Predictors of CD4 count over time among HIV patients initiated ART in Felege Hiwot Referral Hospital, northwest Ethiopia: multilevel analysis

Abstract

BackgroundThe response of HIV patients to antiretroviral therapy could be measured by its strong predictor, the CD4+ T cell (CD4) count for the initiation of antiretroviral therapy and proper management of disease progress. However, in addition to HIV, there are other factors which can influence the CD4 cell count. Patient’s socio-economic, demographic, and behavioral variables, accessibility, duration of treatment etc., can be used to predict CD4 count.MethodsA retrospective cohort study was conducted to examine the predictors of CD4 count among ART users enrolled in the first 6 months of 2010 and followed upto mid 2014. The covariance components model was employed to determine the predictors of CD4 count over time.ResultsA total of 1196 ART attendants were used to analyze their data descriptively. Eight hundred sixty-one of the attendants had two or more CD4 count measurements and were used in modeling their data using the linear mixed method. Thus, the mean rates of incensement of CD4 counts for patients with ambulatory/bedridden and working baseline functional status were 17.4 and 30.6 cells/mm3 per year, respectively. After adjusting for other variables, for each additional baseline CD4 count, the gain in CD4 count during treatment was 0.818 cells/mm3 (p value <0.001). Patient’s age and baseline functional status were also statistically significantly associated with CD4 count.ConclusionIn this study, higher baseline CD4 count, younger age, working functional status, and time in treatment contributed positively to the increment of the CD4 count. However, the observed increment at 4 year was unsatisfactory as the proportion of ART users who reached the normal range of CD4 count was very low. To see their long term treatment outcome, it requires further research with a sufficiently longer follow up data. In line with this, the local CD4 count for HIV negative persons should also be investigated for better comparison and proper disease management.

Statistical Joint Modeling of Longitudinal CD4 Cell variation and Time-to-Lost Follow-up from ART Predictors on HIV/AIDS Patients: A case of Mekelle General Hospital

“…The progression change about √ (CD4 cell) count on patients for those bedridden functional status patients was less than those working functional status when controlling other independent variables. This study agreed with the findings of [19].…”

“…In ART follow-up, CD4 cell is measured repetitively over time and this rise of CD4 cell change at every visiting time inspires the patient to be a good adherent to their regimen [17][18][19].…”

Immunological outcomes of neverapin (NVP) versus efafrenz (EFV) based antiretroviral therapy (ART) regimen among children on ART: A study from Black Lion Hospital, Addis Ababa, Ethiopia

“…Another cohort study in ARV Thai adult patients with advanced HIV infection showed that NVP-and EFV-based HAART regimens were equally effective in terms of virological and immunological responses (Lapphra et al, 2008). The positive association between younger age groups and better immune recovery demonstrated comparably among the two groups in this study which is in congruence with other previous pediatric and adult reports (de Castilla et al, 2008;Reda et al, 2013;Gezie, 2016;Asfaw et al, 2015;Eshun-Wilson et al, 2012). This might be justified by high reserve of lymphocytes cell and early initiation of ART among younger age groups.…”

A Recursive Binary Tree Model for the Analysis of the Response to Antiretroviral Therapy of HIV Infected Adults in Burkina Faso

“…The high proportion of patients (83%) in this condition may partly explain this finding. Gezie et al [24] found Age as a predictor of CD4 counts over time in Ethiopia. Younger age was positively correlated to CD4 count increase during the course of treatment.…”