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  Table of Contents    
ORIGINAL ARTICLE  
Year : 2012  |  Volume : 55  |  Issue : 4  |  Page : 467-473
Usefulness of automated cell counter in detection of malaria in a cancer set up-Our experience


1 Department of Oncopathology, Delhi State Cancer Institute, Dilshad Garden, Delhi, India
2 Department of Clinical Oncology, Delhi State Cancer Institute, Dilshad Garden, Delhi, India

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Date of Web Publication4-Mar-2013
 

   Abstract 

Background: Malaria diagnosis presents a challenge to all laboratories. In malaria-endemic areas, there is a need for rapid, sensitive and cost-effective method to effectively screen all samples, especially when the workload is very high. Various hematology analyzers have been investigated for detection of malaria in the past. Here, we present our experience of malaria detection in a cancer hospital where a large number of complete blood count requests are received either before or during chemotherapy. Fever, being a very common symptom in cancer patients, causes a suspicion of malaria. Aim: This study was conducted to assess the usefulness of hematology cell counter, viz. WBC-DIFF and WBC/BASO scatter plots and the flaggings generated in malaria-positive cases. The occurrence of pseudoeosinophilia as reported by previous studies was also assessed. The parasitic index was determined and its correlation with the abnormalities found on the Hematology analyzer was also studied. Materials and Methods: Blood samples were collected from 80 out-patient department and inpatients with various solid as well as hematological malignancies, who presented with acute febrile illness during September 2010 and January 2012, and for whom complete blood cell analysis and peripheral smear for malaria parasite had been requested. Results: Of the 80 patients who presented with fever and suspicion of malaria, 29 patients were positive for malaria and 10 cases were diagnosed incidentally by the findings on the cell counter and were confirmed by Giemsa-stained blood smears. The sensitivity and specificity of the abnormalities detected in the WBC-Diff channel in detecting malaria is 82% and 100% respectively. Using WBC-BASO channel abnormality for initial diagnosis the sensitivity and specificity is 50% and 92.5% respectively. The sensitivity and specificity with respect to pseudoeosinophilia is 18% and 100% respectively. The most common WBC and PLT flags were leukopenia, atypical lymphocytes, lymphopenia, WBC abnormal scattergram, platelet clumps, thrombocytopenia, platelet abnormal distribution flag. Conclusion: The instrument provides significantly valuable diagnostic parameters in detecting acute Plasmodium vivax malaria; however, it is not very useful for acute falciparum malaria infection. It is suggested that the laboratories using the hematology analyzers should be aware of such specific parameters, even in the absence of a clinical request.

Keywords: Hematology analyzer, malaria, pseudoeosinophilia, WBC scattergram

How to cite this article:
Jain M, Gupta S, Jain J, Grover RK. Usefulness of automated cell counter in detection of malaria in a cancer set up-Our experience. Indian J Pathol Microbiol 2012;55:467-73

How to cite this URL:
Jain M, Gupta S, Jain J, Grover RK. Usefulness of automated cell counter in detection of malaria in a cancer set up-Our experience. Indian J Pathol Microbiol [serial online] 2012 [cited 2019 Nov 17];55:467-73. Available from: http://www.ijpmonline.org/text.asp?2012/55/4/467/107782



   Introduction Top


Malaria is one of the most important parasitic diseases worldwide. Many rapid, sensitive, and cost-effective screening tests have been developed for its diagnosis, particularly where malaria is endemic; however, all these rely on clinical suspicion and a request. In a busy cancer setup, where large numbers of complete blood counts are requested before start and during chemotherapy and where fever is a common symptom, it is important to distinguish the origin of fever, as a prompt and accurate diagnosis would reduce outcomes associated with malaria, including death. In recent times, there has been a growing interest in the use of hematology analyzers for presumptive diagnosis of malarial infection.

The aim of the present study was to determine the usefulness of flow cytometry based cell counter, Sysmex XE- 2100 (Sysmex Corporation, Kobe, Japan) for the diagnosis of malaria in a routine laboratory setting in a cancer hospital and to study the correlation of parasitic index with the abnormalities detected on it. The hematological parameters, for example, hemoglobin (Hb), total leukocyte count (TLC), and platelet (PLT) count, have also been studied in the febrile patients with or without malaria.

This instrument uses combined impedance and radiofrequency conductance detection, semiconductor diode laser light 90° side scatter (SSC) and 0° forward scatter (FSC) detection, and polymethine fluorescence (SFL) detection. The analyzer differentiates WBCs using side fluorescence and side scattered light. An organic acid reagent binds specifically to the granules of eosinophils and allows them to be discriminated from neutrophils based on their higher SSC signal intensities. The WBC/BASO scattergram is obtained by lysis of all the WBCs except the basophils, following which the FSC and SSC information is used to obtain the WBC/BASO scattergram.


   Materials and Methods Top


Blood samples were collected from 80 out-patient department and inpatients with various solid as well as hematological malignancies, who presented with acute febrile illness during September 2010 and January 2012, and for whom complete blood cell analysis and peripheral smear for malarial parasite had been requested. Peripheral blood samples were collected into K 2 EDTA tubes (Becton Dickinson) and were analyzed on XE- 2100 hematology analyzer. All samples were analyzed within 2 h of collection. The analyzer had been calibrated with the Sysmex SCS-1000 calibrator once a year. The controls using three levels of e-check were run daily and the instrument was maintained as per the manufacturer's instructions.

The hematological data (Hb, TLC, PLT) for all patients were collected. Statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS) program (version 12.0 for Windows; SPSS Inc., Chicago, IL, USA). Data were expressed in mean ± SD. Student's t-test was used to compare continuous variables between groups. P values of <0.05 were considered to be statistically significant.

The diagnosis of malaria was made by examining Giemsa-stained thin blood smears. The smears were examined by experienced hematopathologists, and manual WBC differential and PLT counts were done on Giemsa-stained smears. Samples were regarded negative after examining at least 200 fields of thin smears under oil immersion. Parasite index was determined by counting the number of parasites per 1000 red blood cells in a thin blood smear and dividing it by 10 to get it in percentage. [1]

The various abnormalities noted on the hematology cell counter were analyzed, for example, WBC-DIFF and WBC/BASO scatter plots and the flaggings generated in malaria-positive cases.

The occurrence of pseudoeosinophilia as reported by previous studies was also assessed. Pseudoeosinophilia was said to be present when the difference between manual and automated differential count was ≥5%. [2] The parasitic index was determined and its correlation with the abnormalities found on the hematology analyzer was studied.


   Results Top


Peripheral smears for a total of 80 cancer patients who presented with fever were examined for malarial parasite, out of which 29 samples were positive for malaria on peripheral smear. Ten cases were diagnosed incidentally from the findings on the cell counter which were then confirmed on peripheral smears. The total number of malaria-positive cases was 39. Thirty-one were positive for Plasmodium vivax and 8 for Plasmodium falciparum.

Hematological Parameters

[Table 1] shows the comparison of different variables in the malaria and non-malaria groups. The Hb, TLC, and PLT counts were reduced in malaria-positive group as compared to malaria-negative group; however, only the PLT counts showed statistically significant difference (P < 0.0001).
Table 1: Age and hematological parameters in the malaria and non-malaria groups

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Hematology Analyzer Graphical Analysis

WBC-DIFF channel

The various patterns seen in the WBC-DIFF channel include merging, graying, and multiple neutrophil and eosinophil clusters; prominent blue-coded (in the RBC ghost region) events beneath the neutrophil and/or eosinophil cluster; merging of eosinophil and/or neutrophil cluster with blue-coded events (in the RBC ghost region); prominent blue-coded events with no other abnormality; and irregular shape of neutrophil cluster [Figure 2].

The various abnormalities noted in DIFF channel were seen in 32 out of 39 cases. The controls (n = 51) showed well-separated neutrophil and eosinophil clusters and no abnormality with respect to WBC-DIFF channel. Therefore, the sensitivity and specificity of the abnormalities detected in the WBC-DIFF channel in detecting malaria were 82% and 100%, respectively.

In the P. vivax group, the WBC-DIFF channel abnormalities were seen in 28 of 31 cases (sensitivity 90%).

In the P. falciparum group, the WBC-DIFF channel abnormalities were seen in 4 of 8 cases (sensitivity 50%).

Pseudoeosinophilia

Out of 39 malaria-positive cases, WBC differential was given by the counter in 30 cases and WBC differential was given in the research mode in 2 cases. Pseudoeosinophilia was noted in 7 out of 32 cases where differential was given by the counter.

In the control group (n = 51), eosinophilia was noted in 2 cases, which was consistent with microscopy.

Using pseudoeosinophilia for initial diagnosis, the sensitivity and specificity were 18% and 100%, respectively.

In the P. falciparum group, only one case showed pseudoeosinophilia [Table 3].

WBC/BASO channel

Of the 39 cases, 19 cases showed prominent blue-coded events in the area III as described by Campuzano-Zuluaga et al[3] [Figure 4] in the WBC/BASO channel, as compared to the control group (n = 51) which showed such findings in only 3 of 40 cases.

Using WBC/BASO channel abnormality for initial diagnosis, the sensitivity and specificity were 50% and 92.5%, respectively. In the P. falciparum group, no case showed WBC/BASO channel abnormality.

WBC and PLT flaggings

Of the 39 malaria-infected cases, the most common WBC and PLT flags were leukopenia, atypical lymphocytes, lymphopenia, WBC abnormal scattergram, PLT clumps, thrombocytopenia, and PLT abnormal distribution flag [Table 3] and [Table 4]. Three cases showed no WBC and PLT flag.


   Discussion Top


The hematological parameters such as Hb, TLC, and PLT were lowered in malaria-positive patients as compared to the malaria negatives. In the majority of malarial infections, the Hb falls to some degree and the degree of anemia is related to the cumulative parasite density. [4] Two possible causes of this anemia are increased hemolysis and a decreased rate of erythrocyte production. [1] Leukopenia appears to be a relatively common finding in nonimmune adults with malaria. Thrombocytopenia has been identified as a key indicator of malarial infection and is a result of peripheral destruction and consumption. Immune complexes generated by malarial antigen lead to sequestration of the injured platelets by macrophages in the spleen. PLT consumption in disseminated intravascular coagulation contributes to thrombocytopenia in complicated P. falciparum malaria. [5]

In our patients, the Hb, TLC, and PLT were reduced in the malaria group as compared to the non-malaria group. But only the reduction in PLT counts showed statistically significant difference between the two groups (P < 0.0001). However, cancer patients can have varied hematological parameters either due to the disease itself or due to the chemotherapeutic drugs administered.

Microscopic detection and identification of Plasmodium species in Giemsa-stained thick blood films (for screening) and thin blood films (for species confirmation) is the accepted worldwide "gold standard" used for the routine laboratory diagnosis of malaria. [1] During the past decade, efforts to replace the traditional blood film for the diagnosis of malaria have been made. Polymerase chain reaction has been proven to be sensitive in the diagnosis of all four species of malaria. [6] However, it is expensive and impractical in the routine diagnosis of malaria. The quick buffy coat (QBC) blood parasite detection method is used in some laboratories as a backup to blood films or as an initial screening technique. The disadvantages of this method are the high cost of the equipment and also the fluorescent stain which is nonspecific,  Howell-Jolly bodies More Details fluorescing with acridine orange, and the specificity for non-P. falciparum malaria is low owing to the denser late stages of parasites, which may be hidden in the mononuclear layer. [7]

Recently there has been a growing interest in the use of routine hematological blood analysis for presumptive diagnosis of malarial infection. Usefulness of automated blood cell counters for detecting malaria has been reported in the literature. The Cell-Dyn 3500 was the first autoanalyzer that allowed the detection of malaria during routine investigation by complete blood cell analysis. [8] It uses scattered laser light of leukocytes at four different angles to generate a WBC differential. [9] The instrument detects birefringent depolarizing malaria pigment ingested by monocytes and neutrophils. The appearance of monocytes (purple dots) above the separation line, in the eosinophil area (green dots), is a highly specific sign of the presence of ingested malaria pigment and consequently malaria. [10],[11] However, the changes may persist for some time despite clinical and parasitological cure, as pigment-containing monocytes may remain in the circulation for 2-3 weeks. [12] Consequently, the observed changes may not necessarily indicate acute disease, but may persist during convalescence.

Briggs et al.[13] suggested the use of the Standard deviation(SD) volume of lymphocytes and monocytes to flag for the possible presence of malarial parasites. Due to the presence of reactive lymphocytes and histiocytic monocytes in infected patients, these cells are increased in size and therefore have increased volumes and SD of the volumes. The combination of these changes has allowed the development of an algorithm for this (Malaria Factor). Using a cut-off value for the Malaria Factor of greater than 3.7 as an indicator of malarial infection, the specificity was 94% and sensitivity was 98%.

Diagnosis of malaria using Sysmex XE-2100 has also been reported in the past. [2],[3],[14],[15]

The WBC-DIFF channel differentiates leukocytes using SSC light (reflecting the complexity of cell contents) and side fluorescence intensity (SFL, reflecting the nucleic acid content). The lysing reagent for leukocytes contains macromolecular organic acid. This acid binds specifically to the eosinophil (EO) granules, thus increasing the complexity of the EO cell contents. Consequently, the eosinophils can be distinguished from neutrophils [16] [Figure 1].
Figure 1: WBC-DIFF scattergram of XE- 2100

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In our study, the WBC-DIFF scatter plot abnormalities included merging, graying, and multiple neutrophil and eosinophil clusters; prominent deep blue-coded events (in the RBC ghost region) beneath the neutrophil and/or eosinophil cluster; merging of eosinophil and/or neutrophil cluster with blue-coded events (in the RBC ghost region); prominent deep blue-coded events with no other abnormality; and irregular shape of neutrophil cluster [Figure 2]. The sensitivity and specificity of the abnormalities detected in the WBC-DIFF channel in detecting malaria were 82% and 100%, respectively.
Figure 2: Representative WBC-DIFF scatter plots of samples from P. vivax and P. falciparum patients

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In the P. vivax group, the WBC-DIFF channel abnormalities were seen in 28 of 31 cases (sensitivity 90%). The three cases which were negative for the WBC-DIFF channel abnormalities showed early ring forms [Table 2] and [Figure 3]. The abnormalities noted were not related to the parasitic index but to the presence of trophozoites, schizonts, or the ring forms. Increased number of late trophozoites and schizonts positively correlated with the WBC-DIFF scatter plot abnormalities, in comparison to early ring forms. The abnormalities noted in 28 cases were mostly multiple neutrophil and/or eosinophil clusters, graying of neutrophil and/or eosinophil cluster, and abnormal shape of neutrophil cluster.
Figure 3: P. vivax cases with no WBC-DIFF channel abnormalities

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Figure 4: WBC/BASO channel abnormality as in area III described by Campazuana et al. and cases from the present study

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Table 2: Cases of P. vivax negative for WBC-DIFF scatter plot

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In the P. falciparum group, the WBC-DIFF channel abnormalities were seen in four of eight cases (sensitivity 50%). The abnormalities noted were not related to the parasitic index but were seen in cases with prominent gametocytes. The cases with prominent ring forms showed no abnormality in the WBC-DIFF scatter plot [Table 3]. Two cases of P. falciparum showed only occasional gametocytes, but still showed WBC-DIFF scatter plot abnormality. The abnormalities seen in four cases were prominent deep blue-coded events beneath neutrophil and/or eosinophil cluster [Figure 5]. Therefore, the WBC-DIFF scatter plot abnormalities are not helpful in detecting acute and severe P. falciparum infections.
Figure 5: Positive WBC-DIFF scattergrams of P. falciparum cases

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Table 3: Profile of P. falciparum cases

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Similar findings in the WBC-DIFF scatter plot had been described by Huh et al.[15] Using the abnormal WBC scattergrams for initial diagnosis, the sensitivity and specificity were 52.1% and 100%, respectively.

Yoo et al.[17] described a sensitivity and specificity of 15.7% and 99.7%, respectively, in relation with abnormalities on WBC-DIFF scattergram. A remarkable reduction in sensitivity in this study was cited due to the presence of younger and fewer circulating parasites, severity of infection, and host immunity factors, which produce less hemozoin and were below the analyzer detection limits. The parasitemia, however, in this study was determined using reverse transcription polymerase chain reaction (RT-PCR) technology.

Pseudoeosinophilia was noted in 7 out of 32 cases where differential was given by the counter.

In the control group (n = 51), eosinophilia was noted in 2 cases, which was consistent with microscopy. Using pseudoeosinophilia for initial diagnosis, the sensitivity and specificity were 18% and 100%, respectively. In the P. falciparum group, only one case showed pseudoeosinophilia [Table 3]. In our study, pseudoeosinophilia did not correlate with the parasitic counts. However, this requires microscopic evaluation and a manual calculation, limiting its applicability in clinical scenarios.

Two case series from South Korea, one with 16 cases and the other with 3 cases of P. vivax infected patients, reported pseudoeosinophilia and atypical eosinophil distribution in the WBC scattergram in 38% and 100% cases, respectively. [3],[14]

In another study of the 144 samples from P. vivax infected patients, pseudoeosinophilia (>5% difference between the automated and manual eosinophil count) or abnormal WBC scattergram was detected in 100 of 144 malaria-positive samples (sensitivity 69.4%, specificity 100%). Fifty-six (38.9%) patients showed only pseudoeosinophilia. Using pseudoeosinophilia for the diagnosis, the sensitivity and specificity were 39.0% and 100%, respectively. The samples with pseudoeosinophilia or abnormal WBC scattergram also showed significantly higher parasite counts than the samples without these features. [15]

Yoo et al.[17] in their study demonstrated either pseudoeosinophilia or abnormal WBC scattergram in 191 of 413 malaria patients and 4 of 1388 patients without malaria (sensitivity =46.2%, specificity =99.7%). This study also showed that samples with pseudoeosinophilia or abnormal WBC scattergrams had significantly higher parasite counts and lower platelet counts than the samples without pseudoeosinophilia or abnormal WBC scattergrams.

Huh et al.[15] reported pseudoeosinophilia in 6 of 16 malaria-infected patients (38%).

The WBC-DIFF channel abnormalities and pseudoeosinophilia noted are as a result of hemozoin containing neutrophils which, due to high SSC properties, are either placed in the eosinophil region giving rise to pseudoeosinophilia or manifest as multiple neutrophil clusters, fusion of neutrophil and eosinophil clusters. Presence of late trophozoites and schizonts positively correlates with the abnormal findings on WBC-DIFF scatter plot abnormalities as the pigment ingested by neutrophils is wrongly classified as eosinophils or as multiple neutrophil clusters. The erythrocytes and the reticulocytes infected with malaria have significantly increased nucleic acid content, and will appear prominent in the RBC ghost area resulting in additional deep blue-coded events and fusion of blue-coded events either with neutrophil cluster or with eosinophil cluster.

Using WBC/BASO channel abnormality for initial diagnosis, the sensitivity and specificity were 50% and 92.5%, respectively, in our study. In the P. falciparum group, no case showed WBC/BASO channel abnormality.

Campuzano-zuluaga et al.[3] found that P. vivax samples also showed abnormalities in WBC/BASO and RET-EXT scatter plots apart from WBC-DIFF scatter plots. For the WBC/BASO (III) counting area, ≥7 blue-coded events (pixels) had a sensitivity and specificity of 97% and 94%, respectively, for P. vivax and ≥3 pixels had a sensitivity and specificity of 60% and 67%, respectively, for P. falciparum. This study found a significant moderate-to-high correlation for most abnormalities in the DIFF, WBC/BASO, and RET-EXT scatter plots and the concentration of P. vivax mature trophozoites, schizonts, or gametocytes.

Again the prominent blue-coded event in the WBC/BASO channel is due to the erythrocytes and reticulocytes infected by malaria, which appears in the RBC ghost area. As all forms of parasites are present in P. vivax infection as compared to P. falciparum infection, the prominent blue-coded events are more often seen with the former than the latter.

The various WBC and platelet flaggings noted in our study were leukopenia, thrombocytopenia, atypical lymphocytes, lymphopenia, WBC abnormal scattergram, and PLT abnormal distribution flag [Table 4]. The atypical lymphocyte flag is due to the presence of activated lymphoid cells seen in cases of malaria. Lymphopenia is a common finding in acute malaria in non-immune adults. The transient reduction in the circulating lymphocytes in malaria may theoretically be due to either destruction or redistribution of lymphocytes. [18] The TLC is done in the WBC-DIFF channel and WBC/BASO channel, and when the ratio of the two channels is not close to 1, it results in display of the WBC abnormal scattergram flag. Other causes include impossibility of the calculation of 5-DIFF data and ghost interference to WBC. The PLT abnormal distribution flag could be due to PLT aggregation that occurs in vivo in patients with Plasmodium infection, and there is a positive relationship between peripheral parasitemia and the degree of PLT aggregation. [19]
Table 4: Flaggings generated by the cell counter in malaria-positive cases

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Fever in cancer patients is quiet common and remains a challenge, and the differentiation between infectious and non-infectious causes at the onset of fever is very difficult. Despite all the prophylactic measures, infection is still the principal cause and in an immunocompromised host is a serious clinical situation due to high morbidity and mortality, and therefore it is important to distinguish the origin of a fever, as the management of the patient will be different. One of the most important advantages of the blood cell analyzers is that it would allow for a timely diagnosis of malaria which was not suspected clinically and which otherwise could go undetected leading to adverse clinical outcomes.

In conclusion, in a laboratory setting where the diagnosis of malaria may be initially overlooked, one should be aware of such specific patterns so that even in the absence of a clinical request, a diagnosis of malaria may not be missed. Therefore, it is recommended for hematopathologists to review the hematological data and the scatter plots on the analyzer at least once in a day's work to pick some of the unsuspected cases. However, these patterns when present could only suggest a diagnosis of malaria and such cases should always be confirmed by a peripheral blood smear examination.


   Acknowledgments Top


The authors wish to thank the senior residents (Oncopathology) and the technical staff of laboratory for their sincere work.

 
   References Top

1.Warhurst DC, Williams JE. ACP Broadsheet no 148. July 1996. Laboratory diagnosis of malaria. J Clin Pathol 1996;49:533-8.  Back to cited text no. 1
    
2.Huh J, Jung J, Yoon H, Chung W. Pseudoeosinophilia associated with malaria infection determined in the Sysmex XE-2100 hematology analyzer. Ann Hematol 2005;84:400-2.  Back to cited text no. 2
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3.Campuzano-Zuluaga G, Alvarez-Sánchez G, Escobar-Gallo GE, Valencia-Zuluaga LM, Ríos-Orrego AM, Pabón-Vidal A, et al. Design of malaria diagnostic criteria for the Sysmex XE-2100 hematology analyzer. Am J Trop Med Hyg 2010;82:402-11.  Back to cited text no. 3
    
4.Ekvall H, Premji Z, Bennett S, Bjorkman A. Hemoglobin concentration in children in a malaria holoendemic area is determined by cumulated Plasmodium falciparum parasite densities. Am J Trop Med Hyg 2001;64:58-66.  Back to cited text no. 4
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5.Mohanty D, Marwaha N, Ghosh K, Sharma S, Garewal G, Shah S et al. Functional and ultrastructural changes of platelets in malarial infection. Trans R Soc Trop Med Hyg 1988;82:369-75.  Back to cited text no. 5
    
6.Snounou G, Viriyakosol S, Jarra W, Thaithong S, Brown KN. Identification of four human malaria species in field samples by the polymerase chain reaction and detection of high prevalence of mixed infections. Mol Biochem Parasitol 1993;58:283-92.  Back to cited text no. 6
    
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8.Hanscheid T, Pinto BG, Pereira I, Cristino JM, Valadas E. Avoiding misdiagnosis of malaria: A novel automated method allows specific diagnosis, even in the absence of clinical suspicion. Emerg Infect Dis 1999;5:836-38.  Back to cited text no. 8
    
9.deGrooth BG, Terstappen LW, Puppels GJ, Greve J. Light-scattering polarization measurements as a new parameter in flow cytometry. Cytometry 1987;8:539-44.  Back to cited text no. 9
    
10.Mendelow BV, Lyons C, Nhlangothi P, Tana M, Munster M, Wypkema E, et al. Automated malaria detection by depolarization of laser light. Br J Haematol 1999;104:499-503.  Back to cited text no. 10
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11.Hanscheid T, Valadas E, Grobusch MP. Automated malaria diagnosis using pigment detection. Parasitol Today 2000;16:549-51.  Back to cited text no. 11
    
12.Day NP, Pham TD, Phan TL, Dinh XS, Pham PL, Ly VC, et al. Clearance kinetics of parasite and pigment-containing leukocytes in severe malaria. Blood 1996;88:694-700.  Back to cited text no. 12
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14.Park GB, Cha YJ. Three cases of pseudoeosinophilia associated with malaria determined in the sysmex xe-2100 automated hematology analyzer. Korean J Lab Med 2006;26:77-80.  Back to cited text no. 14
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15.Huh HJ, Oh GY, Huh JW, Chae SL. Malaria detection with the Sysmex XE-2100 hematology analyzer using pseudoeosinophilia and abnormal WBC scattergram. Ann Hematol 2008;87:755-9.  Back to cited text no. 15
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Correspondence Address:
Monica Jain
Department of Oncopathology, Delhi State Cancer Institute, Dilshad Garden, Delhi
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0377-4929.107782

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