Haematology Case Study For Modern Hospitals And Clinics: Causes Of Misdiagnosis And Solutions

Discussion

Discuss about case study Haematology for Modern Hospitals and Clinics.

In modern hospitals and clinics, clinical automated haematology analysers have replaced the traditional manual method. The automated medical laboratory instruments designed to diagnose physiological, clinical or pathological conditions more accurate and faster, by measuring various chemicals and observe characteristics with a minimal human assistance. Basic automated haematology cell counters provide a complete count of Red blood cells, the mean red cell volume, white blood cells, the haemoglobin concentration as well as the hematocrit values. However, some conditions prevent the right measurement of biochemical or cellular indices of a full blood count and therefore the haematology analysers produce false results in several instances (Scoffin, 2014). The report deals with conditions where haematology analysers incorrectly measure FBC indices ad provides solutions to resolve them. Later a conclusion is drawn based on the discussion. In this report, a thorough literature review is performed to support the facts.

Despite the advantages of the automated haematology analyzers, there is a need of qualified clinical laboratory professionals to evaluate the results and minimise the errors. The cell counts produced by automated analyzers may have increased or decreased falsely. They are not accurate in differentiating nucleated red blood cells and the tiny platelet clumps. Sometimes the clumps of platelets are misclassified as lymphocytes, leukocytes. While sometimes, nucleated RBCs are misclassified as white blood cells and lymphocytes are classified as vulnerable (Brugnara, 2015).  In the subsequent sections, different conditions, which are falsely reported by hematology analysers, are discussed.

Anemia leads to decrease in RBCs, which mainly occurs due to acute haemorrhage, hemolysis, and ineffective hematopoiesis. In autoimmune haemolytic anemia RBCs are bound to antibodies, which are not well differentiated from the normal RBCs by hematalogy analysers, therefore accurate FBC is not provided (Brugnara, 2015). The “Howell-jolly bodies” are tiny fragmented parts of red cell nucleus appear as dark dots found in patient with splenectomies. On the other hand, Heinz bodies are formed due to G6PD deficiency where the denatured globins proteins stick to the RBC membrane. Hematology analysers are not specific in differentiation of Howell-jolly bodies and Heinz bodies. The former commonly represent platelets in structure resulting in increased count of platelets (Murphy, 2015). Microcytosis or schistocytosis are misdiagnosed due to underestimation of RBCs as the lower threshold of RBC counting window is greater than microcyte size.  Thalassemia trait and anemia are common causes of microcytosis (Ozcelik et al., 2012). In addition, Cold agglutinins is the condition characterised by higher concentration of IgM targeted against RBCs also called as “cold-reacting autoabntibodies”. It is also known as autoimmune haemolytic anemia.  When the RBC doublets and triplets increase the volume of the cell, RBCs are estimated as macrocytosis and are misdiagnosed as cold agglutinins (Urrechaga et al., 2013).

Solutions to resolve the conditions

Most haematologists misdiagnose Gaucher’s disease as patients can be presented with any combination of thrombocytpenia and anemia (Burnett et al., 2016). This disease is mostly misdiagnosed as leukaemia and multiple myeloma. Thrombocytopenia is the abnormally deficiency of platelet count in the blood. This condition occurs because of a separate disorder (Shihabi, 2006). A few paradigms are acute leukemia, disseminated intravascular coagulation, cirrhosis, myelodysplastic syndrome and aplastic anemia (Gersten, 2016). The automated analyzers may underestimate the platelet count in such thrombocytopenic specimens and result to misdiagnosis, due to platelet clumping, the aggregates may be identified as leukocyte (Murphy, 2015). Moreover, cryoglobulinemia occurs in a high rate in autoimmune disorders such as, systemic lupus erythematosus and rheumatoid arthritis, and infectious disorders such as, multiple myeloma and hepatitis C infection (Fujino et al., 2013). Cryoglobilins precipitate when the body temperature is low, therefore the protein precipitates will be identified as platelets in the analyzer and result in a pseudo-thrombocytopenia (Shihabi, 2006).

Furthermore, acute leukemia, chronic lymphocytic leukemia and viral infections may erroneously lower white blood cells. This phenomenon is believed to be caused from the increased fragility of leukocytes, including immature forms. In addition, cryoproteins, heparin, paraproteins, giant platelets, nucleated RBCs, platelet clumping and incomplete red cell lysis can falsely elevate WBC count by increasing significantly the rate. Moreover, the etiology of inauthentic decrease in WBC count owns to the fact of smudge cells, clotting, uremia and immunosuppressants (Wilkins, 2003).

Conclusively, new advanced haematology analysers are essential which can eliminate these limitations of traditional analysers. This misdiagnosis will result in increased death rate due to delayed treatment and severe medical errors.

Figure: 1 Disorders reducing the accuracy of cell count

(Source: www.aafp.org)

The modern haematology analysers are more advance and are developed to minimise the errors caused by false reports generated by traditional analysers. The new VCSn technology incorporated in the latest haematology analysers allows several cell measurements in addition to volume and conductivity (Fujino et al., 2013). These analysers are capable of accessing data from multiple histograms. The information can be used in multiple combinations and dozens of histograms can be generated. It assists in better differentiation of various components of  cells. The new analysers containing the VCSn data can be used across several modules including “differential, reticulocyte and nRBC modules” which improves counting and detection of important cellular elements. These are found to have greater accuracy and precise CBC-diff (Chaves, 2016).

In addition, new analysers are equipped with algorithms employing the data fusion technology (Chaves, 2016). This allows the combination of multiple sources of information collected from different modules and identification of patterns indicating the presence of cellular elements, which was not possible using analysers that uses single module (Brugnara, 2015). This minimises the samples being flagged for the interfering particle therefore accurate results are obtained in a first attempt. New analysers provide several histograms with the help of two of the new angles of light scatter such as “Axial light loss (AL2)” and low angle light scatter (RLALS). This are applicable in nRBC count and can differentiate the causes of several cellular interference in the WBC count such as nRBCs, giant platetlets, platelet aggregation, intra-cellular parasites. The data fusion technology eliminates the requirement of manual labour of sample review and professionals to correct the WBC count (See figure 1 below). This functions because giant platelets are recognised by platelet measurement information and NRBC module and the WBC algorithm correlates this with detected interference. According to (Wu, J., Buhl & Vacca, 2015) “polarised light” measurement are accurate in differentiating neutrophils and eosinophils. Eosinophils are able to disturb the polarisation of the laser beam. Use of fluorescence by nuclear stains have accelerated with the advancement in optical technology advance and found to be highly efficient in enumeration of nucleated RBCs. In addition, the platelet analysis has been found to be less prone to interference. It was found from the study of Zhao et al., (2014), that multi-angle light scatter and florescent dyes have been a great success in enhancing the differentiation of giant platelets and RBCs fragments.

Figure: 1

Figure: 2 Laser light scattering technique

(Source: www.anlyticondiagnostic.com)

New advanced Automated haematology analysers use “multi-purpose reagent system” (Kuang et al., 2015). The blood cell lysing reagents allows enumeration of WBCs by removing the RBCs. It can also determine the hemaoglobin without the use of toxic cyanide anion. The blood diluting reagents improves the counting properties by enhancing the size of the blood specimens and stabilising the cellular volume and integrity for long duration. The second lysing reagents assist in differential determination of WBCs into classes based on functionality and size. This reagent is mainly isotonic blood diluters, and haemoglobin converters. The advanced automated haematology analysers use “lysing reagents” along with a “companion quenching” which differentiates blood cells according to the size based on conductivity/opacity d.c. impedence volume and light scatter measurements. These reagents greatly reduce the limitations of the previous automated analysers and provide better diagnostic aid. The combination of the reagent formulation improves the calibrations by providing the scattergrams of WBCs well delineated and confined to the analyser software (Krockenberger et al., 2014).

Conclusion

Automated haematology analysers designed to achieve operational efficiency and clinical effectiveness in the laboratories by conserving time, cost and produce more precise and accurate results. Physicians can make better clinical decisions by ensuring the correct calibrations of haematology instruments. Despite this sophistication, to improve the laboratory operations and significantly optimize the patient’s care, the automated methods should always be validated by manual microscopic blood examination, especially when blood cell morphology and differential leukocyte count is associated (Samuel O, 2010). The peer-reviewed article has not yet confirmed any pitfalls of the VCS technology. The error prone area is mainly the pre-analytical stage. The limitation of the multipurpose reagent system is the removal of toxicity of the components which otherwise will result in destabilisation of the haematology analysis system.

References

Brugnara, C. (2015). Automated Hematology Analyzers: State of the Art, An Issue of Clinics in Laboratory Medicine (Vol. 35, No. 1). Elsevier Health Sciences.

Burnett, A. E., Bowles, H., Borrego, M. E., Montoya, T. N., Garcia, D. A., & Mahan, C. (2016). Heparin-induced thrombocytopenia: reducing misdiagnosis via collaboration between an inpatient anticoagulation pharmacy service and hospital reference laboratory. Journal of thrombosis and thrombolysis, 1-8.

Chaves, F. (2016). Technological advances in today’s hematology analyzers: how they address common laboratory challenges | MLO. Mlo-online.com. Retrieved 2 September 2016, from https://www.mlo-online.com/technological-advances-in-todays-hematology-analyzers-how-they-address-common-laboratory-challenges.php

Fujino, Y., Nakamura, Y., Matsumoto, H., Fukushima, K., Takahashi, M., Ohno, K., & Tsujimoto, H. (2013). Development and evaluation of a novel in-clinic automated hematology analyzer, ProCyte Dx, for canine erythrocyte indices, leukogram, platelet counts and reticulocyte counts. The Journal of Veterinary Medical Science, 75(11), 1519.

Gersten, T. (2016, 2 12). Thrombocytopenia. Retrieved from MedlinePlus: https://medlineplus.gov/ency/article/000586.htm

Greer, J. P. (2008). Wintrobe’s Clinical Hematology, Volume 1. Lippincott Williams and Wilkins . Retrieved from https://books.google.co.in/books?id=68enzUD7BVgC&pg=PA6&lpg=PA6&dq=hyperosmolarity+cause+automatic+analysers+to+produce+false+results&source=bl&ots=fFJPhJSa0y&sig=uoSl1Mvz3JFCn_Q21fO3DDcu8X4&hl=en&sa=X&ved=0ahUKEwjctam_r97OAhXCGJQKHWu6DXMQ6AEIGzAA#v=onepa

Krockenberger, M., Wu, J., Roemer, B., & Vacca, G. (2014). U.S. Patent No. 8,906,309. Washington, DC: U.S. Patent and Trademark Office.

Kuang, Y., Zhang, B., Xu, B., Shao, J., Lei, T., & Zhang, L. (2015). U.S. Patent No. 8,940,499. Washington, DC: U.S. Patent and Trademark Office.

Murphy, J. (2015, June ). The Immune System and Its Link to Rheumatic Disease. Retrieved from American College of Rheumatology: https://www.rheumatology.org/I-Am-A/Patient-Caregiver/Diseases-Conditions/Living-Well-with-Rheumatic-Disease/The-Immune-System-Its-Link-to-Rheumatic-Disease

Ozcelik, F., Arslan, E., Serdar, M. A., Yiginer, O., Oztosun, M., Kayadibi, H., & Kurt, I. (2012). A useful method for the detection of ethylenediaminetetraacetic acid-and cold agglutinin-dependent pseudothrombocytopenia. The American journal of the medical sciences,344(5), 357-362.

Samuel O, T. N. (2010, April 23). Comparison of haematological parameters determined by the Sysmex KX – 2IN automated haematology analyzer and the manual counts. Retrieved from BioMed Central: https://bmcclinpathol.biomedcentral.com/articles/10.1186/1472-6890-10-3

Scoffin, K. (2014, May 23). Hematology Analyzers—From Complete Blood Counts to Cell Morphology. Retrieved from labcompare: https://www.labcompare.com/10-Featured-Articles/162042-Hematology-Analyzers-From-Complete-Blood-Counts-to-Cell-Morphology/

Shihabi, Z. K. (2006). Cryoglobulins: An Important but Neglected Clinical Test. Retrieved from Annals of Clinical & Laboratory Science: https://www.annclinlabsci.org/content/36/4/395.long

Urrechaga, E., Izquierdo, S., & Escanero, J. F. (2013). Microcytic anemia still a health problem in the third millennium. Intern J Transl Comm Med, 2, 1-3.

Wilkins, L. W. (2003). Blood: Principles and Practice of Hematology, Volume 1 (Vol. 1). Philadelphia.

Wu, J., Buhl, M. R., & Vacca, G. (2015). U.S. Patent Application No. 14/808,211.

Zhao, Y., Lei, T., Zhao, Y., & Xu, B. (2014). U.S. Patent No. 8,685,661. Washington, DC: U.S. Patent and Trademark Office.