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Temporal prediction of the behavior between the number of leukocytes and CD4 + T lymphocytes in HIV positive patients with antiretroviral therapy

Temporal prediction of the behavior between the number of leukocytes and CD4 + T lymphocytes in HIV positive patients with antiretroviral therapy





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Artículos de Investigación

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Rodriguez, J., Pérez, C. ., Pardo, J. ., Barrios, F. ., & González, M. A. . (2023). Temporal prediction of the behavior between the number of leukocytes and CD4 + T lymphocytes in HIV positive patients with antiretroviral therapy. Archivos De Medicina (Manizales), 23(1). https://doi.org/10.30554/archmed.23.1.4157.2023
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Rodriguez, J., Pérez, C. ., Pardo, J. ., Barrios, F. ., & González, M. A. . (2023). Temporal prediction of the behavior between the number of leukocytes and CD4 + T lymphocytes in HIV positive patients with antiretroviral therapy. Archivos De Medicina (Manizales), 23(1). https://doi.org/10.30554/archmed.23.1.4157.2023

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Javier Rodriguez
Calos Pérez
Juan Pardo
Freddy Barrios
María Alejandra González

Javier Rodriguez,

MD, Director of the Insight Group. Colombian Neurosurgery Association. Mederi University Hospital. Bogotá Colombia.";}


Calos Pérez,

Spec. in Infectious disease. Services and advice in Infectology. Marly's Clinic. Bogotá Colombia.


Juan Pardo,

Scientific Director. Mederi University Hospital. Bogotá Colombia.


Freddy Barrios,

MD. Research group in Epidemiology and Biostatistics. CES University. Medellin Colombia.


María Alejandra González,

Researcher Odontoposgrados Group. Faculty of Dentistry. Cooperative University of Colombia. Headquarters Bogotá


Introduction: The elevated cost of flow cytometry for the following up of CD+ T lymphocyte counts has justified the search for predictive methodologies of this values that contribute to simplify and reduce costs of the therapeutic management of patients with HIV/AIDS. Objective: to establish the possible predictive mathematical correspondences between the CD4 + count> 500 cells/μL3 from the amount of leukocytes/μL3. Methodology: A mathematical induction was carried out with eight samples in time to establish a predictive pattern between the leukocyte count in a count of CD4+ > 500 cells/μL3. The validation of the predictive pattern was confirmed in 62 samples that had CD4+ counts previously masked. Then, the probability of success of the pattern was established as well as sensitivity and specificity. Results: the mathematical pattern of the eight samples revealed that, for a CD4 + count> 500 cells/μL3, a value greater than 3.7 leukocytes/μL3 is presented, with a value of one when calculating the probability and, of 100% when calculating the sensitivity and specificity. Conclusions: the present study revealed a deterministic mathematical order from which it is possible to establish direct correspondences between leukocyte count leukocytes/μL3 greater than 3.7 and CD4 + greater than 500 cells/μL3 in the context of probability theory.


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  1. Abbas A. Lichtman A. Inmunología Celular y Molecular. 4 Edición. Madrid: McGraw Hill; 2002. p. 478
  2. Castilla J, Sobrino P, Lorenzo JM, et al. Situación Actual y Perspectivas Futuras de La Epidemia de VIH y Sida En España. Vol 29. Gobierno de Navarra, Departamento de Salud; 2006.
  3. Wu E, Galaz MI, Larrañaga C, et al. Infección por VIH/SIDA en niños y adolescentes: cohorte chilena 1987-2014. Rev Chil infectología. 2016;33(Suppl 1):11-19.
  4. Morales-Miranda S, Loya-Montiel I, Ritter J, et al. Factors associated with HIV testing among men who have sex with men in Guatemala City. Int J STD AIDS. 2019;30(6):577-585.
  5. Zijenah LS, Katzenstein DA, Nathoo KJ, et al. T lymphocytes among HIV-infected and -uninfected infants: CD4/CD8 ratio as a potential tool in diagnosis of infection in infants under the age of 2 years. J Transl Med. 2005;3(1):6.
  6. WHO, UNAIDS. Joint United Nations Programme on HIV/ AIDS. Progress on global access to antiretroviral therapy: an update on “3 by 5”. Vol. 2005
  7. WHO, UNAIDS. Joint United Nations Programme on HIV/ AIDS. Epidemic update 2005.
  8. Gnedenko B, Khintchine, A. Introducción a la teoría de las probabilidades. Barcelona: Montaner y Simon. 1968
  9. Rodríguez J, Prieto S, Bernal P, et al. Predicción de la concentración de linfocitos T CD4 en sangre periférica con base en la teoría de la probabilidad. Aplicación clínica en poblaciones de leucocitos, linfocitos y CD4 de pacientes con VIH. Infectio. 2012;16(1):15-22.
  10. Ministerio de Salud. Resolución Número 8430 de 1993. Bogotá, Colombia [Internet]. 1993 (consultado el 26/05/2019). Disponible en: https://www.minsalud.gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/DE/DIJ/RESOLUCION-8430-DE-1993.PDF
  11. Asociación Médica Mundial. Declaración de Helsinki. Fortaleza, Brasil [Internet]. 2013 (consultado el 26/05/2019). Disponible en: http://www.isciii.es/ISCIII/es/contenidos/fd-investigacion/fd-evaluacion/fd-evaluacion-etica-investigacion/Declaracion-Helsinki-2013-Esp.pdf.
  12. Rodríguez J, Prieto S, Correa C, Mora J, Bravo J, Soracipa Y, et al. Predictions of CD4 lymphocytes’ count in HIV patients from complete blood count. BMC Medical Physics. BMC Medical Physics. 2013; 13:3.
  13. Rodríguez J, Prieto S, Correa C, Forero M, Pérez C, Soracipa Y, et al. Teoría de conjuntos aplicada al recuento de linfocitos y leucocitos: predicción de linfocitos T CD4 de pacientes con virus de la inmunodeficiencia humana/sida. Inmunología. 2013; 32(2): 50-56.
  14. Means AR, Risher KA, Ujeneza EL, Maposa I, Nondi J, Bellan SE. Impact of Age and Sex on CD4+ Cell Count Trajectories following Treatment Initiation: An Analysis of the Tanzanian HIV Treatment Database [published correction appears in PLoS One. 2017 Jan 6;12 (1):e0170155]. PLoS One. 2016;11(10):e0164148. Published 2016 Oct 7. doi:10.1371/journal.pone.0164148.
  15. Obirikorang C, Quaye L, Acheampong I. Total lymphocyte count as a surrogate marker for CD4 count in resource-limited settings. BMC Infect Dis. 2012;12:128. Published 2012 Jun 7. doi:10.1186/1471-2334-12-128.
  16. Shapiro NI, Karras DJ, Leech SH, et al. Absolute lymphocyte count as a predictor of CD4 count. Ann Emerg Med. 1998 Sep;32(3 Pt 1):323-8.
  17. Chen J, Li W, Huang X, et al. Evaluating total lymphocyte count as a surrogate marker for CD4 cell count in the management of HIV-infected patients in resource-limited settings: a study from China. PLoS One. 2013;8(7):e69704. Published 2013 Jul 18. doi:10.1371/journal.pone.0069704
  18. Lok JJ, Bosch RJ, Benson CA, et al. Long-term increase in CD4+ T-cell counts during combination antiretroviral therapy for HIV-1 infection. AIDS. 2010;24(12):1867–1876.
  19. Kidd PG, Cheng SC, Paxton H, et al. Prediction of CD4 count from CD4 percentage: experience from three laboratories. AIDS. 1993 Jul;7(7):933-40.
  20. Sauter R, Huang R, Ledergerber B, et al. CD4/CD8 ratio and CD8 counts predict CD4 response in HIV-1-infected drug naive and in patients on cART. Medicine (Baltimore);95(42):e5094.
  21. Hughes RA, May MT, Taylor N, et al. Long terms trends in CD4+ cell counts, CD8+ cell counts, and the CD4+ : CD8+ ratio. AIDS 2018; 32: 1361-1367.
  22. Rodríguez J. Dynamical systems applied to dynamic variables of patients from the Intensive Care Unit (ICU). Physical and mathematical Mortality predictions on ICU. J. Med. Med. Sci. 2015; 6(8): 102-108.
  23. Rodríguez J, Prieto S, Ramírez L. A novel heart rate atractor for the prediction of cardiovascular disease. Informatics in medicine. 2019; 15(100174):1-9.
  24. Javier R, Prieto S, Correa C, Pérez C, Soracipa M. Dinámica de la epidemia de malaria en Colombia: predicción probabilística temporal. Rev. Salud pública. 2017;91(1):52-59.
  25. Rodríguez J, Bernal P, Prieto P, Correa C, Álvarez L, Pinilla L, et al. Predicción de unión de péptidos de Plasmodium falciparum al HLA clase II. Probabilidad, combinatoria y entropía aplicadas a las proteínas MSP-5 y MSP-6. Archivos de alergia e inmunología clínica. 2013; 44(1): 7-14.
  26. Rodríguez J, Prieto S, Correa C, Dominguez D, Cardona DM, Melo M. Geometrical nuclear diagnosis and total paths of cervix cell evolution from normality to cancer. J Can Res Ther 2015; 11(1): 98-104.