Repeated Measure Analysis for the CD4<sup>+</sup> Cell Counts of HIV-Positive Patients Initiated to ART: A Case Study at Ambo Hospital

Endale Alemayehu; Tsigereda Tilahun

doi:doi:10.11648/j.ijdsa.20210702.12

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Repeated Measure Analysis for the CD4⁺ Cell Counts of HIV-Positive Patients Initiated to ART: A Case Study at Ambo Hospital

Endale Alemayehu, Tsigereda Tilahun

Published in International Journal of Data Science and Analysis (Volume 7, Issue 2)

Received: 8 February 2021 Accepted: 24 March 2021 Published: 20 April 2021

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Abstract

Introduction: HIV is a virus that causes Acquired Immunodeficiency Syndrome (AIDS) by reducing a person's ability to fight the infection. It attacks an immune cell called the CD4 cell which is responsible for the body's immune response to infectious agents. Now a days anti retro viral therapy treatment is avail to elongate the life of patients. The treatment is given for patients to increase the CD4 counts of patients to keep the ability of body preventing the disease. Objectives: This study was aimed to identify the potential associated risk factors with CD4 counts of patients under ART treatment at public hospital in Ethiopia. The other was to fit linear mixed model by handling missing value of the data during follow up time. Method: To see the structure of the data, exploratory data analysis was conducted. Of the familiar variance structures, unstructured variance covariance is selected to be best and to fit the data under study, step-by-step procedure was passed to obtain best model. Results: The descriptive statistics directed that the progressive change in CD4 counts of females seems better than that of males. On the other hand, the output of the fitted model indicated that covariates significant with 5% level of significance is that baseline CD4, time, weight and interaction of Sex, baseline CD4 with time. Allowing the significance level to increase to 25% increases most covariates to be significant that help patients in a better awareness. Conclusion: With this result, full linear mixed with random intercept and slop is found to best model. There was high variability within patients over time and between patients and the interaction of time with covariates was also significant. Generally, the data was fitted by handling the missing value using multiple imputation technique.

Published in	International Journal of Data Science and Analysis (Volume 7, Issue 2)
DOI	10.11648/j.ijdsa.20210702.12
Page(s)	32-38
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), 2024. Published by Science Publishing Group

Keywords

Longitudinal Data Analysis, CD4⁺, ART, Linear Mixed Model

References

[1]	Aboma Temesgen (2017) Application of Poisson Mixed Combined Models for Identifying Correlations of CD4 Count Progression in HIV Infected TB Patients during ART Treatment Period. International Journal of Statistics and Probability; Vol. 6, No. 5; September 2017 ISSN 1927-7032 E-ISSN 1927-7040.
[2]	Adams, M. and Luguterah, A. (2013). Longitudinal analysis of change in CD4⁺ cell counts of HIV-1 patients on antiretroviral therapy (ART) in the Builsa district hospital. European Scientific Journal, 9 (33), 1857-7881.
[3]	Addisu A, Dagim A, Tadele E, Adissu A, Mussie A, Filmon K. CD4 cell count trends after commencement of antiretroviral therapy among HIV infected patients in Tigray, northern Ethiopia: a retrospective cross-sectional study. PLoS ONE. 2015; 10 (3): e0122583. doi: 10.1371/journal.pone.
[4]	Awoke Seyoum, Principal Ndlovu and Zewotir Temesgen: 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). AIDS Research and Therapy DOI 10.1186/s12981-017-0141-3.
[5]	Burton, P., Gurrin, L., and Sly, P. (1998). Extending the Simple Linear Regression Model. Statistics in Medicine, 17, 1261-1291.
[6]	Diggle P. J., Heagetry P. J., Liang K. Y and Zeger S. L. (2002). Analysis of Longitudinal Data. (2nd Ed.). Oxford Science Publications. Oxford: Clarendon Press.
[7]	Fares Qeadan (2016). Longitudinal Data Analysis by Example. A seminar in biostatistics for the Mountain West Clinical Translational Research Infrastructure Network. University of New Mexico Health Sciences Center. Albuquerque, New Mexico.
[8]	Getachew Tekle, Wondwosen Kassahun and Abdisa Gurmessa Statistical Analysis of CD4⁺ Cell Counts progression of HIV-1-positive Patients enrolled in Antiretroviral Therapy at Hossana District Queen Elleni Mohamad Memorial Hospital, South Ethiopia. Biometrics & Biostatistics International Journal.
[9]	Harville, D. A. (1977). Maximum likelihood approaches to variance component estimation and to related problems. Journal of the American Statistical Association, 72 (320-340).
[10]	Jiang, J., Rao, J. S., Gu, Z., and Nguyen, T. (2008). Fence methods for mixed model selection. The Annals of Statistics 36, 1669-1692.
[11]	Kaufmann RG, Perrin L, Pantaleo G, Opravil M, Furrer H, Telenti A, et al. CD4 T-lymphocyte recovery in individuals with advanced HIV-1 infection receiving potent antiretroviral therapy for 4 years: the Swiss HIV cohort study. Arch Intern Med. 2003; 163 (18): 2187–95.
[12]	Laird, N. M., & Ware, J. H. (1982). Random-effects models for longitudinal data. Biometrics, 38, 963-974.
[13]	Singer, J. D. & Willett, J. B. (2003), Applied Longitudinal Data Analysis, Oxford University Press, Oxford, UK.
[14]	Ve, V. Moing, L., Thiébaut, T., Chêne, G., Leport, C., Cailleton, V. Michelet, C., Fleury, H., Herson, S., Raffi, F.-Reviewed work (2002). Predictors of Long-Term Increase in CD+ Cell Counts in Human Immunodeficiency Virus-Infected Patients Receiving a Protease Inhibitor Containing Antiretroviral Regimen. The Journal of Infectious Diseases, Vol. 185, No. 4, pp. 471-480.
[15]	Verbeke, G. and Molenberghs, G. (2000). Linear Mixed Models for Longitudinal Data. New York: Springer-Verlag.
[16]	World health Organization (WHO), Regional office for South-East Asia New Delhi, (2007) Laboratory Guidelines for enumerating CD4 T Lymphocytes in the context of HIV/AIDS, (www.who.int/hiv/amds/LaboratoryGuideEnumeratingCD4 TLymphocytes.pdf; accessed on December 11, 2016).

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Endale Alemayehu, Tsigereda Tilahun. (2021). Repeated Measure Analysis for the CD4+ Cell Counts of HIV-Positive Patients Initiated to ART: A Case Study at Ambo Hospital. International Journal of Data Science and Analysis, 7(2), 32-38. https://doi.org/10.11648/j.ijdsa.20210702.12

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ACS Style

Endale Alemayehu; Tsigereda Tilahun. Repeated Measure Analysis for the CD4+ Cell Counts of HIV-Positive Patients Initiated to ART: A Case Study at Ambo Hospital. Int. J. Data Sci. Anal. 2021, 7(2), 32-38. doi: 10.11648/j.ijdsa.20210702.12

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AMA Style

Endale Alemayehu, Tsigereda Tilahun. Repeated Measure Analysis for the CD4+ Cell Counts of HIV-Positive Patients Initiated to ART: A Case Study at Ambo Hospital. Int J Data Sci Anal. 2021;7(2):32-38. doi: 10.11648/j.ijdsa.20210702.12

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@article{10.11648/j.ijdsa.20210702.12,
  author = {Endale Alemayehu and Tsigereda Tilahun},
  title = {Repeated Measure Analysis for the CD4+ Cell Counts of HIV-Positive Patients Initiated to ART: A Case Study at Ambo Hospital},
  journal = {International Journal of Data Science and Analysis},
  volume = {7},
  number = {2},
  pages = {32-38},
  doi = {10.11648/j.ijdsa.20210702.12},
  url = {https://doi.org/10.11648/j.ijdsa.20210702.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdsa.20210702.12},
  abstract = {Introduction: HIV is a virus that causes Acquired Immunodeficiency Syndrome (AIDS) by reducing a person's ability to fight the infection. It attacks an immune cell called the CD4 cell which is responsible for the body's immune response to infectious agents. Now a days anti retro viral therapy treatment is avail to elongate the life of patients. The treatment is given for patients to increase the CD4 counts of patients to keep the ability of body preventing the disease. Objectives: This study was aimed to identify the potential associated risk factors with CD4 counts of patients under ART treatment at public hospital in Ethiopia. The other was to fit linear mixed model by handling missing value of the data during follow up time. Method: To see the structure of the data, exploratory data analysis was conducted. Of the familiar variance structures, unstructured variance covariance is selected to be best and to fit the data under study, step-by-step procedure was passed to obtain best model. Results: The descriptive statistics directed that the progressive change in CD4 counts of females seems better than that of males. On the other hand, the output of the fitted model indicated that covariates significant with 5% level of significance is that baseline CD4, time, weight and interaction of Sex, baseline CD4 with time. Allowing the significance level to increase to 25% increases most covariates to be significant that help patients in a better awareness. Conclusion: With this result, full linear mixed with random intercept and slop is found to best model. There was high variability within patients over time and between patients and the interaction of time with covariates was also significant. Generally, the data was fitted by handling the missing value using multiple imputation technique.},
 year = {2021}
}

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TY - JOUR
T1 - Repeated Measure Analysis for the CD4+ Cell Counts of HIV-Positive Patients Initiated to ART: A Case Study at Ambo Hospital
AU - Endale Alemayehu
AU - Tsigereda Tilahun
Y1 - 2021/04/20
PY - 2021
N1 - https://doi.org/10.11648/j.ijdsa.20210702.12
DO - 10.11648/j.ijdsa.20210702.12
T2 - International Journal of Data Science and Analysis
JF - International Journal of Data Science and Analysis
JO - International Journal of Data Science and Analysis
SP - 32
EP - 38
PB - Science Publishing Group
SN - 2575-1891
UR - https://doi.org/10.11648/j.ijdsa.20210702.12
AB - Introduction: HIV is a virus that causes Acquired Immunodeficiency Syndrome (AIDS) by reducing a person's ability to fight the infection. It attacks an immune cell called the CD4 cell which is responsible for the body's immune response to infectious agents. Now a days anti retro viral therapy treatment is avail to elongate the life of patients. The treatment is given for patients to increase the CD4 counts of patients to keep the ability of body preventing the disease. Objectives: This study was aimed to identify the potential associated risk factors with CD4 counts of patients under ART treatment at public hospital in Ethiopia. The other was to fit linear mixed model by handling missing value of the data during follow up time. Method: To see the structure of the data, exploratory data analysis was conducted. Of the familiar variance structures, unstructured variance covariance is selected to be best and to fit the data under study, step-by-step procedure was passed to obtain best model. Results: The descriptive statistics directed that the progressive change in CD4 counts of females seems better than that of males. On the other hand, the output of the fitted model indicated that covariates significant with 5% level of significance is that baseline CD4, time, weight and interaction of Sex, baseline CD4 with time. Allowing the significance level to increase to 25% increases most covariates to be significant that help patients in a better awareness. Conclusion: With this result, full linear mixed with random intercept and slop is found to best model. There was high variability within patients over time and between patients and the interaction of time with covariates was also significant. Generally, the data was fitted by handling the missing value using multiple imputation technique.
VL - 7
IS - 2
ER -

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Endale Alemayehu

Departments of Statistics, Ambo University, Ambo, Ethiopia
Tsigereda Tilahun

Departments of Statistics, Ambo University, Ambo, Ethiopia

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APA Style

Endale Alemayehu, Tsigereda Tilahun. (2021). Repeated Measure Analysis for the CD4+ Cell Counts of HIV-Positive Patients Initiated to ART: A Case Study at Ambo Hospital. International Journal of Data Science and Analysis, 7(2), 32-38. https://doi.org/10.11648/j.ijdsa.20210702.12

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ACS Style

Endale Alemayehu; Tsigereda Tilahun. Repeated Measure Analysis for the CD4+ Cell Counts of HIV-Positive Patients Initiated to ART: A Case Study at Ambo Hospital. Int. J. Data Sci. Anal. 2021, 7(2), 32-38. doi: 10.11648/j.ijdsa.20210702.12

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AMA Style

Endale Alemayehu, Tsigereda Tilahun. Repeated Measure Analysis for the CD4+ Cell Counts of HIV-Positive Patients Initiated to ART: A Case Study at Ambo Hospital. Int J Data Sci Anal. 2021;7(2):32-38. doi: 10.11648/j.ijdsa.20210702.12

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@article{10.11648/j.ijdsa.20210702.12,
  author = {Endale Alemayehu and Tsigereda Tilahun},
  title = {Repeated Measure Analysis for the CD4+ Cell Counts of HIV-Positive Patients Initiated to ART: A Case Study at Ambo Hospital},
  journal = {International Journal of Data Science and Analysis},
  volume = {7},
  number = {2},
  pages = {32-38},
  doi = {10.11648/j.ijdsa.20210702.12},
  url = {https://doi.org/10.11648/j.ijdsa.20210702.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdsa.20210702.12},
  abstract = {Introduction: HIV is a virus that causes Acquired Immunodeficiency Syndrome (AIDS) by reducing a person's ability to fight the infection. It attacks an immune cell called the CD4 cell which is responsible for the body's immune response to infectious agents. Now a days anti retro viral therapy treatment is avail to elongate the life of patients. The treatment is given for patients to increase the CD4 counts of patients to keep the ability of body preventing the disease. Objectives: This study was aimed to identify the potential associated risk factors with CD4 counts of patients under ART treatment at public hospital in Ethiopia. The other was to fit linear mixed model by handling missing value of the data during follow up time. Method: To see the structure of the data, exploratory data analysis was conducted. Of the familiar variance structures, unstructured variance covariance is selected to be best and to fit the data under study, step-by-step procedure was passed to obtain best model. Results: The descriptive statistics directed that the progressive change in CD4 counts of females seems better than that of males. On the other hand, the output of the fitted model indicated that covariates significant with 5% level of significance is that baseline CD4, time, weight and interaction of Sex, baseline CD4 with time. Allowing the significance level to increase to 25% increases most covariates to be significant that help patients in a better awareness. Conclusion: With this result, full linear mixed with random intercept and slop is found to best model. There was high variability within patients over time and between patients and the interaction of time with covariates was also significant. Generally, the data was fitted by handling the missing value using multiple imputation technique.},
 year = {2021}
}

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