Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Seyoum, Awoke, Ndlovu, Principal, Zewotir, Temesgen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
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
_version_ 1782466631678558208
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
work_keys_str_mv AT seyoumawoke quasipoissonversusnegativebinomialregressionmodelsinidentifyingfactorsaffectinginitialcd4cellcountchangeduetoantiretroviraltherapyadministeredtohivpositiveadultsinnorthwestethiopiaamhararegion
AT ndlovuprincipal quasipoissonversusnegativebinomialregressionmodelsinidentifyingfactorsaffectinginitialcd4cellcountchangeduetoantiretroviraltherapyadministeredtohivpositiveadultsinnorthwestethiopiaamhararegion
AT zewotirtemesgen quasipoissonversusnegativebinomialregressionmodelsinidentifyingfactorsaffectinginitialcd4cellcountchangeduetoantiretroviraltherapyadministeredtohivpositiveadultsinnorthwestethiopiaamhararegion