Evolution of CD4 Cell Counts over Time for HIV/AIDS Patients on Antiretroviral Therapy (ART) In Mildmay Uganda

Lubyayi, Lawrence

doi:10.15406/bbij.2015.02.00025

Cited by 4 publications

(6 citation statements)

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“…The impact of age on immunologic recovery was well described [ 26 ] and this study had found concordance with previous findings. Accordingly, the CD4+ gain attained by younger (<25 years) patients was +66 cells/mm 3 as compared to those older than 45 years of age (β = −66.19, 95% CI [−126.68,−5.70], P = 0.032).…”

Section: Discussionsupporting

confidence: 93%

“…Study by Mauro et al [ 25 ] has confirmed older age as a key independent predictor for sub-optimal immunologic response as thymus activity decreases with age [ 26 ]. This finding agreed with our result where older age was statistically significant negative predictor of CD4+ gain on multiple regression.…”

Section: Discussionmentioning

confidence: 99%

“…The pre-treatment CD4+ count in relation to sub-optimal immunologic response, however, is controversial as some literatures favour higher baseline CD4+ (>200 cells/mm 3 ) [ 26 ] and explained it as “starting treatment at higher CD4+ cell counts limits the scope for further increases”. Other literatures favoured lower baseline CD4+ count (<200 cells/mm 3 ) and this is biologically plausible given that a low nadir pre-treatment CD4+ cell count is thought to be suggestive of more extensive depletion of CD4+ cells in the gut-associated lymphoid tissue during acute HIV infection, and may be delayed or refractory to reconstitution with ART [ 27 ].…”

Section: Discussionmentioning

confidence: 99%

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Immunological outcomes of Tenofovir versus Zidovudine-based regimens among people living with HIV/AIDS: a two years retrospective cohort study

2017

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BackgroundTenofovir (TDF) based regimen was reported to have better immunological outcomes. Unfortunately, there is limited information regarding the immunologic outcome associated with this regimen in Ethiopia, as its routine utilization in this setting begun since 2013.MethodsA 2 years retrospective cohort study was conducted at Jimma University Specialized Hospital, 346 km Southwest of Addis Ababa, Ethiopia. A total of 280 patients’ data from September 2012 to July 2014 was extracted from records from February 10, 2015 to March 10, 2015. Records were selected using a simple random sampling technique. Data on socio-demographic, clinical and drug related variables were collected; entered into EpiData 3.1 and analyzed by STATA 13.1. Mixed effect linear regression was performed to assess difference in CD4+ change between groups adjusting for baseline characteristics. The change in predicted CD4 count attributed to each regimen was also assessed by marginal analysis. P < 0.05 for slopes of the random effect linear regression was used as indicators for presence of association.ResultsThe mean (SD) duration of cohort follow up was 714.2 (69.6) and 708.8 (78.9) days (P = 0.753) for TDF and AZT groups respectively. The minimum follow up duration was 7.4 and 8.9 months for TDF and AZT groups respectively. Most of TDF (93.6%) and AZT (91.4%) groups completed their follow up, 5 (3.6%) TDF and 6 (4.3%) AZT groups died and 4 (2.9%) TDF and 6 (4.3%) AZT groups were lost for follow-up (P = 0.769). There was statistically significant difference in immunologic recovery between the groups (B = +34.08, 95% CI [7.8, 60.35], P = 0.027) over time. The predicted CD4+ count for TDF/3TC/EFV was (B = +347.65 cells/mm3, P < 0.001) whereas that of AZT/3TC/EFV was (B = +281.54 cells/mm3, P < 0.001).ConclusionsTDF based regimens have shown more efficacy compared to AZT based regimens though AZT based regimens are more affordable in low income countries like Ethiopia. However, we recommend further study with quality design to assess the prevalence of sub-optimal CD4+ response (net CD4 gain <50 cells/µl/6 month) in this set-up among TDF users.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Immunological outcomes of Tenofovir versus Zidovudine-based regimens among people living with HIV/AIDS: a two years retrospective cohort study

2017

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“…This result was inversely proportional to the research done by Lubyayi et al, which stated that patients who initiate antiretroviral treatment with higher initial CD4+ cell counts would experience higher increases in CD4+ cell counts [8]. Patients with an initial CD4+ cell count of < 200 cells/mm 3 have not achieved an increase in CD4+ values, despite taking antiretrovirals for years [17]. However, not all studies have suggested that an early CD4+ cell count will affect the CD4+ cell count increase.…”

Section: Discussionmentioning

confidence: 83%

Comparison of Zidovudine Combination and Tenofovir Combination on the Effectiveness of Therapy and Side Effects in Hiv/Aids Patients in Rsal Mintohardjo

Insaniputri

Supardi

Andrajati

2017

Asian J Pharm Clin Res

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Objectives: Tenofovir-based therapy is a newly adopted first-line HIV/AIDS therapy regimen in Indonesia that is replacing the stavudine-based regimen. However, zidovudine-based regimens remain the first-line therapy for patients with HIV/AIDS. This study aimed to compare the effectiveness and incidence of adverse effects with hemoglobin (Hb) in both zidovudine-and tenofovir-based regimens in HIV/AIDS patients at Mintohardjo Hospital. Methods:We used a cross-sectional comparative research design. The data analyzed were medical records of all HIV/AIDS patients treated through 2015. Results:The sample included 75 patients in the zidovudine group and 53 patients in the tenofovir group. Wilcoxon signed-rank tests indicated that both combinations of therapy were effective in improving CD4+ cells. Initial CD4+ cell counts ≤ 200 cells/mm 3 were 4.55 times better at increasing CD4+ cell counts when compared with an initial CD4+ > 200 cells/mm 3 . Chi-square results showed that both treatment combinations affected the decrease in Hb. Patients using the zidovudine combination had 4.59 times greater risk for a Hb decrease compared with the tenofovir combination. Conclusions:Zidovudine-and tenofovir-based regimens had similar effectiveness in increasing CD4+ cell counts, but the tendency to cause anemia in tenofovir-based regimens was less than that of the zidovudine-based regimens.

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“…Similarly, a study in eastern Ethiopia [20] used a linear mixed model which ignores the non-linear nature of the evolution. Another longitudinal study in Uganda [21] included cubic time effect to account the non-linear nature of CD4 count. In the current study, we proposed a flexible parametric modeling, the fractional polynomials framework [22–26], to predict a subject specific evolution of CD4 counts over time.…”

Section: Introductionmentioning

confidence: 99%

Model-based prediction of CD4 cells counts in HIV-infected adults on antiretroviral therapy in Northwest Ethiopia: A flexible mixed effects approach

et al. 2019

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Background CD4 cell counts is widely used as a biomarker for treatment progression when studying the efficacy of drugs to treat HIV-infected patients. In the past, it had been also used in determining eligibility to initiate antiretroviral therapy. The main aim of this was to model the evolution of CD4 counts over time and use this model for an early prediction of subject-specific time to cross a pre-specified CD4 threshold. Methods Hospital based retrospective cohort study of HIV-infected patients was conducted from January 2009 to December 2014 at University of Gondar hospital, Northwest Ethiopia. Fractional polynomial random effect model is used to model the evolution of CD4 counts over time in response to treatment and to estimate the individual probability to be above a pre-selected CD4 threshold. Human subject research approval for this study was received from University of Gondar Research Ethics Committee and the medical director of the hospital. Results A total of 1347 patients were included in the analysis presented in this paper. The cohort contributed a total of 236.58 per 100 person-years of follow-up. Later the data were divided into two periods: the first is the estimation period in which the parameters of the model are estimated and the second is the prediction period. Based on the parameters from the estimation period, model based prediction for the time to cross a threshold was estimated. The correlations between observed and predicted values of CD4 levels in the estimation period were 0.977 and 0.982 for Neverapine and Efavirenz containing regimens, respectively; while the correlation between the observed and predicted CD4 counts in the prediction period are 0.742 and 0.805 for NVP and EFV, respectively. Conclusions The model enables us to estimate a subject-specific expected time to cross a CD4 threshold and to estimate a subject-specific probability to have CD4 count above a pre-specified threshold at each time point. By predicting long-term outcomes of CD4 count of the patients one can advise patient about the potential ART benefits that accrue in the long-term.

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Evolution of CD4 Cell Counts over Time for HIV/AIDS Patients on Antiretroviral Therapy (ART) In Mildmay Uganda

Cited by 4 publications

References 10 publications

Immunological outcomes of Tenofovir versus Zidovudine-based regimens among people living with HIV/AIDS: a two years retrospective cohort study

Immunological outcomes of Tenofovir versus Zidovudine-based regimens among people living with HIV/AIDS: a two years retrospective cohort study

Comparison of Zidovudine Combination and Tenofovir Combination on the Effectiveness of Therapy and Side Effects in Hiv/Aids Patients in Rsal Mintohardjo

Model-based prediction of CD4 cells counts in HIV-infected adults on antiretroviral therapy in Northwest Ethiopia: A flexible mixed effects approach

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