL (Abbott Diagnostics, USA) is a fully automated hematology analyzer designed for in vitro diagnostic use in clinical laboratories. The CELL-DYN Emerald 22 AL uses approximately 21uL of whole blood aspirated from a well-mixed, open collection tube held by the tube holder or closed tube via the sample autoloader. Electrical Impedance counting is used to count and size WBCs, RBCs, and platelets. This method is based on the measurement changes in an electrical current produced by particles (cells), suspended in a conductive liquid, as they pass through an aperture of known dimensions. Optical flow cytometry technology based on the concept of active sample flow and passive sheath is used to measure the WBC differentials. Haemoglobin is measured using a chromogen formed from a cyanide-free lyse reagent. The chromogen is measured employing absorption spectrophotometry using a 555nm LED as the light source(3).

The reagents, three-level controls, and calibrators used in the two instruments are commercially procured and are operated according to the operating instructions provided by the instrument manufacturer.

Ethical consideration

The study was approved by the Scientific Coordinating Committee of MRCG at LSHTM and the Gambia Government/MRCG Joint Committee.

Statistical Analysis

The data was entered and arranged into Microsoft Word Excel. Statistical analysis was performed with Microsoft Excel and R package (version 4.3.1). The CLSI guidelines recommend that clinical laboratories assess the agreement between two analyzers through either regression or difference plots. In this study, we presented analysis results from both regression analysis to assess for systematic errors and Bland-Altman analysis based on predetermined a priori from our previous publication(10, 11). Precision in a form repeatability and intermediate precision were reported as coefficient of variation (CV(%)) (6, 7).

Regression analysis and correlation between the two analyzers were performed. Correlation scores of 0.10–0.39 were considered weak correlation, 0.40–0.69 were considered moderate correlation, 0.70–0.89 were considered strong correlation, and 0.90-1.0 were considered very strong correlation. The intercept and slope were interpreted in the form of a 95% confidence interval (95% CI). The intercept is a measure of the systematic difference between the two instruments. If the 95% confidence interval of the intercept does not include 0, there are systematic errors in the two instruments. The slope is a measure of the difference in the ratio between the two instruments. If the 95% confidence interval for the slope does not contain 1, then there is at least a proportional difference between the two methods(12, 13).

The bland-Alman test was performed using the R package to assess bias, which is the agreement between the two analyzers. A normality check was performed using the Shapiro method to check for normality in the distribution of the differences. Bland-Alman plots were generated for normally distributed mean differences(11, 14–16).

In this study, the results of the samples concurrently run in Sysmex XN-1500 and CD Emerald 22 AL as shown in Table 1 were compared as part of the performance evaluation in our laboratory. The full blood count parameters generated by both analyzers comprise red blood cells (RBC), hemoglobin (Hb), hematocrit (HCT), mean cell volume (MCV), mean cell hemoglobin (MCH), mean cell hemoglobin concentration (MCHC), red cell distribution width (RDW), platelets, mean platelets volume (MPV) and platelets distribution width (PDW), and white blood cells (WBC) and differentials. Since the absolute count for WBC differentials is directly measured by the analyzers and the percentages are automatically calculated, the absolute count was retrieved. The measured ranges for the main parameters (RBC, Hb, WBC, and PLT) covered a broad concentration range, shown in Table 1.

Correlation and regression analysis is the initial process of performance evaluation to investigate the relationship between the results of the two analyzers or methods in a diagnostic laboratory. Using the Pearson Product-Moment Correlation test, our data showed a strong linear correlation/relationship between the two methods except for MCHC and PDW which generated a moderate correlation coefficient (0.61, CI: 0.48–0.71) and weak correlation coefficient (0.228, CI: 0.469 − 0.395) respectively as shown in Table 2. The correlation results were supported by the regression analysis scatterplot in Fig. 1 which showed a weak linear relationship/correlation between the two analyzers for MCHC and PDW.

Following linear relationship and regression analysis, we performed the Bland-Altman test to determine the agreement between the two analyzers in the form of bias. The predefined a priori (i.e. clinically acceptable bias range) was used to determine the agreement and whether their full blood count results can be interchangeable in clinical decision making as shown in Table 3. In supplementary Fig. 1, the Bland-Altman Plots were generated for RBC and HCT due to their normally distributed mean differences from the normality check. From visual inspection, the result showed good agreement between the two analyzers as more than 95% of the bias falls within the upper level of difference (colored green) and lower level of difference (colored red), shown in supplementary Fig. 1(14). However, the visual inspection alone is not sufficient to establish the agreement, hence predefined clinically acceptable bias range was established. The bias of all the tested full blood count parameters met the clinically acceptable bias range based on the 95% CI except for MCV, MCH, MCHC, and MPV as they fall outside the clinically acceptable bias range. The bias for Hb is clinically acceptable, albeit with low accuracy.

The study also determined the precision in the form of repeatability and intermediate precision through the coefficient of variation (%). Based on CLSI guidelines, the precision of the hematological analyzer is assessed in the form of coefficient of variation: the acceptable coefficient of variation (CV) should be less than 15%(9). For repeatability, CV (%) was acceptable for all the parameters for both Sysmex XN-1500 and Cell-Dyn Emerald 22 AL, shown in Fig. 2 and Fig. 4. For intermediate precision in Fig. 3 and Fig. 5, the CV (%) was also acceptable for all the parameters for both Sysmex XN-1500 and Cell-Dyn Emerald 22 AL except WBC (CV = 34.3%) with a CV% greater than 15% as shown in Fig. 3 (image c).

Table 1

Full blood count parameters and their measured range in both analysers
Parameters	Sample size (n)	Sysmex XN 1500 Measured Range	CD Emerald 22 AL Measured Range
Red blood cells (10^6/uL)	120	1.93–5.63	1.83–5.46
Haemoglobin g/dL	120	6-16.1	6.5–17.4
Haematocrit (%)	120	17.3–48.4	18.3–48
Mean Cell Volume (fL)	120	60.2-104.1	57.3-114.4
Mean Cell Haemoglobin (pg)	120	16.2–36.1	18.6–39
Mean Cell Haemoglobin Conc (g/dL)	120	26.9–37.3	31.3–38
Red Cell Distribution Width (%)	120	10.7–32.2	12.4–26.3
White blood cells (10^3/uL)	120	3.71–30.93	3.8–32.2
Abs Neutrophils (10^3/uL)	120	0.99–17.59	1.10–17.90
Abs Lymphocytes (10^3/uL)	120	0.62–12.39	0.8–13.3
Abs Monocytes (10^3/uL)	119	0.24–2.69	0.20–2.30
Abs Eosinophils (10^3/uL)	119	0.0-1.90	0.0-1.87
Platelets (10^3/uL)	119	94–628.0	103–672
Mean Platelets Volume (fL)	116	7.2–17.9	6.2–10.70
Platelets Distribution Width (fL)	115	7.7–13.00	10.7–20.30

Table 2

Regression table of the full blood count parameters with their intercept, slope, and correlation coefficient at 95% confidence intervals (95% CI). The (P < 0.05) indicates correlation coefficient significance between the two analysers.
Parameters	Intercept (95% CI)	Slope (95% CI)	Pearson Product-Moment Correlation coefficient (95% CI)	P value (P < 0.05)
Red blood cells (10^6/uL)	0.03 (-0.13-0.19)	0.95 (0.92–0.99)	0.98 (0.97–0.98)	P < 0.05
Haemoglobin g/dL	0.21(-0.00–0.42)	1.06 (1.05–1.08)	1.00(0.99-1.00)	P < 0.05
Haematocrit (%)	1.01 (-0.49 -2.52)	0.96 (0.92-1.00)	0.97(0.96–0.98)	P < 0.05
Mean Cell Volume (fL)	-1.28 (-6.09–3.55)	1.05 (0.99–1.11)	0.96(0.94–0.97)	P < 0.05
Mean Cell Haemoglobin (pg)	0.53 (-0.89–1.96)	1.10 (1.06–1.15)	0.97 (0.96–0.98)	P < 0.05
Mean Cell Haemoglobin Conc (g/dL)	19.772 (16.01–23.53)	1.05 (0.37–0.60)	0.61 (0.48–0.71)	P < 0.05
RDW (%)	5.81 (5.10–6.52)	0.68 (0.63–0.73)	0.93 (0.91–0.95)	P < 0.05
White blood cells (10^3/uL)	0.07 (-0.074–0.208)	1.03 (1.01–1.04)	0.996 (0.994–0.997)	P < 0.05
Abs Neutrophils (10^3/uL)	0.08 (0.02–0.13)	1.00 (0.99–1.02)	0.998(0.997–0.999)	P < 0.05
Abs Lymphocytes (10^3/uL)	0.06 (-0.02–0.14)	1. 03 (1.01–1.06)	0.991(0.988–0.994)	P < 0.05
Abs Monocytes (10^3/uL)	0.05 (0.00–0.08)	1.00 (0.98–1.07)	0.936(0.909–0.955)	P < 0.05
Abs Eosinophils (10^3/uL)	0.02 (-0.02–0.012)	0.94 (1.01–1.08)	0.963 (0.948–0.974)	P < 0.05
Platelets (10^3/uL)	10.4 (-8.11–28.99)	0.93 (0.94 - 1.06)	0.973(0.962–0.981)	P < 0.05
Mean Platelets Volume (fL)	3.65 (3.25–4.05)	0.45 (0.38–0.45)	0.916(0.881–0.941)	P < 0.05
Platelets Distribution Width (fL)	9.40 (6.12–12.67)	0.40 (0.08- 0.71)	0.228(0.469 − 0.395)	P = 0.14

Table 3

Bland-Altman Analysis with 95% confidence intervals (95% CI). Clinically acceptable bias range was used to determine whether the bias at 95% CI is clinically acceptable. (P ≤ 0.05 was used to whether the bias is skewed or normally distributed (ND)). Skewed(P < 0.05). Normally distributed (P > 0.05).
Parameters	Shapiro-wilk Normality Test	Bias (95%CI) from Bland-Altman Analysis	Clinically Acceptable Bias Range
Red blood cells (10^6/uL)	ND (P = 0.09)	0.17(0.15 to 0.20)	± 0.18
Haemoglobin g/dL	Skewed (P = 0.0008)	-0.94(-0.98 to -0.90)	± 0.83
Haematocrit (%)	ND(P = 0.34)	0.37(0.13 to 0.61)	± 1.44
Mean Cell Volume (fL)	Skewed (P = 0.02)	-2.75 (-3.24 to -2.26)	± 2.5
Mean Cell Haemoglobin (pg)	Skewed (P = 0.02)	-3.48(-3.66 to -3.30)	± 2.5
RDW (%)	Skewed (P < 0.05)	-1.14 ( -1.40 to -0.88 )	± 2.5
White blood cells (10^3/uL)	Skewed (P < 0.05)	-0.28 (-0.35 to -0.21)	± 0.33
Abs Neutrophils (10^3/uL)	Skewed (P < 0.05)	-0.10 (-0.13 to -0.07)	± 0.2
Abs Lymphocytes (10^3/uL)	Skewed (P < 0.05)	-0.15 (-0.19 to -0.11)	± 0.5
Abs Monocytes (10^3/uL)	Skewed (P < 0.05)	-0.06 (-0.09 to -0.03)	± 0.2
Abs Eosinophils (10^3/uL)	Skewed (P < 0.05)	-0.002 (-0.015 to 0.001)	± 0.1
Platelets (10^3/uL)	Skewed (P < 0.05)	-9.3 (-15.46 to -3.14)	± 51
Mean Platelets Volume (fL)	Skewed(p = 0.00010)	3.200 (2.98 to 3.415)	± 2.5

Figure 5: Intermediate precision results of the five main measurable parameters from Sysmex XN-1500 (image a-e). The precision is determined by coefficient of variation less than15%. The full blood count parameters that were directly measured by the analysers were used to determine intermediate precision following six runs (Day 1 to Day 6) of a sample over six days period. Red blood cells (RBC); Haemoglobin (HB); White blood cells (WBC); Platelets (PLT); Mean Cell Volume (MCV); Haematocrit (HCT)

The main objective of this study was to assess the comparability and interchangeability of our existing Sysmex XN-1500 hematology analyzer and the newly purchased Cell-Dyn Emerald 22 AL hematology analyzer. The results have shown a very good correlation and agreement between the Sysmex XN-1500, and the newly purchased automated Cell-Dyn Emerald 22 AL analyzer for almost all the clinically relevant main full blood count parameters. Generally, Sysmex and Abbott analyzers are comparable and interchangeable in routine diagnostic haematology laboratories, and this is evident in several studies comparing different haematological analyzers (17–19). The MCHC and PDW calculated values were not considered for the Bland-Altman analysis as no correlation/relationship between the two analyzers was found during the correlation and regression analysis. This finding is consistent with the results of Malecka and Ciepiela's study which found a significant difference between Sysmex-XN 2000 and Yumizen H2500 automated analyzers for MCHC and PDW calculated full blood count parameters (31). Hence, our findings suggest that the two analyzers cannot be used interchangeably for MCHC and PDW, albeit the clinical relevance of the latter is still under investigation(20).

Since correlation analysis may not necessarily depict agreement between two analyzers, a Bland-Altman analysis was conducted (14). The bland-Altman analysis is a statistical approach to quantify the agreement between two quantitative analyzers by constructing limits of agreement introduced by Bland and Altman in 1983. Bland-Altman plot is used to detect the presence of systematic differences between the measurements (i.e., fixed bias) or possible outliers(21). Despite our results showing very good agreement between the two analyzers, the bias for MCV, MCH, MCHC, PDW, and MPV falls outside our clinically acceptable bias range (predefined a priori). Hence, their results should be interpreted with caution, preferably using a locally established equipment-specific reference interval. Among these parameters, MCV is the most useful full blood count parameter in clinical decision-making. MCV is used to estimate the mean volume of RBCs in a sample and is a useful parameter to classify anemias based on RBC size as microcytic (MCV < 80fL), normocytic (MCV: 80-100fL), and macrocytic anemia (MCV > 100fL). The reference interval for the MCV is generally reported as 80–100 fL, but this varies by age, gender, technology, and reference population(22–24). Depending on the instrument technology, the MCV can be determined automatically when the RBC is being counted or calculated using the RBC count and the HCT(25). The MCV disagreement between the two analyzers based on Bland-Altman analysis is understandable as the MCV is directly measured by Cell-Dyn Emerald whilst calculated by Sysmex XN-series from measured RBC count and HCT results. Interestingly, MCH, MCHC, MPV, and PDW are not directly measured but are calculated parameters. The software used for the calculation of these parameters could have resulted in a significant bias in our results(26–28).

A precision study in the form of repeatability and intermediate precision was performed to assess the stability of measured full blood count parameters (red blood cells, hemoglobin, white blood cells, platelets, and mean cell volume/hematocrit) as part of the performance evaluation. In our hematology laboratory, the sample retention period is one week as our previous mini-lab laboratory study showed that full blood count parameters are stable for six days provided the blood sample is stored at a chilled temperature (2 to 8oC). Using the coefficient of variation, our result showed very good stability of all the measurable full blood count parameters for both analyzers as the CVs conformed with the manufacturer’s CV and CLSI guidelines(9). However, the coefficient of variation for Cell-Dyn Emerald 22 AL WBC result was significantly high during intermediate precision. This significant decrease in total WBC count could be the result of a drastic decrease in a particular subpopulation of WBCs as shown in a previous study that the WBC subpopulations changed over time with a decrease in eosinophils and lymphocytes and an increase in neutrophils at 2–8°C. Furthermore, the stability of WBC subpopulations was significantly different among Bayer Advia 120, Beckman Coulter LH 750, and Sysmex XE 2100 with some analytes only displaying a stability of 4h(29, 30). A sample stored beyond 24 hours at a chilled temperature would not be suitable for total white blood cell counting.

Unlike Sysmex XN-1500, our study could not assess and compare the flagging characteristics of the two analyzers as the Cell-Dyn Emerald 22 AL does not possess the technology to assess the morphological changes of cellular components of blood. Furthermore Cell-Dyn Emerald 22 AL lacks the measurement technology for reticulocytes and nucleated red blood cell counting, hence the agreement between the two analyzers using Bland-Altman analysis for these two parameters could not be assessed(3–5, 8, 19).

From this study, we can confirm the comparability and interchangeability of Sysmex XN-1500 and Cell-Dyn Emerald 22 AL for all the clinically relevant full blood count parameters. However, MCV, MCHC, and PLT derivatives (MPV and PDW) results should be treated with caution, preferably using a locally established equipment-specific reference interval. This study highlights the importance of assessing the agreement between two hematology analyzers in diagnostics settings for aiding clinicians in clinical decision-making and disease monitoring.

Conflict of Interest

The authors have no conflict of interest to disclose

Acknowledgement

Acknowledgement goes to Interns that assisted in data entry and the clinical laboratory department for purchasing of the two haematology analysers.

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Comparing Cell-Dyn Emerald 22 AL to Sysmex XN-1500 automated haematology analyser for full blood count estimation

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Abstract

Introduction

Method and Results

Conclusion

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Introduction

Methods

Study setting

Sample size, Study design, and Sample Processing

Analytical methods

Ethical consideration

Statistical Analysis

Results

Discussion

Conclusion

Declarations

References

Supplementary Files

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