生物识别与生物统计学杂志

Statistical Modeling for the Survival of HIV/AIDS Patients Treated with Highly Active Anti-Retroviral Therapy (HAART): A Case Study at Dilchora Hospital, Dire Dawa, Ethiopia

Abstract

Million Wesenu Demissie

The introduction of Highly Active Anti Retro Viral Treatment has brought about a significant reduction in the morbidity and mortality of patients living with HIV/AIDS infection. However, the mortality rate of patients treated with Highly Active Anti Retro Viral Treatment is still high in developing country. The study has reviewed patient forms and follow-up cards of 1437 patients treated with Highly Active Anti Retro Viral Treatment in Dilchora Hospital in Dire Dawa from January, 2010 to December, 2016 G.C and used to identify factors leading to mortality and statistically modeling the survival of patients with HIV/AIDS treated under Highly Active Anti Retro Viral Treatment. Survival of patients was significantly related with gender, functional status, marital status, educational level, WHO clinical stage, place of residence and baseline CD4 cell count. Results of both Cox Proportional Hazard and parametric lognormal regression model revealed that; male, being bedridden, WHO clinical stage-IV, lived in rural residence and patients with lower baseline CD4 count had significantly higher risk of death or shorter survival time than their counterparts. Based on Akaike information criteria (AIC) parametric lognormal regression model best fits the dataset and used to predict survival experience of patients.