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Quasi-Poisson versus negative binomial regression models in identifying factors affecting initial CD4 cell count change due to antiretroviral therapy administered to HIV-positive adults in North–West Ethiopia (Amhara region)
BACKGROUND: CD4 cells are a type of white blood cells that plays a significant role in protecting humans from infectious diseases. Lack of information on associated factors on CD4 cell count reduction is an obstacle for improvement of cells in HIV positive adults. Therefore, the main objective of th...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5103612/ https://www.ncbi.nlm.nih.gov/pubmed/27843481 http://dx.doi.org/10.1186/s12981-016-0119-6 |
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author | Seyoum, Awoke Ndlovu, Principal Zewotir, Temesgen |
author_facet | Seyoum, Awoke Ndlovu, Principal Zewotir, Temesgen |
author_sort | Seyoum, Awoke |
collection | PubMed |
description | BACKGROUND: CD4 cells are a type of white blood cells that plays a significant role in protecting humans from infectious diseases. Lack of information on associated factors on CD4 cell count reduction is an obstacle for improvement of cells in HIV positive adults. Therefore, the main objective of this study was to investigate baseline factors that could affect initial CD4 cell count change after highly active antiretroviral therapy had been given to adult patients in North West Ethiopia. METHODS: A retrospective cross-sectional study was conducted among 792 HIV positive adult patients who already started antiretroviral therapy for 1 month of therapy. A Chi square test of association was used to assess of predictor covariates on the variable of interest. Data was secondary source and modeled using generalized linear models, especially Quasi-Poisson regression. RESULTS: The patients’ CD4 cell count changed within a month ranged from 0 to 109 cells/mm(3) with a mean of 15.9 cells/mm(3) and standard deviation 18.44 cells/mm(3). The first month CD4 cell count change was significantly affected by poor adherence to highly active antiretroviral therapy (aRR = 0.506, P value = 2e(−16)), fair adherence (aRR = 0.592, P value = 0.0120), initial CD4 cell count (aRR = 1.0212, P value = 1.54e(−15)), low household income (aRR = 0.63, P value = 0.671e(−14)), middle income (aRR = 0.74, P value = 0.629e(−12)), patients without cell phone (aRR = 0.67, P value = 0.615e(−16)), WHO stage 2 (aRR = 0.91, P value = 0.0078), WHO stage 3 (aRR = 0.91, P value = 0.0058), WHO stage 4 (0876, P value = 0.0214), age (aRR = 0.987, P value = 0.000) and weight (aRR = 1.0216, P value = 3.98e(−14)). CONCLUSIONS: Adherence to antiretroviral therapy, initial CD4 cell count, household income, WHO stages, age, weight and owner of cell phone played a major role for the variation of CD4 cell count in our data. Hence, we recommend a close follow-up of patients to adhere the prescribed medication for achievements of CD4 cell count change progression. |
format | Online Article Text |
id | pubmed-5103612 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-51036122016-11-14 Quasi-Poisson versus negative binomial regression models in identifying factors affecting initial CD4 cell count change due to antiretroviral therapy administered to HIV-positive adults in North–West Ethiopia (Amhara region) Seyoum, Awoke Ndlovu, Principal Zewotir, Temesgen AIDS Res Ther Research BACKGROUND: CD4 cells are a type of white blood cells that plays a significant role in protecting humans from infectious diseases. Lack of information on associated factors on CD4 cell count reduction is an obstacle for improvement of cells in HIV positive adults. Therefore, the main objective of this study was to investigate baseline factors that could affect initial CD4 cell count change after highly active antiretroviral therapy had been given to adult patients in North West Ethiopia. METHODS: A retrospective cross-sectional study was conducted among 792 HIV positive adult patients who already started antiretroviral therapy for 1 month of therapy. A Chi square test of association was used to assess of predictor covariates on the variable of interest. Data was secondary source and modeled using generalized linear models, especially Quasi-Poisson regression. RESULTS: The patients’ CD4 cell count changed within a month ranged from 0 to 109 cells/mm(3) with a mean of 15.9 cells/mm(3) and standard deviation 18.44 cells/mm(3). The first month CD4 cell count change was significantly affected by poor adherence to highly active antiretroviral therapy (aRR = 0.506, P value = 2e(−16)), fair adherence (aRR = 0.592, P value = 0.0120), initial CD4 cell count (aRR = 1.0212, P value = 1.54e(−15)), low household income (aRR = 0.63, P value = 0.671e(−14)), middle income (aRR = 0.74, P value = 0.629e(−12)), patients without cell phone (aRR = 0.67, P value = 0.615e(−16)), WHO stage 2 (aRR = 0.91, P value = 0.0078), WHO stage 3 (aRR = 0.91, P value = 0.0058), WHO stage 4 (0876, P value = 0.0214), age (aRR = 0.987, P value = 0.000) and weight (aRR = 1.0216, P value = 3.98e(−14)). CONCLUSIONS: Adherence to antiretroviral therapy, initial CD4 cell count, household income, WHO stages, age, weight and owner of cell phone played a major role for the variation of CD4 cell count in our data. Hence, we recommend a close follow-up of patients to adhere the prescribed medication for achievements of CD4 cell count change progression. BioMed Central 2016-11-09 /pmc/articles/PMC5103612/ /pubmed/27843481 http://dx.doi.org/10.1186/s12981-016-0119-6 Text en © The Author(s) 2016 Open AccessThis article is 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, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Seyoum, Awoke Ndlovu, Principal Zewotir, Temesgen Quasi-Poisson versus negative binomial regression models in identifying factors affecting initial CD4 cell count change due to antiretroviral therapy administered to HIV-positive adults in North–West Ethiopia (Amhara region) |
title | Quasi-Poisson versus negative binomial regression models in identifying factors affecting initial CD4 cell count change due to antiretroviral therapy administered to HIV-positive adults in North–West Ethiopia (Amhara region) |
title_full | Quasi-Poisson versus negative binomial regression models in identifying factors affecting initial CD4 cell count change due to antiretroviral therapy administered to HIV-positive adults in North–West Ethiopia (Amhara region) |
title_fullStr | Quasi-Poisson versus negative binomial regression models in identifying factors affecting initial CD4 cell count change due to antiretroviral therapy administered to HIV-positive adults in North–West Ethiopia (Amhara region) |
title_full_unstemmed | Quasi-Poisson versus negative binomial regression models in identifying factors affecting initial CD4 cell count change due to antiretroviral therapy administered to HIV-positive adults in North–West Ethiopia (Amhara region) |
title_short | Quasi-Poisson versus negative binomial regression models in identifying factors affecting initial CD4 cell count change due to antiretroviral therapy administered to HIV-positive adults in North–West Ethiopia (Amhara region) |
title_sort | quasi-poisson versus negative binomial regression models in identifying factors affecting initial cd4 cell count change due to antiretroviral therapy administered to hiv-positive adults in north–west ethiopia (amhara region) |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5103612/ https://www.ncbi.nlm.nih.gov/pubmed/27843481 http://dx.doi.org/10.1186/s12981-016-0119-6 |
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