Incidence and predictors of attrition among human immunodeficiency virus infected children on antiretroviral therapy in Amhara comprehensive specialized hospitals, Northwest Ethiopia, 2022: a retrospective cohort study

Abstract

AbstractAttrition rate is higher in developing nations and it leftovers a major obstacle to enhance the benefits of therapy and achieve the 90–90–90 plan targets. Despite this fact, data on the incidence and its predictors of attrition among human immune deficiency virus infected children on antiretroviral therapy are limited in developing countries including Ethiopia especially after the test and treat strategy implemented. This study aimed to assess the incidence and predictors of attrition among human immune deficiency virus infected children on antiretroviral therapy in Amhara Comprehensive Specialized Hospitals, Northwest Ethiopia. A retrospective follow-up study was conducted among 359 children on ART from June 14, 2014, to June 14, 2022. Study participants were selected using simple random sampling method and the data were collected using Kobo Toolbox software and analysis was done by STATA version 14. Both bi-variable and multivariable Cox regression models were fitted to ascertain predictors. Lastly, an AHR with a 95% CI was computed and variables with a p-value of < 0.05 were took an account statistically key predictors of attrition. The overall incidence of attrition rate was 9.8 (95% CI 7.9, 11.9) per 100 PYO. Children having baseline hemoglobin < 10 mg/dl (AHR 3.94; 95% CI 2.32, 6.7), suboptimal adherence (AHR 1.96; 95% CI 1.23, 3.13), baseline opportunistic infection (AHR 1.8; 95% CI 1.17, 2.96), and children who had experienced drug side effects (AHR 8.3; 95% CI 4.93, 13.84) were established to be a significant predictors of attrition. The attrition rate was relatively high. Decreased hemoglobin, suboptimal adherence, presence of drug side effects and baseline opportunistic infection were predictors of attrition. Therefore, it is crucial to detect and give special emphasis to those identified predictors promptly.