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), 2021. Published by Science Publishing Group |
Longitudinal Data Analysis, CD4+, ART, Linear Mixed Model
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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
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
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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Download@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}
}
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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