Joint clinical and socio-demographic determinants of CD4 cell count and body weight in HIV/TB co-infected adult patients on HAART

Abstract

Background: Tuberculosis is one of the most lethal communicable diseases in the world. In tuberculosis patients, HIV speeds up the course of the infection from latent to active illness. This study aimed to identify joint clinical and socio demographic determinant factors of CD4+ cell count and body weight in HIV/TB co-infected adult patients. Methods: From January 2013 to December 2019, 374 HIV/TB co-infected individuals were treated and had follow-ups. This study used descriptive data analysis, a linear mixed effects model for longitudinal data, and joint modeling of the two longitudinal outcome variables. Results: In this study, 51.1% of the 374 HIV-TB co-infected patients were women, 47.1% were rural dwellers, and 71.9% developed extra pulmonary TB. Females made up 54.3% of all patients who died. To detect the presence of correlation among repeated measured data, the AR (1) structure was chosen. The joint model was more appropriate for analysing and interpreting current data. Conclusions: Baseline age, follow-up time, baseline weight, place of residence, adherence level, educational background, functional status, WHO clinical stage, smoking status and type of TB developed were identified as significant joint factors in CD4 cell count and weight of HIV/TB co-infected patients from potential joint predictor variables. Therefore, the concerned bodies, specifically the FMOH and regional health staffs, should enhance public awareness about the factors that lead to a drop in CD4 count and weight gain, as well as an increased risk of death from HIV/TB co-infection. Furthermore, special attention should be paid to women and patients with poor adherence. Medication and treatment must be affordable and accessible to all co-infected patients in order to maximize their CD4 count and proportional body weight to their height, and to lengthen the lives of individuals who are co-infected.

Keywords

• CD4 cell count
• HIV/TB co-infection
• Joint modeling
• Linear mixed model
• Weight