Longitudinal Analysis of CD4 Cell Counts Data on HIV Patients Initiated on Anti-retroviral Therapy: Case of Ayder Comprehensive Specialized Hospital, Tigray, Ethiopia

Naod Gebrekrstos Zeru

doi:doi:10.11648/j.bio.20221006.12

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Longitudinal Analysis of CD4 Cell Counts Data on HIV Patients Initiated on Anti-retroviral Therapy: Case of Ayder Comprehensive Specialized Hospital, Tigray, Ethiopia

Naod Gebrekrstos Zeru

Published in American Journal of Bioscience and Bioengineering (Volume 10, Issue 6)

Received: 27 May 2021 Accepted: 11 September 2021 Published: 31 January 2023

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Abstract

Human immune virus (HIV) attacks an immune cell called cluster of differentiation 4 (CD4) cells which are responsible for the body’s immune response to infectious agents. Even if, HIV is treated through ART, the occurrence of event is still continued. The objective of this study was identifying risk factors of the change in CD4 cell counts on HIV positive patients initiated on Anti-Retroval Therapy (ART). The study population of this study were consists of 632 HIV+ patients who were under ART follow up from September 2016 - August 2019 in Ayder Comprehensive Specialized Hospital, Ethiopia. Retrospective Longitudinal study was used with minimum three and maximum six times follow up time per individual. The CD4 cell count data were explored using basic descriptive statistics and also a profile of the mean CD4 cell count over the period of the study. Generalized Linear Mixed Model (GLMM) and Generalized Estimation Equation (GEE) models were used to modeling the change in CD4 cell counts over the time. The mean of CD4 cell count revealed that there is an improvement with duration of treatment in linear trend. From the Generalized Linear Mixed Model covariates time, sex, age, weight, hemoglobin level, functional status, regimen class, WHO stage, TB status, time by WHO stage and time by weight significantly determined a change in the CD4 cell count over time. Generalized Linear Mixed Model was the better fitted model compared to GEE as proven by the minimum standard error. Moreover, CD4 count increases in a linear trend over time after patients initiated to the ART program i.e. the immune system increases whereas the progression of the disease turn down due to the therapy. Therefore, patients should start ART treatment early to increase their CD4 cell count.

Published in	American Journal of Bioscience and Bioengineering (Volume 10, Issue 6)
DOI	10.11648/j.bio.20221006.12
Page(s)	114-121
Creative Commons	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), 2023. Published by Science Publishing Group

Keywords

ART, CD4 Cell Count, GEE, GLMM, Longitudinal Data Analysis

References

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[15]	Lemma D., (2016). Predictors of CD4 count over time among HIV patients initiated ART in Felege Hiwot Referral Hospital, northwest Ethiopia multilevel analysis, Stat Med; 43.
[16]	Belay D., (2017). Application of Longitudinal Count Data Models to Progression of CD4 Count: A Case of DebreMarkos Referral Hospital.
[17]	Birhan, T. Y., Gezie, L. D., Teshome, D. F., & Sisay, M. M. (2020). Predictors of CD4 count changes over time among children who initiated highly active antiretroviral therapy in Ethiopia. Tropical Medicine and Health, 48, 1-8.

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APA Style

Naod Gebrekrstos Zeru. (2023). Longitudinal Analysis of CD4 Cell Counts Data on HIV Patients Initiated on Anti-retroviral Therapy: Case of Ayder Comprehensive Specialized Hospital, Tigray, Ethiopia. American Journal of Bioscience and Bioengineering, 10(6), 114-121. https://doi.org/10.11648/j.bio.20221006.12

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ACS Style

Naod Gebrekrstos Zeru. Longitudinal Analysis of CD4 Cell Counts Data on HIV Patients Initiated on Anti-retroviral Therapy: Case of Ayder Comprehensive Specialized Hospital, Tigray, Ethiopia. Am. J. BioSci. Bioeng. 2023, 10(6), 114-121. doi: 10.11648/j.bio.20221006.12

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AMA Style

Naod Gebrekrstos Zeru. Longitudinal Analysis of CD4 Cell Counts Data on HIV Patients Initiated on Anti-retroviral Therapy: Case of Ayder Comprehensive Specialized Hospital, Tigray, Ethiopia. Am J BioSci Bioeng. 2023;10(6):114-121. doi: 10.11648/j.bio.20221006.12

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@article{10.11648/j.bio.20221006.12,
  author = {Naod Gebrekrstos Zeru},
  title = {Longitudinal Analysis of CD4 Cell Counts Data on HIV Patients Initiated on Anti-retroviral Therapy: Case of Ayder Comprehensive Specialized Hospital, Tigray, Ethiopia},
  journal = {American Journal of Bioscience and Bioengineering},
  volume = {10},
  number = {6},
  pages = {114-121},
  doi = {10.11648/j.bio.20221006.12},
  url = {https://doi.org/10.11648/j.bio.20221006.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.bio.20221006.12},
  abstract = {Human immune virus (HIV) attacks an immune cell called cluster of differentiation 4 (CD4) cells which are responsible for the body’s immune response to infectious agents. Even if, HIV is treated through ART, the occurrence of event is still continued. The objective of this study was identifying risk factors of the change in CD4 cell counts on HIV positive patients initiated on Anti-Retroval Therapy (ART). The study population of this study were consists of 632 HIV+ patients who were under ART follow up from September 2016 - August 2019 in Ayder Comprehensive Specialized Hospital, Ethiopia. Retrospective Longitudinal study was used with minimum three and maximum six times follow up time per individual. The CD4 cell count data were explored using basic descriptive statistics and also a profile of the mean CD4 cell count over the period of the study. Generalized Linear Mixed Model (GLMM) and Generalized Estimation Equation (GEE) models were used to modeling the change in CD4 cell counts over the time. The mean of CD4 cell count revealed that there is an improvement with duration of treatment in linear trend. From the Generalized Linear Mixed Model covariates time, sex, age, weight, hemoglobin level, functional status, regimen class, WHO stage, TB status, time by WHO stage and time by weight significantly determined a change in the CD4 cell count over time. Generalized Linear Mixed Model was the better fitted model compared to GEE as proven by the minimum standard error. Moreover, CD4 count increases in a linear trend over time after patients initiated to the ART program i.e. the immune system increases whereas the progression of the disease turn down due to the therapy. Therefore, patients should start ART treatment early to increase their CD4 cell count.},
 year = {2023}
}

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TY - JOUR
T1 - Longitudinal Analysis of CD4 Cell Counts Data on HIV Patients Initiated on Anti-retroviral Therapy: Case of Ayder Comprehensive Specialized Hospital, Tigray, Ethiopia
AU - Naod Gebrekrstos Zeru
Y1 - 2023/01/31
PY - 2023
N1 - https://doi.org/10.11648/j.bio.20221006.12
DO - 10.11648/j.bio.20221006.12
T2 - American Journal of Bioscience and Bioengineering
JF - American Journal of Bioscience and Bioengineering
JO - American Journal of Bioscience and Bioengineering
SP - 114
EP - 121
PB - Science Publishing Group
SN - 2328-5893
UR - https://doi.org/10.11648/j.bio.20221006.12
AB - Human immune virus (HIV) attacks an immune cell called cluster of differentiation 4 (CD4) cells which are responsible for the body’s immune response to infectious agents. Even if, HIV is treated through ART, the occurrence of event is still continued. The objective of this study was identifying risk factors of the change in CD4 cell counts on HIV positive patients initiated on Anti-Retroval Therapy (ART). The study population of this study were consists of 632 HIV+ patients who were under ART follow up from September 2016 - August 2019 in Ayder Comprehensive Specialized Hospital, Ethiopia. Retrospective Longitudinal study was used with minimum three and maximum six times follow up time per individual. The CD4 cell count data were explored using basic descriptive statistics and also a profile of the mean CD4 cell count over the period of the study. Generalized Linear Mixed Model (GLMM) and Generalized Estimation Equation (GEE) models were used to modeling the change in CD4 cell counts over the time. The mean of CD4 cell count revealed that there is an improvement with duration of treatment in linear trend. From the Generalized Linear Mixed Model covariates time, sex, age, weight, hemoglobin level, functional status, regimen class, WHO stage, TB status, time by WHO stage and time by weight significantly determined a change in the CD4 cell count over time. Generalized Linear Mixed Model was the better fitted model compared to GEE as proven by the minimum standard error. Moreover, CD4 count increases in a linear trend over time after patients initiated to the ART program i.e. the immune system increases whereas the progression of the disease turn down due to the therapy. Therefore, patients should start ART treatment early to increase their CD4 cell count.
VL - 10
IS - 6
ER -

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Naod Gebrekrstos Zeru

Department of Statistics, College of Natural and Computational Science, Mekelle University, Mekelle, Ethiopia

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APA Style

Naod Gebrekrstos Zeru. (2023). Longitudinal Analysis of CD4 Cell Counts Data on HIV Patients Initiated on Anti-retroviral Therapy: Case of Ayder Comprehensive Specialized Hospital, Tigray, Ethiopia. American Journal of Bioscience and Bioengineering, 10(6), 114-121. https://doi.org/10.11648/j.bio.20221006.12

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ACS Style

Naod Gebrekrstos Zeru. Longitudinal Analysis of CD4 Cell Counts Data on HIV Patients Initiated on Anti-retroviral Therapy: Case of Ayder Comprehensive Specialized Hospital, Tigray, Ethiopia. Am. J. BioSci. Bioeng. 2023, 10(6), 114-121. doi: 10.11648/j.bio.20221006.12

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AMA Style

Naod Gebrekrstos Zeru. Longitudinal Analysis of CD4 Cell Counts Data on HIV Patients Initiated on Anti-retroviral Therapy: Case of Ayder Comprehensive Specialized Hospital, Tigray, Ethiopia. Am J BioSci Bioeng. 2023;10(6):114-121. doi: 10.11648/j.bio.20221006.12

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@article{10.11648/j.bio.20221006.12,
  author = {Naod Gebrekrstos Zeru},
  title = {Longitudinal Analysis of CD4 Cell Counts Data on HIV Patients Initiated on Anti-retroviral Therapy: Case of Ayder Comprehensive Specialized Hospital, Tigray, Ethiopia},
  journal = {American Journal of Bioscience and Bioengineering},
  volume = {10},
  number = {6},
  pages = {114-121},
  doi = {10.11648/j.bio.20221006.12},
  url = {https://doi.org/10.11648/j.bio.20221006.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.bio.20221006.12},
  abstract = {Human immune virus (HIV) attacks an immune cell called cluster of differentiation 4 (CD4) cells which are responsible for the body’s immune response to infectious agents. Even if, HIV is treated through ART, the occurrence of event is still continued. The objective of this study was identifying risk factors of the change in CD4 cell counts on HIV positive patients initiated on Anti-Retroval Therapy (ART). The study population of this study were consists of 632 HIV+ patients who were under ART follow up from September 2016 - August 2019 in Ayder Comprehensive Specialized Hospital, Ethiopia. Retrospective Longitudinal study was used with minimum three and maximum six times follow up time per individual. The CD4 cell count data were explored using basic descriptive statistics and also a profile of the mean CD4 cell count over the period of the study. Generalized Linear Mixed Model (GLMM) and Generalized Estimation Equation (GEE) models were used to modeling the change in CD4 cell counts over the time. The mean of CD4 cell count revealed that there is an improvement with duration of treatment in linear trend. From the Generalized Linear Mixed Model covariates time, sex, age, weight, hemoglobin level, functional status, regimen class, WHO stage, TB status, time by WHO stage and time by weight significantly determined a change in the CD4 cell count over time. Generalized Linear Mixed Model was the better fitted model compared to GEE as proven by the minimum standard error. Moreover, CD4 count increases in a linear trend over time after patients initiated to the ART program i.e. the immune system increases whereas the progression of the disease turn down due to the therapy. Therefore, patients should start ART treatment early to increase their CD4 cell count.},
 year = {2023}
}

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