Archive
2020, Volume 4
2019, Volume 3
2018, Volume 2
2017, Volume 1




Volume 4, Issue 1, June 2020, Page: 1-6
Evaluation of CD4 Cell Progression Among HIV Infected Children Initiating ART: A Case of Adama Referral Hospital and Medical College, Ethiopia
Tayu Nigusie Abebe, Department of Statistics, Bule Hora University, Bule Hora, Ethiopia
Received: Dec. 12, 2019;       Accepted: Dec. 23, 2019;       Published: Apr. 8, 2020
DOI: 10.11648/j.plm.20200401.11      View  96      Downloads  23
Abstract
Human immune deficiency virus (HIV) is a major cause of infant and childhood mortality and morbidity; without treatment about 50% of them will succumb to HIV/AIDS before the age of two years. HIV infected children should start ART in order to reduce AIDS related morbidity and mortality, or to improve their survival time. Effective therapies and reduced AIDS related morbidity and mortality have shifted the focus in pediatric human immune deficiency virus (HIV) from minimizing short-term disease progression to maintaining optimal long-term health. The main purpose of this study was to evaluate the predictors of longitudinal CD4 cell progression of HIV infected children who were under ART. The study considered a cohort of 201 HIV infected children who were aged 15 years or younger and those were on ART from October 1, 2013 to March 30, 2017 at Adama Referral Hospital and Medical College. To analyze the data we employed exploratory data analysis and linear mixed effect model. The result from linear mixed effect model reviled that observation time, age, WHO clinical stage, history of TB, and functional status had significantly associated with mean change in the square root of CD4 cell count, and they are the predictor of longitudinal CD4 cell change.
Keywords
CD4 Cell Count, HIV/AIDS, Linear Mixed Effect Model
To cite this article
Tayu Nigusie Abebe, Evaluation of CD4 Cell Progression Among HIV Infected Children Initiating ART: A Case of Adama Referral Hospital and Medical College, Ethiopia, Pathology and Laboratory Medicine. Vol. 4, No. 1, 2020, pp. 1-6. doi: 10.11648/j.plm.20200401.11
Copyright
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Reference
[1]
UNAIDS/WHO. AIDS epidemic update Executive summary. Geneva: Joint United Nation Programmes on HIV/ AIDS, 2006: 1–36.
[2]
WHO. Scaling Up Antiretroviral Therapy in Resource-Limited Settings. Available at: http://www.who.int.
[3]
UNAIDS, Joint United Nations Programme on HIV/AIDS, Global AIDS Update 2018, available at URL: http://www.unAIDS.org/sites/default/files/media asset/global-AIDS update 2018 en pdf.
[4]
Ethiopian Public Health Institute (EPHI), Federal Ministry of Health. HIV Related Estimates and Projections for Ethiopia July, 2017, Addis Ababa, Ethiopia.
[5]
Ashir, G. M., Rabasa, A. I., Gofama, M. M., Elechi, H. A., & Lawan, B. M. (2014). Clinical Staging of HIV Infection as a Surrogate for CD4 Count in HIV-Infected Children. West African Journal Of Medicine: 29 (5).
[6]
Welch, S. B., & Gibb, D. (2014). When should children with HIV infection be started on antiretroviral therapy. PLoS medicine, 5 (3), e73.
[7]
Hannah, M., & Dhayendre, M. (2012). The impact of highly active antiretroviral therapy on obstetric conditions: a review. European Journal of Obstetrics & Gynecology and Reproductive Biology, 210, 126-131.
[8]
Mellors, JW., Munoz, A., Giorgi, JV., Margolick, JB., Tassoni, CJ., & Gupta, P. (1997). Plasma viral load and CD4z lymphocytes as prognostic markers of HIV-1 infection. Ann Intern Med 1997; 126: 946–54.
[9]
Chattopadhya, D., Baveja, UK., Bose, M., & Kumar, A. (2002). Disease progression markers during asymptomatic phase of HIV-1 infected children with unimpaired CD4 cell values. J Trop Pediatr 2002; 48: 340–7.
[10]
Yogev, R., & Chadwick, EG. (2001). Acquired immunodeficiency syndrome. Nelson Text book of Pediatrics. WB Saunders co. 2001: 1022–1032.
[11]
Tara, N., & Mangal, T. D. (2015). CD4 Progression and Mortality Amongst HIV Seroconverters including the CASCADE Collaboration in EuroCoord. (London, England), 31 (8), 1073–1082.
[12]
Fuu-Jen, T., Chi Fung, C., Chih Ho, L., Yang Chang, W., Mao Wang H., Jen Hsien, W., Ni Tien, T., Xiang, L., Hsinyi, T., Ting Hsu, L., Chiu Chu, L., Shao Mei, H., Ju Pi, L., Jung Chun, L., Chih Chien, L., Jin Hua, L., & Ying-Ju L. (2017). Effect of antiretroviral therapy use and adherence on the risk of hyper lipidemia among HIV infected patients, in the highly active antiretroviral therapy era: Oncotarget, 2017, Vol. 8, (No. 63), pp: 106369-106381.
[13]
Verbeke, G., & Molenberghs, G. (2000). Linear Mixed Models for Longitudinal Data. new York: Springer.
[14]
Fitzmaurice, G. M., Laird, N. M., & Ware, J. H. (2011). Applied Longitudinal Analysis (2nd ed. New York: Wiley). Circulation, 118: 2005‐2010.
[15]
Fitzmaurice, G., Molenberghs, G., Davidian, M., & Verbeke, G. (2008). Generalized estimating equations for longitudinal data analysis. Chapman and Hall/CRC. (pp. 51-86).
[16]
Laird, N. M., & Ware, J. H. (1982). Random-effects models for longitudinal data. Biometrics, 38 (4), 963-974.
[17]
Little, R. J. A. (2006). Modeling the drop out mechanism in repeated measures studies. Journal of the American Statistical Association, 90 (431): 1112-1121.
[18]
Marie-Quitterie, P., Joanna, L., Victor, M., Andrew P., Kusum, N., & Addy, K. (2013). Predicting Patterns of Long-Term CD4 Reconstitution in HIV-Infected Children Starting Antiretroviral Therapy in Sub-Saharan Africa: A Cohort-Based Modelling Study: PLoS Med 10 (10): e1001542.
[19]
Lemma, G. (2016). Predictors of CD4 count over time among HIV patients initiated ART in Felege Hiwot Referral Hospital, northwest Ethiopia: multilevel analysis. BMC Research Notes volume 9, Article number: 377 (2016).
[20]
Tekle, G., Kassahun, W., & Gurmessa, A. (2016). Statistical Analysis of CD4 Cell Counts progression of HIV- positive Patients enrolled in Antiretroviral Therapy at Hossana District Queen Elleni Mohamad Memorial Hospital, South Ethiopia. BiomBiostatInt J 3 (1): 00057.
[21]
Aboma, T., Abdisa, G., & Yehenew, G. (2018). Joint Modeling of Longitudinal CD4 Count and Time to Death of HIV/TB Co-infected Patients: A Case of Jimma University Specialized Hospital. Annals of Data Science, 5 (4), 659-678.
[22]
Abdulbasit, A., Luguterah, A., Nasiru, S., & Abdul Rahaman, S. (2018). Joint Longitudinal and Survival Modeling of HIV in the Upper West Region of Ghana. International Journal of Health Sciences, 6 (1), 56-63.
Browse journals by subject