Abstract
Ethiopia has the highest proportion of the HIV population receiving ART of any African country. The objective of this study was to identify 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. Secondary data source conducted at the University of Gondar Comprehensive Specialized Hospital from September 2015 to March 2022. In this study, the generalized linear mixed model and the Cox PHs model were jointly used to get a wide range of information about female HIV data. The mean (standard deviation) of white blood cells and red blood cells was 6.11 (1.8) and 4.02 (1.26), respectively. Out of 201 study participants, 27.9% defaulted from treatment, and the remaining were considered censored. In this study, the association parameter (gamma_1) for hemoglobin level and default from HIV treatment is negative and statistically significant ([Formula: see text]) at the 5% level of significance. These findings suggested that the patient's association parameter had an inverse link with hemoglobin and treatment default. The result of the study also shows low red blood cell and white blood cells lead to low hemoglobin levels and a high hazard of defaulting. Likewise, patients under the categories of World Health Organization (WHO) clinical stage III and IV, ambulatory, bedridden, primary education, Opportunistic Infections (OIs), and substance abuse were at high hazard of being defaulters. Conversely, secondary and tertiary education and patients expressing diseases status to family members were low hazards for defaulters. In addition, WHO clinical stage III and IV patients, bedridden patients, primary educators, OIs, and substance abusers had low hemoglobin level concentrations, and tertiary education and disclosing the diseases to family members were high hemoglobin level concentrations. Healthcare workers in similar settings should pay more attention to clients related to hemoglobin levels and time to default from medication based on these important factors.