International Journal of HIV/AIDS Prevention, Education and Behavioural Science

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Predictors of Change in CD4 Count among Adult HIV/AIDS Patients on Anti-Retroviral Treatment in West Hararghe Zone, Ethiopia; Retrospective Longitudinal Study

Received: Jun. 03, 2020    Accepted: Jun. 17, 2020    Published: Jul. 04, 2020
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Abstract

Background: As one of the countries in the Sub-Saharan African Region, Ethiopia also happens to bear a higher burden of HIV infection. For HIV-infected patients, the level of CD4 count remains an important test with regard to diagnostic decision-making. There is limited information on predictors of longitudinal change in CD4 count over time that examine immunologic response of patients during the course of treatment in Ethiopia. Therefore, this study aimed to examine predictors of change in CD4 count among adult HIV infected patients on antiretroviral treatment in west Hararghe zone, Ethiopia. Methods: An institutional based retrospective cohort study was conducted among 405 adult HIV/AIDS patients on Anti-Retro Viral Therapy (ART) from September 2013 to January 2019. Data was entered into Epi info 7 and analyzed in R software. Generalized mixed effect model was applied to identify predictors of longitudinal change in CD4 count. Results: In multivariable analysis time since start of ART (beta=0.306, 95%CI, 0.286: 0.326), primary level educational status (beta=0.048, 95%CI, 0.004: 0.092), tertiary educational status (beta=0.094, 95%CI, 0.007: 0.182), WHO RVI stage II (beta=-0.108, 95%CI, -0.156:-0.061), bedridden functional status (beta=-0.175, 95%CI,-0.309:-0.039), poor baseline adherence (beta=-0.145, 95%CI, -0.214: -0.076) and baseline weight (beta=-0.004, 95%CI, -0.006, -0.002) were significant predictors of longitudinal CD4 change. Conclusion: In this study time since start of ART, primary and tertiary educational status contributed positively to the change in CD4 count whereas bedridden functional status, poor adherence, WHO RVI stage II and baseline weight are negatively associated with longitudinal change in CD4 count. Close monitoring for bedridden patients and patients with poor baseline adherence is needed especially during the initiation of ART for immunological response.

DOI 10.11648/j.ijhpebs.20200602.11
Published in International Journal of HIV/AIDS Prevention, Education and Behavioural Science ( Volume 6, Issue 2, December 2020 )
Page(s) 32-37
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This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

HIV/AIDS, CD4 Count, Generalized Linear Mixed Model, ART

References
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[2] Kharsany, A. B. and Q. A. J. T. o. A. j. Karim, HIV infection and AIDS in sub-Saharan Africa: current status, challenges and opportunities. 2016. 10: p. 34.
[3] UNAIDS, W. and W. J. L. G. U. Cameroon, WHO, Epidemiological Fact Sheet on HIV/AIDS and Sexually Transmitted Infections, 2002 update. 2002.
[4] Osler, M., et al., The continuing burden of advanced HIV disease over 10 years of increasing antiretroviral therapy coverage in South Africa. 2018. 66 (suppl_2): p. S118-S125.
[5] McCune, J. M. J. N., The dynamics of CD4+ T-cell depletion in HIV disease. 2001. 410 (6831): p. 974-979.
[6] Low-Beer, S., et al., Adherence to triple therapy and viral load response. 2000. 23 (4): p. 360-361.
[7] Thompson, M. A., et al., Guidelines for improving entry into and retention in care and antiretroviral adherence for persons with HIV: evidence-based recommendations from an International Association of Physicians in AIDS Care panel. 2012. 156 (11): p. 817-833.
[8] WHO, Guidelines on post-exposure prophylaxis for HIV and the use of co-trimoxazole prophylaxis for HIV-related infections among adults, adolescents and children: recommendations for a public health approach: December 2014 supplement to the 2013 consolidated guidelines on the use of antiretroviral drugs for treating and preventing HIV infection, in Guidelines on post-exposure prophylaxis for HIV and the use of co-trimoxazole prophylaxis for HIV-related infections among adults, adolescents and children: recommendations for a public health approach: December 2014 supplement to the 2013 consolidated guidelines on the use of antiretroviral drugs for treating and preventing HIV infection. 2014.
[9] IeDEA, T. J. J. o. a. i. d. s., Immunodeficiency at the start of combination antiretroviral therapy in low-, middle-and high-income countries. 2014. 65 (1): p. e8.
[10] Smith, C. J., et al., Factors influencing increases in CD4 cell counts of HIV-positive persons receiving long-term highly active antiretroviral therapy. 2004. 190 (10): p. 1860-1868.
[11] Seyoum, A., Z. J. A. r. Temesgen, and therapy, Joint longitudinal data analysis in detecting determinants of CD4 cell count change and adherence to highly active antiretroviral therapy at Felege Hiwot Teaching and Specialized Hospital, North-west Ethiopia (Amhara Region). 2017. 14 (1): p. 14.
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[15] Lord, G. M., et al., Leptin inhibits the anti-CD3-driven proliferation of peripheral blood T cells but enhances the production of proinflammatory cytokines. 2002. 72 (2): p. 330-338.
[16] Gezie, L. D. J. B. r. n., Predictors of CD4 count over time among HIV patients initiated ART in Felege Hiwot Referral Hospital, northwest Ethiopia: multilevel analysis. 2016. 9 (1): p. 377.
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    Adisu Birhanu Weldesenbet, Biruk Shalmeno Tusa, Sewnet Adem Kebede, Getachew Asfaw Dagne. (2020). Predictors of Change in CD4 Count among Adult HIV/AIDS Patients on Anti-Retroviral Treatment in West Hararghe Zone, Ethiopia; Retrospective Longitudinal Study. International Journal of HIV/AIDS Prevention, Education and Behavioural Science, 6(2), 32-37. https://doi.org/10.11648/j.ijhpebs.20200602.11

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    ACS Style

    Adisu Birhanu Weldesenbet; Biruk Shalmeno Tusa; Sewnet Adem Kebede; Getachew Asfaw Dagne. Predictors of Change in CD4 Count among Adult HIV/AIDS Patients on Anti-Retroviral Treatment in West Hararghe Zone, Ethiopia; Retrospective Longitudinal Study. Int. J. HIV/AIDS Prev. Educ. Behav. Sci. 2020, 6(2), 32-37. doi: 10.11648/j.ijhpebs.20200602.11

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    AMA Style

    Adisu Birhanu Weldesenbet, Biruk Shalmeno Tusa, Sewnet Adem Kebede, Getachew Asfaw Dagne. Predictors of Change in CD4 Count among Adult HIV/AIDS Patients on Anti-Retroviral Treatment in West Hararghe Zone, Ethiopia; Retrospective Longitudinal Study. Int J HIV/AIDS Prev Educ Behav Sci. 2020;6(2):32-37. doi: 10.11648/j.ijhpebs.20200602.11

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  • @article{10.11648/j.ijhpebs.20200602.11,
      author = {Adisu Birhanu Weldesenbet and Biruk Shalmeno Tusa and Sewnet Adem Kebede and Getachew Asfaw Dagne},
      title = {Predictors of Change in CD4 Count among Adult HIV/AIDS Patients on Anti-Retroviral Treatment in West Hararghe Zone, Ethiopia; Retrospective Longitudinal Study},
      journal = {International Journal of HIV/AIDS Prevention, Education and Behavioural Science},
      volume = {6},
      number = {2},
      pages = {32-37},
      doi = {10.11648/j.ijhpebs.20200602.11},
      url = {https://doi.org/10.11648/j.ijhpebs.20200602.11},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijhpebs.20200602.11},
      abstract = {Background: As one of the countries in the Sub-Saharan African Region, Ethiopia also happens to bear a higher burden of HIV infection. For HIV-infected patients, the level of CD4 count remains an important test with regard to diagnostic decision-making. There is limited information on predictors of longitudinal change in CD4 count over time that examine immunologic response of patients during the course of treatment in Ethiopia. Therefore, this study aimed to examine predictors of change in CD4 count among adult HIV infected patients on antiretroviral treatment in west Hararghe zone, Ethiopia. Methods: An institutional based retrospective cohort study was conducted among 405 adult HIV/AIDS patients on Anti-Retro Viral Therapy (ART) from September 2013 to January 2019. Data was entered into Epi info 7 and analyzed in R software. Generalized mixed effect model was applied to identify predictors of longitudinal change in CD4 count. Results: In multivariable analysis time since start of ART (beta=0.306, 95%CI, 0.286: 0.326), primary level educational status (beta=0.048, 95%CI, 0.004: 0.092), tertiary educational status (beta=0.094, 95%CI, 0.007: 0.182), WHO RVI stage II (beta=-0.108, 95%CI, -0.156:-0.061), bedridden functional status (beta=-0.175, 95%CI,-0.309:-0.039), poor baseline adherence (beta=-0.145, 95%CI, -0.214: -0.076) and baseline weight (beta=-0.004, 95%CI, -0.006, -0.002) were significant predictors of longitudinal CD4 change. Conclusion: In this study time since start of ART, primary and tertiary educational status contributed positively to the change in CD4 count whereas bedridden functional status, poor adherence, WHO RVI stage II and baseline weight are negatively associated with longitudinal change in CD4 count. Close monitoring for bedridden patients and patients with poor baseline adherence is needed especially during the initiation of ART for immunological response.},
     year = {2020}
    }
    

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  • TY  - JOUR
    T1  - Predictors of Change in CD4 Count among Adult HIV/AIDS Patients on Anti-Retroviral Treatment in West Hararghe Zone, Ethiopia; Retrospective Longitudinal Study
    AU  - Adisu Birhanu Weldesenbet
    AU  - Biruk Shalmeno Tusa
    AU  - Sewnet Adem Kebede
    AU  - Getachew Asfaw Dagne
    Y1  - 2020/07/04
    PY  - 2020
    N1  - https://doi.org/10.11648/j.ijhpebs.20200602.11
    DO  - 10.11648/j.ijhpebs.20200602.11
    T2  - International Journal of HIV/AIDS Prevention, Education and Behavioural Science
    JF  - International Journal of HIV/AIDS Prevention, Education and Behavioural Science
    JO  - International Journal of HIV/AIDS Prevention, Education and Behavioural Science
    SP  - 32
    EP  - 37
    PB  - Science Publishing Group
    SN  - 2575-5765
    UR  - https://doi.org/10.11648/j.ijhpebs.20200602.11
    AB  - Background: As one of the countries in the Sub-Saharan African Region, Ethiopia also happens to bear a higher burden of HIV infection. For HIV-infected patients, the level of CD4 count remains an important test with regard to diagnostic decision-making. There is limited information on predictors of longitudinal change in CD4 count over time that examine immunologic response of patients during the course of treatment in Ethiopia. Therefore, this study aimed to examine predictors of change in CD4 count among adult HIV infected patients on antiretroviral treatment in west Hararghe zone, Ethiopia. Methods: An institutional based retrospective cohort study was conducted among 405 adult HIV/AIDS patients on Anti-Retro Viral Therapy (ART) from September 2013 to January 2019. Data was entered into Epi info 7 and analyzed in R software. Generalized mixed effect model was applied to identify predictors of longitudinal change in CD4 count. Results: In multivariable analysis time since start of ART (beta=0.306, 95%CI, 0.286: 0.326), primary level educational status (beta=0.048, 95%CI, 0.004: 0.092), tertiary educational status (beta=0.094, 95%CI, 0.007: 0.182), WHO RVI stage II (beta=-0.108, 95%CI, -0.156:-0.061), bedridden functional status (beta=-0.175, 95%CI,-0.309:-0.039), poor baseline adherence (beta=-0.145, 95%CI, -0.214: -0.076) and baseline weight (beta=-0.004, 95%CI, -0.006, -0.002) were significant predictors of longitudinal CD4 change. Conclusion: In this study time since start of ART, primary and tertiary educational status contributed positively to the change in CD4 count whereas bedridden functional status, poor adherence, WHO RVI stage II and baseline weight are negatively associated with longitudinal change in CD4 count. Close monitoring for bedridden patients and patients with poor baseline adherence is needed especially during the initiation of ART for immunological response.
    VL  - 6
    IS  - 2
    ER  - 

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Author Information
  • Department of Epidemiology and Biostatistics, Collage of Health and Medical Sciences, Haramaya University, Haramaya, Ethiopia

  • Department of Epidemiology and Biostatistics, Collage of Health and Medical Sciences, Haramaya University, Haramaya, Ethiopia

  • Department of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia

  • College of Public Health, University of South Florida, Tampa, United State of America

  • Section