Abstract
Background: South Africa has the biggest HIV epidemic in the world, with Mpumalanga province in which Albert Luthuli municipality is located having the second highest HIV prevalence rate after KwaZulu-Natal province. The objective of the study was to identify the factors that affect the survival lifetime of HIV+ terminal patients in rural district hospitals of Albert Luthuli municipality.Methods: This is a typical retrospective cohort longitudinal design study whereby cohort of HIV+ terminal patients was retrospectively followed from 2010 to 2017 until a patient died, transferred to another hospital, lost to follow-up or was still alive at the end of the observation period. The follow-up time for each patient started at the time the patient got initiated to the ART programme at the hospital’s wellness centre. Nonparametric survival analysis and semiparametric survival analysis methods were used to analyse the data.Results: Through Cox proportional hazards regression modelling, it was found that ART adherence (poor, fair, good), Age, Follow-up mass, Baseline sodium, Baseline viral load, Follow CD4 count by Treatment (Regimen 1) interaction and Follow-up lymphocyte by TB history (yes, no) interaction had significant effects on survival lifetime of HIV+ terminal patients (p-values < 0.1). Furthermore, through quantile regression modelling, it was found that short, medium and long survival times of HIV+ patients, respectively represented by the 0.1, 0.5 and 0.9 quantiles, were not necessarily significantly affected by the same factors.Discussion: The Cox PH modelling and the quantile regression analysis complemented each other in answering the research question. However, although the Cox PH modelling was the main approach in this study, the quantile regression analysis results are more informative than the Cox PH modelling results.Conclusion: The study identified and modelled the factors affecting the survival of HIV+ terminal patients in Albert Luthuli Municipality by using Logistic regression, Cox PH regression, and Quantile regression modelling. . Cox regression modelled the factors affecting the survival lifetime of HIV+ terminal patients as: ART adherence, Age, Follow-up mass, Baseline sodium, Baseline viral load and interactions of Follow-up lymphocyte by TB history and Follow-up CD4 by Treatment (Regimen 1).