ANALYSIS OF LABORATORY RESULTS IN PATIENTS WITH ACUTE LEUKEMIA
Ключевые слова:
CBC, myelogram, acute leukemia, blasts.Аннотация
To analyze laboratory changes in peripheral blood and myelogram in adult patients with acute leukemias.
Methods. The material for clinical and laboratory studies in the work were patients with AL (n=102) who sought diagnostic help and subsequent inpatient examination at the republican specialized Scientific and Practical Medical Center of Hematology (RSSPMCH, Tashkent) from 2019 to 2023. Patients with AL were aged from 18 to 74 years, while the median age was 37.0±1.5 years. The diagnosis was made taking into account clinical and laboratory data.
The research methods included laboratory examination (complete blood count (CBC) and myelogram) and statistical methods for data processing using the applied PC software package “OpenEpi 2009, Version 2.3”.
Conclusions. The severity of changes in peripheral blood and bone marrow, characterized by erythropenia, thrombocytopenia, blastosis, and reduced mature neutrophils common to all acute leukemia variants, differs in depth and severity in cases of T-ALL.
To analyze laboratory changes in peripheral blood and myelogram in adult patients with acute leukemia.
Methods. The material for clinical and laboratory research consisted of patients with acute leukemia (n=102) who sought diagnostic assistance and subsequent inpatient examination at the Republican Specialized Hematology Scientific and Practical Medical Center (RSSPMCH, Tashkent) from 2019 to 2023. Patients with acute leukemia were aged from 18 to 74 years, with an average age of 37.0±1.5 years. The diagnosis was established based on clinical and laboratory data.
The research methods included laboratory examination (clinical (complete) blood count (CBC) and myelogram) and statistical methods for processing results using the OpenEpi 2009, Version 2.3 software package.
Conclusion. The severity of changes in peripheral blood and bone marrow characteristic of all variants of acute leukemia, including erythro- and thrombocytopenia, blastosis, and reduction of mature neutrophils, is distinguished by the depth and severity of disturbances in T-ALL.
Библиографические ссылки
REFERENCES
1. Anilkumar K. K., Manoj V. J., Sagi T. M. Automated detection of b cell and t cell acute lymphoblastic leukaemia using deep learning //Irbm. – 2022. – Т. 43. – №. 5. – С. 405-413.
2. Ansari S. et al. A customized efficient deep learning model for the diagnosis of acute leukemia cells based on lymphocyte and monocyte images //Electronics. – 2023. – Т. 12. – №. 2. – С. 322.
3. Arber D. A. et al. Initial diagnostic workup of acute leukemia: guideline from the College of American Pathologists and the American Society of Hematology //Archives of pathology & laboratory medicine. – 2017. – Т. 141. – №. 10. – С. 1342-1393.
4. Behrmann L., Wellbrock J., Fiedler W. Acute myeloid leukemia and the bone marrow niche—take a closer look //Frontiers in oncology. – 2018. – Т. 8. – С. 444.
5. Boldú L. et al. A deep learning model (ALNet) for the diagnosis of acute leukaemia lineage using peripheral blood cell images //Computer Methods and Programs in Biomedicine. – 2021. – Т. 202. – С. 105999.
6. Godínez-Chaparro J. A. et al. Leukemia cutis and other dermatological findings in pediatric patients with acute myeloid leukemia //Boletín médico del Hospital Infantil de México. – 2021. – Т. 78. – №. 5. – С. 411-417.
7. Hansen B. A. et al. Febrile neutropenia in acute leukemia. Epidemiology, etiology, pathophysiology and treatment //Mediterranean journal of hematology and infectious diseases. – 2020. – Т. 12. – №. 1.
8. Liu Q. et al. Immunorelated gene polymorphisms associated with acute myeloid leukemia //Clinical & Exper imental Immunology. – 2020. – Т. 201. – №. 3. – С. 266-278.
9. Narayanan D., Weinberg O. K. How I investigate acute myeloid leukemia //International journal of laboratory hematology. – 2020. – Т. 42. – №. 1. – С. 3-15.
10. Rastogi P., Khanna K., Singh V. LeuFeatx: Deep learning–based feature extractor for the diagnosis of acute leukemia from microscopic images of peripheral blood smear //Computers in Biology and Medicine. – 2022. – Т. 142. – С. 105236.
Akhmedova Fatima Bakhtiyarovna, basic doctoral student RSSPMCH,
number: +99899 741 98 88.
Matkarimova Dilfuza Saburova, Professor of the Department of Hematology, Transfusiology and Laboratory Science of TMA.
number: +99897 412 91 18.
Boboev Kodirjon Tukhtabaevich, Head of the Department of Molecular Medicine and Cellular Technologies of the RSSPMCH,
number: +99890 319 39 57.
