Clin Chem Lab Med 2022; 60(5): 748–755
Peng Xu, Kui Fang, Xiling Chen, Yangruiqi Liu, Zheqing Dong, Ji Zhu and Keda Lu*
The flagging features of the Sysmex XN-10
analyser for detecting platelet clumps and the
impacts of platelet clumps on complete blood
count parameters
https://doi.org/10.1515/cclm-2021-1226
Received November 24, 2021; accepted February 11, 2022;
published online February 23, 2022
Abstract
Objectives: Platelet clumps present in anticoagulant
specimens may generate a falsely decreased platelet count
and lead to an incorrect diagnosis. A clear understanding
of the ability of a haematology analyser (HA) to detect
platelet clumps is important for routine work in the clinical
laboratory.
Methods: Citrate-anticoagulated whole-blood samples
were collected from various patients as a negative group.
Adenosine diphosphate (ADP)-induced platelet aggregation was performed on those negative samples to mimic
platelet-clump-containing (positive) samples. The ‘platelet
clumps’ and ‘platelet abnormal’ flags generated by the
Sysmex XN-10 instrument were used to assess the flagging
performance of this HA and demonstrate its flagging features. The complete blood count (CBC) results of paired
negative and positive samples were compared to evaluate
the impact of platelet clumps on the CBC parameters.
Results: A total of 187 samples were eligible for this
study. The total accuracy, sensitivity, and specificity of the
platelet clumps flag were 0.786, 0.626, and 0.947, respectively. The total accuracy, sensitivity, and specificity of
the platelet abnormal flag were 0.631, 0.348, and 0.914,
respectively. A separate assessment focusing on the positive samples with low platelet counts showed that the total
sensitivities of the platelet clumps and platelet abnormal
flags were 0.801 and 1.000, respectively. Platelet clumps
Peng Xu and Kui Fang contributed equally as co-first authors.
*Corresponding author: Keda Lu, Zhejiang Chinese Medical University
Affiliated Third Hospital, Hangzhou 310000, P.R. China,
E-mail: lukedazsyy@outlook.com
Peng Xu, Kui Fang, Xiling Chen, Yangruiqi Liu, Zheqing Dong and Ji
Zhu, Zhejiang Chinese Medical University Affiliated Third Hospital,
Hangzhou, P.R. China
may interfere with the leukocyte count and with platelet
and erythrocyte indices.
Conclusions: Platelet clumps can influence not only
platelet indices but also leukocyte and erythrocyte counts.
The Sysmex XN-10 instrument is sensitive to positive
samples with low platelet counts but insensitive to those
with high platelet counts.
Keywords: complete blood count; flagging quality;
haematology analyser; platelet aggregates.
Introduction
Although platelet clumping in ethylenediaminetetraacetic
acid (EDTA)-anticoagulated blood samples, which is usually caused by insufficient mixing of the sample tube, poor
venepuncture or insufficient mixing, is an uncommon
phenomenon, it may generate a falsely decreased platelet
count and mislead the diagnosis towards thrombopenia,
causing improper treatment and unnecessary transfusion
[1, 2].
Compared with other factors influencing platelet count,
platelet clumps are more inconspicuous, as they may not
form visible clots and cause no unique changes in the
complete blood count (CBC) parameters. Although various
highly specific techniques, such as immunoplatelet counting and fluorescence platelet counting, have been developed, platelet clumping is still a common kind of
interference shared by these techniques [3]. In practice, the
routine way to remove such interference is to perform a
slide review when the outcomes of the haematology analyser (HA) meet the criteria recommended by the international council for standardization in haematology (ICSH)
(i.e., platelet-related flags, including ‘platelet clumps’ and
‘platelet abnormal’, are generated by the HA, or the platelet
count is lower than 100 × 109/L [4]). As a consequence,
laboratory technicians should know the flagging performance of their HA.
The performance in platelet clump detection has been
investigated on various brands of HAs, including Sysmex,
Xu et al.: Flagging features of the Sysmex XN-10 for detecting platelet clumps
Abbott, Mindray, Beckman, and Siemens, but the sensitivities seem far from satisfactory. The sensitivities of the HAs
in most of the reports are less than 60% [5–8]. Low flagging
sensitivity means that more pseudothrombocytopenia cases
will be misdiagnosed due to inaccurate platelet count reports or that technicians will spend more time on microscopic examinations when handling samples that have
platelet counts of 100–150 × 109/L and no positive flags.
Microscopic examination is not mandatory in this interval if
no platelet-associated flags arise.
This study aimed to introduce little-known algorithmic
features of the Sysmex XN-10 instrument in its detection of
platelet clumps and the potential influences of platelet
clumps on CBC parameters.
Materials and methods
Sample collection and data preparation
Citrate (3.2% sodium citrate) whole-blood samples were collected from
the patients (including inpatients, outpatients, and healthy people
who were undergoing a health examination) of The Third Affiliated
Hospital of Zhejiang Chinese Medical University between June and
August 2021. The samples used in this study were all collected
concomitantly with blood tests ordered by the doctors and would not
cause unnecessary venepuncture. The study was approved by the
Institutional Research Ethics Committee of The Third Affiliated Hospital of Zhejiang Chinese Medical University, and all patients provided
written informed consent. CBC (using the Sysmex XN-10 instrument
with default flagging thresholds and information processing unit
version 22.11) and blood smear (using the Sysmex SP-10) were performed on each specimen within half an hour, as the platelets in citrate
whole blood may form aggregates spontaneously if the standing time
is over 2 h [9]. The quality control procedure was run daily to ensure
that the HA was running within acceptable limits. Platelet measurement in this study used the impedance method. Platelet-rich plasma
(PRP) was isolated from the specimen tube and mixed with ADP at
37 °C for 10 min. After incubation, the PRP was gently transferred back
into the sample tube and mixed with the blood cells by inverting the
tube 5–7 times to mimic a positive sample. Finally, the CBC count and
blood smear were performed again immediately. The platelet aggregation rate (PAR) of each sample was calculated using the formula
PAR=(Pb − Pa)/Pb, in which Pb represents the platelet count before
ADP induction and Pa represents the platelet count after ADP induction. Only samples with PAR ≥10% and ≤90% were regarded as positive samples because the sample size of the two endmost intervals was
too small. The data used in this study were processed and analysed
within the Python (version 3.8) computing environment.
Microscopic examination
The blood smears of the negative samples (entire slides) were quickly
examined at a magnification of 100× to detect platelet clumping, and
the samples in which significant platelet clumping was observed were
749
excluded from this study. Then 96 pairs of blood smears (negative and
positive) were randomly selected and reviewed at a magnification of
1,000× from the edge to the centre to count 200 platelets. A clump was
counted as one platelet and was classified into one of three types,
paired platelets, small platelet clumps (3–4 platelets), and large
platelet clumps (≥5 platelets), to estimate the frequency of each type of
platelet clump. Another 30 clinical EDTA samples, namely, 15 positive
and 15 corresponding negative samples, were evaluated morphologically for comparison with the ADP-induced samples.
Assessment of the flagging performance
A confusion matrix was built to visualize the performance of the
platelet clumps flag in different PARs. Total sensitivity, specificity,
and accuracy were calculated based on the confusion matrix. The
performance of the platelet abnormal flag was also assessed. Scatter
plots were drawn based on the flags and the platelet count to depict
the features of the platelet clump detection algorithms. The truepositive and true-negative samples were morphologically positive and
negative samples that were correctly identified by HA, respectively.
Similarly, false-positive and false-negative samples were morphologically positive and negative samples that were misidentified by HA.
The efficiency was defined as the percentage of specimens among
those 374 samples that were correctly identified by the analyser as
having true-positive or true-negative results. A smoothed heatmap
based on radial basis functions was plotted to depict the relationship
between the efficiency of the platelet clumps flag and the number and
size of the clumps. An additional investigation in which the parameters of negative and positive samples were compared by the Wilcoxon
signed-rank test was conducted to observe the influence of platelet
clumping on the parameters of the CBC. In this additional investigation, the data were generated by deleting the incomplete CBC results
from the total dataset because the PDW, MPV, P-LCR, and PCT of
several samples were invalidated by the HA. However, XN-10 reports
the platelet count regardless of the existence of platelet clumps. The
p-value of each parameter for each PAR interval was calculated to
generate a p-value matrix. The impact of platelet clumps on diagnosis,
which was defined as the transition of the CBC result from normal to
pathosis, was also evaluated using the false-negative cases. p-values
<0.05 were considered statistically significant.
Results
Profiles of the sample data
One hundred 87 negative and 187 positive CBC results were
eligible for this study. The features of their data are summarized in Table 1. Table 1 showed that most of the patients
were in the ageing population because our hospital specializes in the treatment of patients with senile diseases.
The flagging performance of Sysmex XN-10
The confusion matrices that assessed the identification
abilities of the platelet clumps and platelet abnormal flags
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Xu et al.: Flagging features of the Sysmex XN-10 for detecting platelet clumps
Table : Features of the dataset.
Platelet count (negative)
Platelet count (positive)
Age, years
PAR, %
Table : The performance of the XN- instrument in detecting
platelet clumps.
Q
Median
Q
% CI
.
.

.
.
.

.
.
.

.
.–.
.–.
–
.–.
The platelet counts of  negative and  positive samples, the age
of the  patients, and the PARs of the positive samples are
summarized and show that the dataset used in our study was
comprehensive and representative. Q, first quartile; Q, third
quartile; % CI, % confidence interval.
are exhibited in Figure 1. The total accuracy, sensitivity,
and specificity of the platelet clumps flag were 78.6%,
62.6%, and 94.7%, respectively (Table 2). The histogram
showed that the sensitivity of this flag decreased significantly as PAR decreased (Figure 2A). The highest sensitivity was 94.7% at a PAR of 70–80 (%), while the lowest
sensitivity was 17.6% at a PAR of 10–20 (%). For the platelet
abnormal flag, the total accuracy, sensitivity, and specificity were 63.1%, 34.8%, and 91.4%, respectively (Table 2).
If both flags were used to identify platelet clumping (at
least one flag was generated by the HA), the total sensitivity
reached 71.1% (Figure 2C).
To further understand the characteristics of the flagging algorithm, a scatter diagram of the positive samples
was plotted according to the PARs and platelet counts
(Figure 3). Unexpectedly, the flagged samples (red points)
seemed to have invisible boundaries that were perpendicular to the X-axis (platelet count) at 140 × 109/L because
none of the positive samples whose platelet counts
exceeded 140 × 109/L were correctly flagged by the HA
(Figure 3A). A separate assessment of only the samples
Platelet clumps flag, %
Platelet abnormal flag, %
ACC
SPE
SEN
SENa
.
.
.
.
.
.
. (n=)
. (n=)
The flagging performance of platelet clumps and platelet abnormal at
detecting platelet clumps using  positive and  negative
samples. aThe sensitivities were determined from the samples with
low platelet count (≤ × /L for platelet clumps, and ≤ × /L
for platelet abnormal). ACC, accuracy; SEN, sensitivity; SPE,
specificity; n, number of samples.
with a low platelet count (≤140 × 109/L) had highest,
lowest, and total sensitivity values of 94.7%, 56.2%, and
80.1%, respectively (Figure 2D). The platelet abnormal flag
was also insensitive to the positive samples with a platelet
count >60 × 109/L but highly sensitive (sensitivity was
100.0%) to the samples with a platelet count <60 × 109/L.
The impact of platelet clumping on the CBC
parameters
All 348 (174 pairs) negative and positive samples that had
complete CBC parameters were compared (Figure 4). The
samples were grouped into eight groups based on their
PARs, and each group had enough samples (the fewest was
28). The influence on most parameters was not consistent
across all PAR intervals. The mean leukocyte count was
significantly (p=0.02) increased from 8.0 × 109/L (95%
CI=4.2–19.3 × 109/L) in clump-negative samples to
8.2 × 109/L (95% CI=4.4–19.9 × 109/L) in clump-positive
blood only in the PAR interval of 20–30 (%). Clumps
Figure 1: Confusion matrices of the two flags.
(A) The confusion matrix of platelet clumps. (B) The confusion matrix of platelet abnormal. The numbers in the subsquares in the upper left,
upper right, lower left, and lower right represent the true-positive, false-negative, false-positive, and true-negative cases, respectively.
Xu et al.: Flagging features of the Sysmex XN-10 for detecting platelet clumps
751
Figure 2: Assessment of the sensitivities to the positive samples within different PAR intervals.
(A) Sensitivity of the platelet clumps flag. Each PAR interval included only the left endpoint, except the last PAR interval, which included both
endpoints (≥80 and ≤90). (B) Sensitivity of the platelet abnormal flag. (C) Sensitivity of mutual complementation of the two flags. The
sensitivity in this histogram is defined as the percentage of positive samples for which test results revealed either or both of the flags (platelet
clumps and platelet abnormal). (D) Separate assessment of the sensitivity of the platelet clumps flag in the samples with fewer than
140 × 103 platelets/µL.
Figure 3: Scatter plots depicting the flagging features of the XN-10 instrument.
Each dot represents a positive sample; the red dots represent positive samples that were correctly flagged as platelet clumps (A) or platelet
abnormal (B), while the blue dots represent positive samples that were not flagged by either of these two flags. The green dashed lines
perpendicular to the X-axis (140 for A and 60 for B) were added by us to help visualize the characteristics of the flagging algorithms.
752
Xu et al.: Flagging features of the Sysmex XN-10 for detecting platelet clumps
Figure 4: The coloured p-value matrix.
The p-value in each square was determined by the paired-sample t-test between the CBC parameters of positive and negative samples. pValues <0.05 were considered statistically significant. The labels on the y-axis are the CBC parameters, and the labels on the x-axis are the PAR
intervals. The rightmost column has the total p-Values. The nonlinear colour map was used to highlight the squares with p-values lower than
0.05. The colour filled in the square represents whether the mean of the parameter of the positive samples was higher (red) or lower (blue) than
that of negative samples. WBC, white blood cell; RBC, red blood cell; HGB, haemoglobin; HCT, haematocrit; MCV, mean corpuscular volume;
MCH, mean corpuscular haemoglobin; MCHC, mean corpuscular haemoglobin concentration; PLT, platelet; RDW-SD, the standard deviation of
the red cell distribution width; RDW-CV, the variation coefficient of the red cell distribution width; PDW, platelet distribution width; MPV, mean
platelet volume; P-LCR, platelet-large cell rate; PCT, plateletcrit; NEUT, neutrophil; LYMPH, lymphocyte; MONO, monocyte; EO, eosinophil;
BASO, basophil; IG, immature granulocyte; #, in the form of raw number; %, in the form of percentage.
notably increased the large platelet ratio (P-LCR) and
mean platelet volume (MPV) in the PAR interval of 50–90%
but reduced them in the PAR interval of 10–30%. Such
results may imply the variability of the morphology of
platelet clumps in different PAR intervals, which cause
different impacts on the CBC parameters. In summary, the
CBC parameters that had the possibility of being influenced
by platelet clumps were total leukocytes, neutrophilic and
basophilic granulocytes, monocytes, and indices of platelets and erythrocytes, such as P-LCR, MPV, platelet distribution width (RDW), platelet distribution width (PDW), and
plateletcrit (PCT). The probability of being misdiagnosed due
to failed detection of platelet clumps was 5% for pseudoleukocytosis, 27% for pseudothrombocytopenia, and 5% for
falsely elevated neutrophils which was not totally overlapped
with pseudo-leukocytosis.
Results of microscopy
No small or large clump was observed in the blood smears
of the negative cases; nevertheless, paired platelets were
present in the many negative samples at an average frequency of 1.3 (per 200 platelets). In contrast, the average
frequencies of presenting paired platelets, small clumps,
and large clumps in the smears of the positive samples
were 17.7, 13.3, and 12.1 per 200 platelets, respectively.
Figure 5 roughly demonstrates the relationship between
the frequency and the PAR for each type of clump. The
results of the ADP-induced samples (Figure 5A) showed
that the variability in the frequency of each type of clump
was wide, especially for paired platelets, whose coefficient
of determination (R squared) was 0.077. Furthermore,
small and large clumps were not observed within 200
Xu et al.: Flagging features of the Sysmex XN-10 for detecting platelet clumps
753
Figure 5: Relationship between frequency and PAR for each type of platelet clump.
The relationship between the number of platelet clumps and PAR in ADP-induced positive samples (A) and clinical samples (B). Each dot
represents a positive sample. A red dot indicates that this type of clump was not observed within 200 platelets. The blue fitted lines/curve
roughly illustrate the relationships between frequency and PAR.
platelets in several cases (red points in Figure 5A). Figure 6
demonstrates that the flagging efficiency was dependent
on the number of both large clumps and paired platelets.
The efficiency was poor if only large clumps or paired
platelets increased alone, especially for paired platelets.
Figure 6: The influence of the size and number of aggregates on the
flagging efficiency.
This heatmap is plotted based on the number of paired platelets and
large clumps. The colour represents the flagging efficiency for
platelet clumps.
Discussion
Platelet count, which is routinely offered by automated HAs,
is an important parameter for evaluating haemostatic status
for clinical decision making [10]. Many factors, including
the systematic error presented by the HA and the presence
of platelet clumps, can influence its accuracy, leading to
spuriously low platelet counts [11]. Although several studies
have investigated the performance of the Sysmex haematology analyser to detect platelet clumps, few studies have
provided an explicit description of how they discover positive
samples in routine work. If the highly suspicious positive
samples are collected for selective microscopic examination,
biased or incomprehensive outcomes may be generated.
There is no uniform procedure for microscopy and no uniform
definition of platelet clumping when handling a sample with
suspected platelet clumping. Under these circumstances, a
comprehensive and nonsubjective investigation focusing on
the issue of platelet aggregates in the CBC is in demand.
Instead of microscopy, the actual reduction in platelet count
was set as the criterion of a positive sample in this study to
avoid subjectivity in positive sample collection.
The total flagging sensitivity of HA in our study is
similar to previous assessments of Sysmex HA [5–7].
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Xu et al.: Flagging features of the Sysmex XN-10 for detecting platelet clumps
However, our results also demonstrated that the flagging
algorithm of Sysmex HA was extremely insensitive to
the positive samples with platelet count higher than
140 × 109/L (Figure 3A). This implies that the flagging
mechanism of platelet clumps is not simply dependent on
the number of particles in the specific area of the WNR
scatter plot but also the platelet count. The condition of
being flagged may be more strict for samples with a platelet
count >140 × 109/L, which is likely one of the reasons for the
extremely poor sensitivity (approximately 10%) found in
Briggs’s study [12]. Nevertheless, such a threshold may
generate a false-negative result for thrombocytosis. The
platelet abnormal flag was also insensitive to the positive
samples with high platelet count (>60) but very sensitive
to those with low platelet count (≤60), although this flag is
not specifically designed for detecting platelet clumps.
These results indicate that the platelet abnormal flag is
also a strong sign of platelet clumping for the samples
with platelet count ≤60.
Because platelet clumps are resistant to lysis reagents
that disrupt red cells and assist with leukocyte differential
analysis in dedicated channels such as the white-blood-celldifferential (WDF) and white-cell-nucleated (WNR) channels
[13, 14], they will be retained in the measuring chamber
together with leukocytes and may disturb the count and differentiation of leukocytes [15, 16]. Previous articles have reported that platelet clumping spuriously elevates the
leukocyte count [17, 18]. Yufei et al. recently demonstrated a
linear relationship between PAR and leukocyte count in
blood samples that showed EDTA-dependent pseudothrombocytopenia [16]. In our study, however, there was no
significant difference in leukocyte count between positive
and negative samples. This inconsistency may be primarily
attributed to the difference in the measuring technique. The
HA employed in Yufei’s and several other similar reports was
the Coulter LH 750, in which leukocytes are enumerated only
using the impedance method [19]. By contrast, the XN-10
instrument uses the impedance method together with three
signals produced by a laser beam and fluorescent dye to
identify leukocytes, which may be subject to less interference
generated by platelet clumps. Nevertheless, we observed
three extreme cases (not only in the false-negative cases)
where the leukocyte counts were increased by over 50% due
to the false increase in both neutrophils and lymphocytes,
thus generating false markers of infection (data not shown).
The impedance technique is also used by the XN-10 instrument to count platelets and erythrocytes; therefore, the P-LCR
and MPV could be falsely increased by platelet clumps.
Interestingly, the MPV and P-LCR were decreased by clumps
in the PAR interval of 10–30%. One probable interpretation is
that when platelets are activated by ADP, they contract
rapidly to secrete granules and change their shape from
discoid to spherical [20, 21]. The contraction and shape
change of the platelet may reduce its volume and the variation in its volume, whereas the number of clumps is not
adequate to spuriously elevate the MPV and P-LCR. In addition to the above phenomena, the positive samples with PARs
of 80–90% presented a typical feature of haemolysis, which
was depicted in de Jonge’s research [22], causing a marked
reduction in erythrocytes.
Microscopic examinations of the positive samples
revealed that the size of the large clumps, to some extent,
was positively correlated with the PAR and actual platelet
count. The results of the clinical cases also showed similar
relations between the number of clumps and PAR. Herein,
the clinical cases were utilized only for comparison due to
the limited sample size. In the microscopic examination,
two positive samples with similar PARs and actual platelet
counts could exhibit quite different degrees of clumping on
the blood smears. This heterogeneity was also mentioned
in Koplitz’s study, in which blood smears made from the
same positive sample demonstrated various degrees of
platelet clumping [23]. Such a phenomenon may cause
technicians to miss some positive cases.
There are several limitations to this study: 1. We must
note the bias in age. Platelet activity and several CBC parameters are influenced by age [24–26]. 2. Citrate blood
samples also differ from EDTA samples in baseline CBC
parameters [27, 28], and the samples were collected using
citrate as an anticoagulant, which is not the routine anticoagulant for CBC. These factors may have generated bias
in the means of the CBC parameters. 3. Even though the
citrate samples were analysed within 30 min, spontaneous
platelet aggregation in the negative samples could not be
eliminated, which may have falsely elevated the number of
paired platelet clumps. 4. EDTA-dependent aggregates are
antibody mediated, and their behaviour may be different
from ADP-induced aggregates because ADP-induced activation is a rapid and shape-changing process for platelets,
while antibody-induced aggregation is a mild process that
may have no association with platelet shape [16]. 5. The
preparation of the PRP and the subsequent reconstitution
of the sample are different from the routine analysis to
obtain the CBC, which may cause inaccurate CBC results.
In summary, our study demonstrated the influence
of platelet clumping on CBC parameters and presented a
little-known flagging characteristic of the Sysmex XN-10
instrument in detecting platelet clumps. The results
showed that the Sysmex XN-10 instrument was competent for detecting platelet clumps in samples with a low
platelet count. Nevertheless, its sensitivity remains far
from satisfactory.
Xu et al.: Flagging features of the Sysmex XN-10 for detecting platelet clumps
Research funding: This work was supported by the Science
Fund of the Medical and Health Research Project of
Zhejiang Province. Project ID: 2022KY931.
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved
its submission.
Competing interests: The authors stated that there are no
conflicts of interest regarding the publication of this article.
Informed consent: Informed consent was obtained from all
individuals included in this study.
Ethical approval: The study was approved by the Institutional
Research Ethics Committee of The Third Affiliated Hospital of
Zhejiang Chinese Medical University.
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