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Predictors of CD4 count changes over time among children who initiated highly active antiretroviral therapy in Ethiopia.

ABSTRACT: Introduction:Human immunodeficiency virus (HIV) infection results in a gradual depletion of immune function, particularly CD4 cells. The CD4 assessment plays a significant role in assessing treatment responses and clinical decision-making for patients on combination antiretroviral therapy (ART) in resource-limited settings. However, new data on CD4 count changes are scarce; the volatility of CD4 counts after initiation of ART over time remains largely uncharacterized. This study aimed to identify the predictors of CD4 changes over time among HIV-infected children who began ART in Amhara, Ethiopia. Methods:A retrospective follow-up study was performed. A total of 983 HIV-infected children who initiated ART in government hospitals in the Amhara region between 2010 and 2016 were included using a simple random sampling technique. Data were extracted using a structured checklist. An exploratory data analysis was carried out to explain individual and average profile plots. The linear mixed model was used to identify the CD4 change count predictors over time. Variables with p value < 0.05 were considered statistically significant in a multivariable linear mixed regression analysis. Results:The mean CD4 count of the participants was 465.1 cells/mm3 with an average CD4 count increase of 30.06 cells/mm3 over 6 months from baseline CD4 count and ART initiation. Childhood age (? = - 0.015; 95% Cl - 0.021, - 0.009), opportunistic infection at ART initiation (? = - 0.044, 95% CI - 0.085, - 0.004), hemoglobin level (? = 0.013; 95% CI 0.004, 0.022), and baseline WHO clinical stage II (? = - 0.046, 95% CI - 0.091, - 0.0003) were significant predictors of CD4 changes over time. Conclusions:The average CD4 count increase was sufficient in HIV patients who began combined antiretroviral therapy over time. The younger age of the infant, the higher baseline level of hemoglobin, the baseline WHO clinical stage II, and opportunistic infections led to changes in CD4 counts. As a result, timely diagnosis and treatment of opportunistic infections will reduce the risk of opportunistic infections.

SUBMITTER: Birhan TY

PROVIDER: S-EPMC7243309 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Predictors of CD4 count changes over time among children who initiated highly active antiretroviral therapy in Ethiopia.

Birhan Tilahun Yemanu TY Gezie Lemma Derseh LD Teshome Destaw Fetene DF Sisay Malede Mequanent MM

Tropical medicine and health 20200522

<h4>Introduction</h4>Human immunodeficiency virus (HIV) infection results in a gradual depletion of immune function, particularly CD4 cells. The CD4 assessment plays a significant role in assessing treatment responses and clinical decision-making for patients on combination antiretroviral therapy (ART) in resource-limited settings. However, new data on CD4 count changes are scarce; the volatility of CD4 counts after initiation of ART over time remains largely uncharacterized. This study aimed to ...[more]

PMID: 32476985

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Project description:BackgroundAlthough antiretroviral therapy has significantly altered the natural history of human immunodeficiency virus infection and improved the quality of life of patients, there are conflicting reports regarding its impact on hematological outcomes. Thus, this study aimed at investigating the prevalence and predictors of anemia among adults on antiretroviral therapy in Northeast Ethiopia.Materials and methodsA retrospective cohort study was carried out among adults who began antiretroviral treatment between September 2005 and January 2019 at two governmental hospitals in Dessie town. Data were collected from patients' medical records using a pretested data extraction instrument. Anemia was the primary outcome variable of the study. It was defined based on WHO criteria after adjustment for altitude and smoking status of measured values. Data were entered and validated using EpiData Version 3.1 and then exported to SPSS Version 20.0 for analysis. Descriptive analysis was done for prevalence and binary logistic regression was carried out to assess whether covariates were associated with experiencing anemia. Statistical significance has been considered at p-value <0.05.ResultsMedical records of 392 patients (mean age: 35.58 ± 9.46 years) were reviewed. Of the total 392 patients, 218 (55.6%) were females, 261 (66.6%) were categorized under WHO clinical stage III/IV and 134 (34.2%) had a baseline CD4 cell count of <100 cells/mm3. The mean baseline CD4 cell count was 179 cells/mm3 (range: 2 to 853 cells) and 230 (58.7%) of the participants were on zidovudine-based regimen. Anemia was diagnosed among 162 (41.3%) patients. After adjustment for other confounding factors, risk of anemia was significantly associated with low baseline CD4 cell count (AOR 1.80, 95% CI 1.05-3.06) and tenofovir based regimen (AOR 2.05, 95% CI 1.31-3.21). On the other hand, being educated was found to be protective (AOR 0.40, 95% CI 0.21-0.78).ConclusionIn this research, the prevalence of anemia was relatively high. Low baseline CD4 cell count and tenofovir based regimen were independent predictors of anemia; while being educated was protective. Treatment programs should focus on early diagnosis and treatment of HIV as well as routine screening and proper treatment of anemia.

Project description:BackgroundModelling of longitudinal biomarkers and time-to-event data are important to monitor disease progression. However, these two variables are traditionally analyzed separately or time-varying Cox models are used. The former strategy fails to recognize the shared random-effects from the two processes while the latter assumes that longitudinal biomarkers are exogenous covariates, resulting in inefficient or biased estimates for the time-to-event model. Therefore, we used joint modelling for longitudinal and time-to-event data to assess the effect of longitudinal CD4 count on mortality.MethodsWe studied 4014 patients from the Centre for the AIDS Programme of Research in South Africa (CAPRISA) who initiated ART between June 2004 and August 2013. We used proportional hazards regression model to assess the effect of baseline characteristics (excluding CD4 count) on mortality, and linear mixed effect models to evaluate the effect of baseline characteristics on the CD4 count evolution over time. Thereafter, the two analytical approaches were amalgamated to form an advanced joint model for studying the effect of longitudinal CD4 count on mortality. To illustrate the virtues of the joint model, the results from the joint model were compared to those from the time-varying Cox model.ResultsUsing joint modelling, we found that lower CD4 count over time was associated with a 1.3-fold increase in the risk of death, (HR: 1.34, 95% CI: 1.27-1.42). Whereas, results from the time-varying Cox model showed lower CD4 count over time was associated with a 1.2-fold increase in the risk of death, (HR: 1.17, 95% CI: 1.12-1.23).ConclusionsJoint modelling enabled the assessment of the effect of longitudinal CD4 count on mortality while correcting for shared random effects between longitudinal and time-to-event models. In the era of universal test and treat, the evaluation of CD4 count is still crucial for guiding the initiation and discontinuation of opportunistic infections prophylaxis and assessment of late presenting patients. CD4 count can also be used when immunological failure is suspected as we have shown that it is associated with mortality.

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Predictors of CD4 count changes over time among children who initiated highly active antiretroviral therapy in Ethiopia.

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Predictors of CD4 count changes over time among children who initiated highly active antiretroviral therapy in Ethiopia.

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