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Prediction of CD4+ ranges based on the total number of leukocytes in people living with HIV

https://doi.org/10.22328/2077-9828-2022-14-4-67-72

Abstract

Objective. To predict the amount of CD4+/μL3 in sequences of patient records with CD4 T lymphocyte values above 500 cells/μL3 and / or between 200 to 500 cells/μL3 from the absolute leukocyte count in the context of the theory of probability.

Materials and methods. Two mathematical inductions were performed to find predictive mathematical relationships for CD4+/μL3 when they are above 500 cells/μL3 and between 200 to 500 cells/μL3, from the absolute count of leukocytes. Subsequently, the probability of success of the predictions was calculated, two blind studies were performed on 80 remaining data, and sensitivity and specificity were calculated for both cases.

Results and discussion. If there are more than three records in time per patient, and these are above 500 CD4/μL3 cells or between 200 to 500 CD4/μL3 cells, finding that the absolute leukocyte count has a greater or equal value to three and lower to 4 for all the records, the following record will be maintained with a measurement of CD4 lymphocytes>500 or between [200, 500], if in the absolute count of leukocytes of the patient sequences a value of four is observed and CD4+ ranges from 200 to 500 cells/μL3, it can be deduced that there will be at least one measurement of CD4 +>500 cells/μL3 associated with a leukocyte measurement / μL3 greater than 3.7.

Conclusions. We established two temporal mathematical patterns capable of predicting the CD4+/μL3 count from the absolute leukocyte count.

About the Authors

J. O. Rodríguez Velásquez
Hospital Universitario Nacional de Colombia
Colombia

Javier Oswaldo Rodríguez Velásquez — Medical-Researcher

Cl. 44 #59–75 Bogotá



E. Prieto
Hospital Universitario Nacional de Colombia
Colombia

Esperanza Prieto — Physical-Researcher

Cl. 44 #59–75 Bogotá



C. E. Pérez Díaz
Servicios y Asesorías en Infectología
Colombia

Carlos Eduardo Pérez Díaz — Medical and Infectologist

Cl. 50 #13–62 Bogotá



C. A. Valdés Cadena
Hospital Universitario Nacional de Colombia
Colombia

César Alejandro Valdés Cadena — Medical-Researcher

Cl. 44 #59–75 Bogotá



G. F. Bulla
Asociación Colombiana de Neurocirugía
Colombia

Germán Forero Bulla — Medical and neurosurgeon

Carrera 16 # 9–46 Oficina 201 Bogotá



F. A. Barrios Arroyave
Grupo de investigación en Epidemiología y Bioestadística. Universidad CES
Colombia

Freddy Andrés Barrios Arroyave — Medical

Cl 10A #22–04 Medellín



N. López
Universidad de los Andes
Colombia

Nathalia López — Physics student

Cra. 1 #18a-12 Bogotá



F. López
Hospital Universitario Nacional de Colombia
Colombia

Freddy López — Systems engineer

Cl. 44 #59–75 Bogotá



References

1. UNAIDS. Global HIV & AIDS statistics — 2018 fact sheet. 2018 (consultado el 26/05/2019). Available at: https://www.unaids.org/en/resources/fact-sheet.

2. Morales-Miranda S., Loya-Montiel I., Ritter J., Rocha-Jiménez T., Gordon L., García J., et al. Factors associated with HIV testing among men who have sex with men in Guatemala City // Int. J. STD AIDS. 2019. Vol. 30, No. 6. Р. 577–585. doi: 10.1177/0956462419826393.

3. Castilla J., Sobrino P., Lorenzo J.M., Moreno C., Izquierdo A., Lezaun ME. et al. Situación Actual y Perspectivas Futuras de La Epidemia de VIH y Sida En España // Annales Sis San Navarra. 2006. Vol. 29. Р. 13–25. https://scielo.isciii.es/pdf/asisna/v29n1/colaboracion.pdf

4. Wu E., Galaz MI., Larrañaga C., Chávez A., González M., Álvarez AM et al. Infección por VIH/SIDA en niños y adolescentes: cohorte chilena 1987–2014 // Rev. Chil. infectología. 2016. Vol. 33. Р. 11–19. https://scielo.conicyt.cl/pdf/rci/v33s1/art02.pdf.

5. Luz P.M., Grinsztejn B., Velasque L., Pacheco A.G., Veloso V.G., Moore R.D. et al. Long-Term CD4+ Cell Count in Response to Combination Antiretroviral Therapy // PloS Оne. 2014. Vol. 9, No. 4. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0093039.

6. Lok J.J., Bosch R.J., Benson C.A., Collier A.C., Robbins G.K., Shafer R.W. et al. Long-term increase in CD4+ T-cell counts during combination antiretroviral therapy for HIV-1 infection // AIDS. 2010. Vol. 24, No. 12. Р. 1867–1876. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3018341/

7. Wright S.T., Petoumenos K., Boyd M., Carr A., Downing S., O’Connor C.C. et al. Ageing and long-term CD4 cell count trends in HIV-positive patients with 5 years or more combination antiretroviral therapy experience // HIV Medicine. 2013. Vol. 14, No. 4. Р. 208–216. https://pubmed.ncbi.nlm.nih.gov/23036045/

8. Hoffmann C.J., Schomaker M., Fox MP., Mutevedzi P., Giddy J., Prozesky H. et al. CD4 count slope and mortality in HIV-infected patients on antiretroviral therapy: multicohort analysis from South Africa // J. Acquir. Immune Defic. Syndr. 2013. Vol. 63, No. 1. Р. 34–41. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3655761/

9. Kye K., Jongyoun Y., Sun L. The CD4 slope can be a predictor of immunologic recovery in advanced HIV patients: a case-control study // Korean J. Intern. Med. 2015. Vol. 30, No. 5. Р. 705–713. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4578040/

10. Chu H., Gange S.J., Yamashita T.E., Hoover D.R., Chmiel J.S., Margolick J.B. et al. Individual Variation in CD4 Cell Count Trajectory among Human Immunodeficiency Virus-infected Men and Women on Long-term Highly Active Antiretroviral Therapy: An Application using a Bayesian Random Change-Point Model // Amer. J. Epidemiol. 2005. Vol. 162, No 8. Р. 787–797. https://academic.oup.com/aje/article/162/8/787/122315

11. De Beaudrap P., Etard J.F., Diouf A., Ndiaye I., Gueye N.F., Gueye P.M. et al. Modeling CD4+ cell count increase over a six-year period in HIV-1-infected patients on highly active antiretroviral therapy in Senegal // The American journal of tropical medicine and hygiene. 2009. Vol. 80, No. 6. Р. 1047–1053. https://pubmed.ncbi.nlm.nih.gov/19478274/

12. Gnedenko B., Khintchine A. Introducción a la teoría de las probabilidades. Barcelona: Montaner y Simon. 1968. http://urss.ru/cgi-bin/db.pl?lang=Ru&blang=en&page=Book&id=248857

13. Rodríguez J., Prieto S., Bernal P., Pérez C., Correa C., Vitery S. Teoría de conjuntos aplicada a poblaciones de leucocitos., linfocitos y CD4 de pacientes con VIH. Predicción de linfocitos T CD4, de aplicación clínica // Rev. Fac. Med. 2011. Vol. 19, No. 2. Р. 148–156. https://revistas.unimilitar.edu.co/index.php/rmed/article/view/1276

14. Rodríguez J., Prieto S., Bernal P., Pérez C., Correa C., Álvarez L. 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. Vol. 16, No. 1. Р. 15–22. https://www.elsevier.es/es-revista-infectio-351-articulo-prediccion-concentracion-linfocitos-t-cd4-S012393921270053X.

15. 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. Vol. 32, No. 2. Р. 50–56. https://medes.com/publication/80939

16. 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. 2013, No. 13. Р. 3. https://bmcmedphys.biomedcentral.com/articles/10.1186/1756-6649-13-3.

17. Rodriguez J., Prieto S., Correa C., Melo M., Dominguez D., Olarte N. et al. Prediction refinement of CD4 cells number based on sets and probability theory // Current HIV Research. 2018. Vol. 16. Р. 416–424. https://www.eurekaselect.com/170478/article.

18. Rodríguez J., Prieto S., Melo M., Domínguez D., Correa C., Soracipa Y. et al. Predicción del número de linfocitos T CD4 en sangre periférica a partir de teoría de conjuntos y probabilidad en pacientes con VIH/SIDA. Inmunologia. 2014, No. 33. Р. 113–120. https://www.elsevier.es/esrevista-inmunologia-322-articulo-prediccion-del-numero-linfocitos-t-S021396261400064X.

19. Rodríguez J., Prieto S., Flórez M., Alarcón C., López R., Aguirre G. et al. Physical-mathematical diagnosis of cardiac dynamic on neonatal sepsis: predictions of clinical application // J. Med. Med. Sci. 2014. Vol. 5, No. 5. Р. 102–108. https://www.interesjournals.org/abstract/physicalmathematical-diagnosis-of-cardiac-dynamic-on-neonatal-sepsis-predictions-of-clinical-application-17079.html.

20. 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. Vol. 6, No. 8. Р. 102–108. https://www.interesjournals.org/articles/dynamical-systems-appliedto-dynamic-variables-of-patients-from-the-intensive-care-unit-icu-physical-and-mathematical-mo.pdf

21. Rodríguez-Velásquez J.O., Prieto-Bohórquez S.E., Correa-Herrera S.C., Pérez-Díaz C.E., Soracipa-Muñoz M.Y. Dinámica de la epidemia de malaria en Colombia: Predicción probabilística temporal // Rev. Salud. Pública. 2017. Vol. 19, No. 1. Р. 52–59. https://revistas.unal.edu.co/index.php/revsaludpublica/article/view/48203/61211.

22. Rodríguez J., Oliveros D., Soracipa Y., Bernal L., Correa C., Abrahem L. et al. Análisis probabilista con caminata al azar del número de personas viviendo con VIH mundialmente // Rev. Fac. Nac. Salud Pública. 2018. Vol. 36, No. 1. Р. 27–33. http://www.scielo.org.co/pdf/rfnsp/v36n1/0120-386X-rfnsp-36-01-00027.pdf.


Review

For citations:


Rodríguez Velásquez J.O., Prieto E., Pérez Díaz C.E., Valdés Cadena C.A., Bulla G.F., Barrios Arroyave F.A., López N., López F. Prediction of CD4+ ranges based on the total number of leukocytes in people living with HIV. HIV Infection and Immunosuppressive Disorders. 2022;14(4):67-72. https://doi.org/10.22328/2077-9828-2022-14-4-67-72

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