Prognostic value of combined stratification using TyG index and CD4+ T cell count for 28-day all-cause mortality risk in patients with HIV infection and sepsis: a retrospective cohort study.

BACKGROUND: Sepsis contributes to global mortality due to chronic immunodeficiency and metabolic disturbances, particularly in those infected with the human immunodeficiency virus (HIV). The TyG index and CD4+ T-cell count individually predict sepsis outcomes, but reflect different biological aspects. The benefit of integrating these markers for risk stratification in patients with HIV-associated sepsis remains unclear. This study aimed to assess whether combining the TyG index, a surrogate for insulin resistance, with CD4+ T cell count enhanced early prediction of 28-day mortality risk in adults hospitalized with HIV-associated sepsis.

METHODS: Clinical data were retrospectively collected from patients admitted to the Eighth Affiliated Hospital of Guangzhou Medical University. The participants were stratified into four risk categories according to their TyG index and CD4+ T cell count. The primary outcome was 28-day all-cause mortality, and secondary outcomes were 7-day and in-hospital all-cause mortality. Survival across strata was compared using the Kaplan-Meier analysis and the log-rank test; associations were determined using multivariate Cox proportional hazards models. Independent predictors of death were ranked using the Boruta feature selection algorithm. In a nested sub-cohort of 155 patients, plasma concentrations of 13 inflammatory cytokines were quantified using the LEGENDplex Human Inflammation Panel 1.

RESULTS: Among 1,278 patients with HIV-associated sepsis, 847 had CD4 counts <50 cells/μL. The Kaplan-Meier analysis revealed progressively higher 7-day and 28-day all-cause mortality rates across these strata, with the highest mortality in the low CD4+ and high TyG groups. A multivariable Cox regression analysis, adjusted for multiple covariates, indicated an elevated risk of 28-day mortality in patients with low CD4 and high TyG compared to those with high CD4 and low TyG. Similar trends were observed for 7-day and in-hospital mortality. The Boruta algorithm identified combined TyG-CD4 as an important predictor. The immunological sub-study demonstrated significant differences in cytokine profiles among the risk groups, with the low CD4 and high TyG groups exhibiting a specific inflammatory response.

CONCLUSION: A combined TyG-CD4 assessment provides a rapid and straightforward means of integrating metabolic and immunological insights to identify high-risk individuals early, thereby generating hypotheses for future trials of personalized therapeutic strategies.