Volume 8, Issue 2 (Journal of Clinical and Basic Research (JCBR) 2024)
jcbr 2024, 8(2): 5-9 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Patel D D, Desai P N, Prajapati J A, Patel A B, Patel A D. Red blood cell histogram in different morphological types of anemia in comparison with peripheral blood smears: A comparative analysis. jcbr 2024; 8 (2) :5-9
URL: http://jcbr.goums.ac.ir/article-1-428-en.html
URL: http://jcbr.goums.ac.ir/article-1-428-en.html
1- Department of Pathology, GMERS Medical College and Hospital, Panchmahal, Godhra, Gujarat, India , devdev966@gmail.com
2- Department of Pathology, GMERS Medical College and Hospital, Panchmahal, Godhra, Gujarat, India
3- Department of Pathology, GMERS Medical College and Hospital, Valsad, Gujarat, India
4- Navsari, Gujarat, India
2- Department of Pathology, GMERS Medical College and Hospital, Panchmahal, Godhra, Gujarat, India
3- Department of Pathology, GMERS Medical College and Hospital, Valsad, Gujarat, India
4- Navsari, Gujarat, India
Abstract: (1305 Views)
Background: Anemia is a significant health concern around the world, and it is particularly prevalent in developing nations like India. A red blood cell (RBC) histogram is a graphic representation of particle size distribution (cell frequencies vs size). The goal of this study was to examine various types of anemia in patients and compare RBC histograms and results from peripheral smears.
Methods: The study involved a total of 600 anemic patients. A histogram was produced with the use of a 5-part differential automated analyzer, following the complete mixing of the 3 mL of the EDTA blood sample. Additionally, a peripheral smear was prepared simultaneously and stained using Giemsa stain per standard operating procedures (SOP). The peripheral smear findings were then correlated with the histogram charts from the cell counter, taking into account the relevant clinical history.
Results: Out of 600 cases, 339 were females, with a female-to-male ratio of 1.3:1. The 56.2% showed moderate anemia, 31.3 % showed mild anemia, and 12.5 % showed severe anemia. Among the histogram patterns, 52.7% exhibited a left shift, 35.5% showed the normal curve, 8.6% showed a broad base curve, 1.8% showed a right shift, and 1.3% showed a bimodal curve. Blood samples were evaluated along with the corresponding peripheral smear findings. The type of anemia was diagnosed by peripheral smear. 32.8 % of the cases were normocytic normochromic anemia, and 57.0% were microcytic hypochromic anemia. Macrocytic anemia was observed only in 2.5 % of cases, and dimorphic anemia was observed only in 8.0 % of cases diagnosed with PBS. The majority of times, peripheral smear findings and histogram patterns corresponded in cases of normocytic normochromic, microcytic hypochromic, and macrocytic anemias. In 600 cases, 420 had typing findings that accorded with those of the 2 methods, while 180 had discordant typing.
Conclusion: Through its graphical representation of anemia typing, the automated analyzer helps decrease the total burden; nonetheless, it should always be verified through microscopy. As a result, it is concluded that in the era of molecular analysis and automation, the histogram alone could be used as a screening method. When combined with PBS findings, they act as a useful supplement, and by correlating the results of both methods, we could diagnose the majority of anemias.
Methods: The study involved a total of 600 anemic patients. A histogram was produced with the use of a 5-part differential automated analyzer, following the complete mixing of the 3 mL of the EDTA blood sample. Additionally, a peripheral smear was prepared simultaneously and stained using Giemsa stain per standard operating procedures (SOP). The peripheral smear findings were then correlated with the histogram charts from the cell counter, taking into account the relevant clinical history.
Results: Out of 600 cases, 339 were females, with a female-to-male ratio of 1.3:1. The 56.2% showed moderate anemia, 31.3 % showed mild anemia, and 12.5 % showed severe anemia. Among the histogram patterns, 52.7% exhibited a left shift, 35.5% showed the normal curve, 8.6% showed a broad base curve, 1.8% showed a right shift, and 1.3% showed a bimodal curve. Blood samples were evaluated along with the corresponding peripheral smear findings. The type of anemia was diagnosed by peripheral smear. 32.8 % of the cases were normocytic normochromic anemia, and 57.0% were microcytic hypochromic anemia. Macrocytic anemia was observed only in 2.5 % of cases, and dimorphic anemia was observed only in 8.0 % of cases diagnosed with PBS. The majority of times, peripheral smear findings and histogram patterns corresponded in cases of normocytic normochromic, microcytic hypochromic, and macrocytic anemias. In 600 cases, 420 had typing findings that accorded with those of the 2 methods, while 180 had discordant typing.
Conclusion: Through its graphical representation of anemia typing, the automated analyzer helps decrease the total burden; nonetheless, it should always be verified through microscopy. As a result, it is concluded that in the era of molecular analysis and automation, the histogram alone could be used as a screening method. When combined with PBS findings, they act as a useful supplement, and by correlating the results of both methods, we could diagnose the majority of anemias.
References
1. McLean E, Cogswell M, Egli I, Wojdyla D, De Benoist B. Worldwide prevalence of anaemia, WHO vitamin and mineral nutrition information system, 1993-2005. Public Health Nutr. 2009;12(4):444-54. [View at Publisher] [DOI] [PMID] [Google Scholar]
2. Lanzkowsky P. Manual of pediatric hematology and oncology. 5th ed. NewYork: Elsevier; 2005. [View at Publisher] [Google Scholar]
3. Sullivan E. Hematology analyzer: From workhorse to thoroughbred. Lab Med. 2006;37(5):273-8. [View at Publisher] [DOI] [Google Scholar]
4. Bessman JD, Gilmer PR , Gardner FH. Improved classifcation of anemias by MCV and RDW. Am J Clin Pathol. 1983;80(3):322-6. [View at Publisher] [DOI] [PMID] [Google Scholar]
5. Williams LJ. Cell histograms: New trends in data interpretation and classifcation. J Med Technol. 1984;1(3):189-97. [View at Publisher] [Google Scholar]
6. Shifa Maqsood, Sharadrutha A. Study of RBC histograms in various anemias: A six months prospective study. Perspectives in Medical Research. 2019; 7(1):40-4. [View at Publisher] [Google Scholar]
7. Bhadran DR, Mathew DSS, Jayalekshmi DB. A study on RBC histogram in different morphological types of anemia in comparison with peripheral blood smears in a tertiary care Centre in rural South India. Int J Appl Res. 2020;6(10):425-30. [View at Publisher] [Google Scholar]
8. Aravind P, Meghashree V. RBC histograms and peripheral smear study: A comparative analysis. MedPulse Int J Pathol. 2021;17(3):49-54. [View at Publisher] [DOI]
9. Chavda J, Goswami P, Goswami A. RBC histogram as diagnostic tool in anemias. IOSR Journal of Dental and Medical Sciences. 2015;14(10):19-22. [View at Publisher] [DOI] [Google Scholar]
10. Rao BSS, Vissa S, Rao NM, Grandhi B, Muramreddy V, Sirasala P. RBC Histogram as Supplementary Diagnostic Tool with Peripheral Smear Examination in Evaluating Anaemia. Annals of Pathology and Laboratory Medicine. 2017;4(6):A668-672. [View at Publisher] [DOI] [Google Scholar]
11. Shrivastav A, Shah N, Goyal S, Shah CK. RBC histogram: Utility in diagnosis of various anemia. Int J Clin Diagn Pathol. 2019;2(1):14-7. [View at Publisher] [DOI] [Google Scholar]
12. Varghese AM, Sankar S, Jayalakshmy PL. Efficacy of RBC histogram in the diagnosis of morphological types of anaemia compared with peripheral smear. Int J Res Med Sci. 2023;11(5):1653-9. [View at Publisher] [DOI]
13. Radadiya P, Mehta N, Goswami H, Gonsai RN. Automated red blood cell analysis compared with routine red blood cell morphology by smear review. NHL Journal of Medical Sciences. 2015;4(1):53-7. [View at Publisher] [Google Scholar]
14. Farah E, Mehwish A, Nafisa HA. Comparative Study in the Diagnosis of Anemia by Sysmex Kx-21n Hematology Analyzer with Peripheral Blood Smear. Int J Endors Health Sci Res (IJEHSR). 2013;1(2):89. [View at Publisher] [DOI] [Google Scholar]
15. Mukaya JE, Ddungu H, Ssali F, O'Shea T, Crowther MA. Prevalence and morphological types of anaemia and hookworm infestation in the medical emergency ward, Mulago Hospital, Uganda. S Afr Med J. 2009;99(12):881-6. [View at Publisher] [PMID] [Google Scholar]
16. Kumar A, Kushwaha R, Gupta C, Singh US. An analytical study on peripheral blood smears in anemia and correlation with cell counter generated red cell parameters. J Appl hematol. 2013;4(4):137-44. [View at Publisher] [DOI]
17. Patel S, Shah M, Patel J, Kumar N. Iron Deficiency Anemia in Moderate to Severely Anaemia Patients. Guj Med J. 2009;64(2):15-7. [View at Publisher]
18. Yogender P, Sujatha R, Rangaswamy R ,Sreekantha, Avinash S. The Study of Iron Related Parameters in Iron Deficiency Anaemia in Pregnancy. Research Journal of Pharmaceutical, Biological and Chemical Sciences. 2014;5(1):980-92. [View at Publisher]
19. Choudhary S, Bordia S, Choudhary K. Sensitivity of Red cell histogram and CBC parameters against peripheral blood smear in various anaemias. Indian Journal of Basic and Applied Medical Research. 2018;8(1):135-41. [View at Publisher] [Google Scholar]
20. Kakkar N, Makkar M. Red cell cytograms generated by an ADVIA 120 automated hematology analyzer: Characteristic patterns in common hematological conditions. LabMed. 2009;40(9):549-55. [View at Publisher] [DOI] [Google Scholar]
21. Jivani TB, Patel RP. Comparative study of RBC Histogram and peripheral smear in anaemias. Indian Journal of Pathology Research and Practice. 2019;8(6):763-7. [View at Publisher] [DOI]
22. Gupta A, Gupta P, Bhagat VM. Interpretation of Histograms and its correlation with peripheral smear findings. J Evol Med Dent Sci. 2017;6(60):4417-20. [View at Publisher] [DOI] [Google Scholar]
23. Adewoyin AS, Nwogoh B. Peripheral blood film - A review. Ann Ib Postgrad Med. 2014;12(2):71-9. [View at Publisher] [PMID] [Google Scholar]
24. LabCE. Interpretation of red blood cell rbc histograms. CE Courses. [View at Publisher]
25. Singh T. Atlas and Text of Hematology. v1; 4th ed. vichal;2019:65. [View at Publisher] [Google Scholar]
26. Novis DA, Walsh M, Wilkinson D, Louis MS, Ben-Ezra J. Laboratory productivity and the rate of manual peripheral blood smear review: A College of American Pathologists QProbes study of 95,141 complete blood count determinations performed in 263 institutions. Arch Pathol Lab Med. 2006;130(5):596-601. [View at Publisher] [DOI] [PMID] [Google Scholar]
27. Cook JD, Finch CA, Smith NJ. Evaluation of the Iron Status of a Population. Blood. 1976;48(3):449-55. [View at Publisher] [DOI] [PMID] [Google Scholar]
28. DeMayer EM, Tegman A. The Prevalence of anaemia in the World. World Health Stat Q. 1985;38(3):302-16. [View at Publisher] [Google Scholar]
29. Rahman KM, Ali KM, Vijayalakshmi S, Ramkumar S, Hashmi G. Prevalence of Iron deficiency anemia and its associated factors among reproductive age women in a rural area of Karaikal, Puducherry, India. JCDR. 2019;13(3):LC06-10. [View at Publisher] [DOI] [Google Scholar]
30. Garg M, Gitika, Sangwan K. Comparison of automated analyzer generated red blood cell parameters and histogram with peripheral smear in the diagnosis of anaemia. Int J Contemp Med Res. 2019;6(8):1-6. [View at Publisher] [DOI] [Google Scholar]
31. Fossat C, David M, Harle JR, Sainty D, Horschowski N, Verdot JJ. New parameters in erythrocyte counting. Value of histograms. Arch Pathol Lab Med. 1987;111(12):1150-4. [View at Publisher] [PMID] [Google Scholar]
32. Constantino BT .The red cell histogram and the dimorphic red cell population . Lab Med. 2011;42(5): 300-8. [View at Publisher] [DOI] [Google Scholar]
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0).