Predictors of Viral Load and Medication Adherence Among HIV-Positive Adults Under Treatment at Felege-Hiwot Comprehensive Specialized Hospital, North-West, Ethiopia.

BACKGROUND: Maintaining good medication adherence and decreasing viral load in patients living with HIV/AIDS are critical to ensuring antiretroviral therapy's preventive and therapeutic benefits. The main objective of this study was to assess the predictors of viral load and medication adherence among HIV-positive adults under treatment at Felege Hiwot Comprehensive Specialized Hospital (FHCSH).

METHODS: A retrospective cohort study design was conducted from a random sample of 281 adult HIV-infected patients under treatment at FHCSH in northwest Ethiopia from June 2017 to June 2021. Separate GLMM was used in analysis of viral load and medication adherence, and joint mode was applied to fit those two outcomes jointly. The potential correlation of those two outcomes was linked by random intercepts. Information criteria (AIC and BIC) were used for model comparison and covariance structure selection.

RESULTS: The small standard error of significant predictors and significant correlation between viral load and medication adherence over time provide evidence for joint model selection. The correlation between viral load and medication adherence was -0.7688 ( P -value=< 0.05), which indicates that the decrement of viral load tends to increase good medication adherence. Patient substance use, visit time, baseline CD4 cell, baseline hemoglobin, and the interaction of visit time by substance use were significantly associated with viral load and medication adherence jointly.

CONCLUSION: The study revealed that substance user adult patients, patients with low baseline CD4 cells, and patients with low baseline hemoglobin were with high viral loads and poor medication adherence. Therefore, health officials and other concerned bodies should give special attention and high intervention to patients with low baseline hemoglobin; poor adherence and low baseline CD4 cell count.