Joint Model for Cd4 Count Measurements and Time-to-First Occurrence of Hospitalization and Death Among Hiv And Tuberculosis Pericarditis Patients

Abstract

This study investigated the effects of Mycobacterium immunotherapy (M.w) and timevarying CD4 counts on survival outcomes, specifically the time to first hospitalization and death, in patients with HIV and tuberculosis (TB) pericarditis. Joint modeling techniques were used to integrate longitudinal CD4 measurements and survival data, adjusting for factors like age, gender, and antiretroviral therapy (ART) status. The analysis was conducted using linear mixed effects models and the Cox proportional hazards model, and the best model was selected based on performance criteria. The results showed that M.w treatment did not significantly impact the risk of death with a hazard ratio (HR = 0.404) or hospitalization (HR = 0.014) compared to placebo. However, a one-unit increase in CD4 count was associated with a 2% reduction in the risk of death and hospitalization. Older patients (46+ years) had a higher risk of death (HR = 7.510), while ART use with (HR = 0.169) and heart rates above 100 beats per minute (HR = 0.064) were associated with reduced mortality risk. In conclusion, M.w treatment had no significant effect on survival outcomes, but higher CD4 counts, ART use, and heart rate were key predictors of reduced death risk. Keywords: Joint modeling, CD4 count, HIV, Tuberculosis pericarditis, Survival analysis, Mycobacterium indicus pranii Key implications for stakeholders: Results suggest integrating serial immunological markers (CD4 trends) into patient risk stratification and highlight the need for cautious evaluation of adjunctive immunotherapy (M.w). Dedication