ArticleAfrican health sciences2022
Predictors of non-adherence to medication and time to default from treatment on HIV infected patients under HAART: a comparison of joint and separate models.
Article in African health sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Exploring optimal HAART adherence rates in Ethiopian adults: a systematic review and meta-analysis.Frontiers in public health · 2024Pooled it
- Modeling antiretroviral therapy adherence among people living with HIV: a cross-sectional study at Pantang Hospital, Ghana.BMC infectious diseases · 2026Article
- Survival analysis and predictors for hemoglobin level and time-to-default from HIV treatment among first-line female HIV-positive patients within the reproductive age group.Scientific reports · 2025Article
- Predictors associated with time to default for HIV/AIDS patients under HAART at Debre Tabor Referral Hospital: a Cox regression model.Scientific reports · 2025Article
- Sexual reproductive health, NCDs and infectious diseases.African health sciences · 2022Article
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2 authors.
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Abstract
Background: Ethiopia is one of the Sub-Saharan Africa with the highest number of people living with HIV. Amhara region is one of the regions in the country in which many people are under medication. The main objective of this research was to identify significant predictors of non-adherence to medication and time to default from treatment for HIV infected patients under HAART. Methods: A retrospective secondary data were obtained from a random sample of 220 HIV patients under HAART. Separate and joint modeling approaches were conducted in data analysis. Joint modeling was conducted for analysis of non-adherence to medication and the time to default from treatment. In the joint model, a GLMM and Cox PH sub-models were fit together for non-adherence to medication and time to default from treatment. Results: The significant predictors for the variables of interests in current investigation were length of visiting time(AOR of 95% CI=0.866 (0.752, 0.997), female patients(AOR of 95% CI= 0.219 (0.067, 0.717)), patients disclosed the disease(AOR of 95% CI= 0.353 (0.194,0.641)), patients who got social support(AOR of 95% CI= 0.252 (0.194,0.631)), patients living with parter(AOR of 95% CI=0.188 (0.042,0.844)), patients with owner of cell phone(AOR of 95%CI= 0.272 (0.081,0.916)), urban HIV patients(AOR of 94%CI= 0.238 (0.078,0.722)), patients with working functional status(AOR of 95% CI= 0.234 (0.079,0.692)), patients with normal BMI(AOR of 95% CI=0.921 (0.881, 0.963)), patients with high baseline CD4 cell count(AOR of 95% CI=0.873 (0.552, 0.997)). Conclusion: Some groups of HIV patients were non-adherent to medication and defaulted from treatment. Health related education is recommended for non-adherent patients to be adherent for the prescribed medication and live long in the treatment.
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