Time to death predictors of HIV/AIDS infected patients on antiretroviral therapy in Ethiopia

Tadege, Melaku

doi:10.1186/s13104-018-3863-y

Cited by 22 publications

(46 citation statements)

References 12 publications

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“…The risk of survival time to death on patients for those who had developed HIV/TB (yes) patients was more risk than those had not developed HIV/TB (No) patients when controlling other independent variables. These results conformed to the studies conducted [6,12]. This shows that, the main known risk factor for mortality in HIV/AIDS patients are TB development.…”

Section: Discussionsupporting

confidence: 90%

“…That means, Patient's baseline CD4+ count significantly impact on his or her survival time. This study was agreed with a study [6,12]. The progression change of √ 4 count on patients for those who had developed HIV/TB (yes) patients was less than those had not developed HIV/TB (No) patients when controlling other independent variables.…”

Section: Discussionsupporting

confidence: 79%

“…Ethiopia is one of the most highly affected among the seven countries that are greatest hit by the HIV/AIDS pandemic diseases in Sub-Saharan Africa [5]. Approximately to about one million people living with HIV becomes the leading cause of mortality among 15-49 years of age that accounts for 43% of all population deaths in 2016, and approximately a total of 114,690 people died of AIDS related conditions [6].…”

Section: Introductionmentioning

confidence: 99%

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Statistical Joint Modeling on Longitudinal Body Weight and CD4 Cell Progression with Survival Time-to-Death Predictors on HIV/AIDS Patients in Mekelle General Hospital, Ethiopia.

Gebrerufael

Asfaw

Melese

2020

Preprint

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Background This study assessed the impact of repeated biomarker measurements of statistical joint modeling on survival time-to-death and determines potential predictors of HIV/AIDS patients on ART in Mekelle General Hospital Ethiopia. Methods A retrospective cohort study was conducted among HIV/AIDS patients who were under ART follow-up during September 11, 2013 - September 5, 2016 at Mekelle General Hospital, Ethiopia. The two repeated biomarkers of longitudinal measurements and survival outcome with separate univaraite longitudinal modeling approach and statistical joint modeling approach were used to fit simultaneously. A total of 216 HIV/AIDS patients were selected by using systematic random sampling technique from ART follow-up. Results The relationship between the two biomarkers CD4 cell and body weight with risk for survival time-to-death were statistical insignificant. Thus, death is less probable to occur in HIV/AIDS patients with higher value of CD4 cell count and body weight progression. In event process the sub-model, Baseline CD4, Fair and Good Adherence, HIV/TB (yes) and Sex (male) were significant factors of risk to short survival Time-to-Death on HIV/AIDS patients. In the 1st longitudinal process sub-model, Baseline CD4, Ambulatory functional status, HIV/TB (yes), Time*Ambulatory functional status, Time*Working functional status and Time*Baseline CD4 were the significant factors of \sqrt{CD4 cell } count progression. Moreover, In 2nd longitudinal process sub-model, visit Time of follow-up, Age, Sex (male), Baseline weight, Time*Ambulatory and Time*Working functional status were the significant factors of log 10(body weight) progression. Conclusion Both governmental and non-governmental stakeholders should pay special attention for HIV positive adults, especially for those who had developed HIV/TB, male, bedridden functional status, poor adherence and lower Baseline CD4 cell count progression so that mortality due to HIV/AIDS optimally reduced.

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Section: Discussionsupporting

confidence: 90%

Section: Discussionsupporting

confidence: 79%

Section: Introductionmentioning

confidence: 99%

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Statistical Joint Modeling on Longitudinal Body Weight and CD4 Cell Progression with Survival Time-to-Death Predictors on HIV/AIDS Patients in Mekelle General Hospital, Ethiopia.

Gebrerufael

Asfaw

Melese

2020

Preprint

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“…So, a better knowledge of determinant factors would allow closer follow-up and more targeted interventions for HIV infected patients, thus reduce excess mortality, alter morbidity and improve quality of life (9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19).…”

mentioning

confidence: 99%

Incidence and determinants of mortality among HIV infected adult patients on antiretroviral therapy in Ethiopia: A systematic review and Meta-analysis

Lijalem¹,

Workie

Suleiman

et al. 2020

Preprint

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Background Antiretroviral therapy has been highly associated with reduction in the incidence of mortality in HIV/AIDS patients over time. However, there is a regional variation in the extent of reducing the incidence of mortality in many developing countries including Ethiopia. Hence, this study was conducted to generate summary evidences-based data for incidence of mortality and determinants of mortality. Methods Articles were comprehensively searched on Pub Med, Google Scholar, Cochrane library, Scopus, and DOAJ databases using Boolean operators. A Dersimonian and Laird methods of random effect model was used to estimate incidence and determinants of mortality. Heterogeneity, publication bias and quality of each study were checked. Subgroup analysis was employed. Relevant data from each study were extracted. STATA software version 14 was used for all statistical analysis. Result A total of 21 articles were finally reviewed and analyzed. Incidence of mortality was found to be 5/100-person year of observation (95% CI: 4–5/100pyo). Most of the death (67%) occurred during the first year of HAART initiation. Baseline Advanced WHO clinical stage (PHR (Pooled Hazard Rate) 2.88; 95%CI: 2.2–3.8), low CD4 cells count (PHR 1.88; 95% CI: 1.5–2.4), low body weight (PHR 1.6; 95% CI: 1.2–2.2), low hemoglobin level (PHR 2.4; 95% CI: 1.7–3.4), presence of TB infection (PHR 2.9; 95% CI: 2.13–4.61), non – working functional status (PHR 3.9; 95% CI: 2.8–5.4), bad medication adherence (PHR 4.8; 95% CI: 3.2–7.2), lack of cotrimoxazole preventive therapy (PHR 1.5; 95% CI: 1.2–2.0), being male (PHR 1.4; 95% CI: 1.2–1.8) and older age (PHR 1.2; 95% CI: 1.04–1.41) were significantly associated with increased mortality in this study. Conclusion Incidence of mortality was high particularly early in the course of therapy. Advanced WHO clinical stage, CD4 cells count low body weight, low hemoglobin level presence of TB infection, bad medication adherence older age and non-working functional status were significant determinants of incidence of mortality. Comprehensive service and strict follow up should be given to avert this high rate of mortality.

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mentioning

confidence: 99%

Incidence and determinants of mortality among HIV infected adult patients on antiretroviral therapy in Ethiopia: A systematic review and Meta-analysis

Workie

Lijalem

Suleiman

et al. 2020

Preprint

View full text Add to dashboard Cite

Background Antiretroviral therapy has been highly associated with reduction in the incidence of mortality in HIV/AIDS patients over time. However, there is a regional variation in the extent of reducing the incidence of mortality in many developing countries including Ethiopia. Hence, this study was conducted to generate summary evidences-based data for incidence of mortality and determinants of mortality. Methods Articles were comprehensively searched on Pub Med, Google Scholar, Cochrane library, Scopus, and DOAJ databases using Boolean operators. A Dersimonian and Laird methods of random effect model was used to estimate incidence and determinants of mortality. Heterogeneity, publication bias and quality of each study were checked. Subgroup analysis was employed. Relevant data from each study were extracted. STATA software version 14 was used for all statistical analysis. ResultA total of 21 articles were finally reviewed and analyzed. Incidence of mortality was found to be 5/100-person year of observation (95% CI: 4 – 5/100pyo). Most of the death (67%) occurred during the first year of HAART initiation. Baseline Advanced WHO clinical stage (PHR (Pooled Hazard Rate) 2.88; 95%CI: 2.2 – 3.8), low CD4 cells count (PHR 1.88; 95% CI: 1.5 – 2.4), low body weight (PHR 1.6; 95% CI: 1.2 – 2.2), low hemoglobin level (PHR 2.4; 95% CI: 1.7 – 3.4), presence of TB infection (PHR 2.9; 95% CI: 2.13 – 4.61), non – working functional status (PHR 3.9; 95% CI: 2.8 – 5.4), bad medication adherence (PHR 4.8; 95% CI: 3.2 – 7.2), lack of cotrimoxazole preventive therapy (PHR 1.5; 95% CI: 1.2 – 2.0), being male (PHR 1.4; 95% CI: 1.2 – 1.8) and older age (PHR 1.2; 95% CI: 1.04 – 1.41) were significantly associated with increased mortality in this study. ConclusionIncidence of mortality was high particularly early in the course of therapy. Advanced WHO clinical stage, CD4 cells count low body weight, low hemoglobin level presence of TB infection, bad medication adherence older age and non-working functional status were significant determinants of incidence of mortality. Comprehensive service and strict follow up should be given to avert this high rate of mortality.

show abstract

Time to death predictors of HIV/AIDS infected patients on antiretroviral therapy in Ethiopia

Cited by 22 publications

References 12 publications

Statistical Joint Modeling on Longitudinal Body Weight and CD4 Cell Progression with Survival Time-to-Death Predictors on HIV/AIDS Patients in Mekelle General Hospital, Ethiopia.

Statistical Joint Modeling on Longitudinal Body Weight and CD4 Cell Progression with Survival Time-to-Death Predictors on HIV/AIDS Patients in Mekelle General Hospital, Ethiopia.

Incidence and determinants of mortality among HIV infected adult patients on antiretroviral therapy in Ethiopia: A systematic review and Meta-analysis

Incidence and determinants of mortality among HIV infected adult patients on antiretroviral therapy in Ethiopia: A systematic review and Meta-analysis

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