Abstract
Background/Objectives: This study aimed to investigate the prognostic significance of the triglyceride-glucose index (TGI), triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C) ratio, and inflammatory biomarkers in predicting short-term mortality among intensive care unit (ICU) patients with sepsis. Additionally, this study evaluated whether combining these indices with conventional clinical scores improves prognostic accuracy. Methods: This retrospective cohort study included 600 adult ICU patients diagnosed with sepsis according to Sepsis-3 criteria between January 2020 and April 2025. Clinical, biochemical, and hematological data were collected within the first 24 h of ICU admission. Metabolic indices (TGI, TG/HDL-C) and inflammatory markers (neutrophil-to-lymphocyte ratio [NLR], systemic immune-inflammation index [SII], and pan-immune-inflammation value [PIV]) were analyzed. The primary outcome was 28-day mortality. Receiver operating characteristic (ROC) analyses, Kaplan-Meier survival curves, and a multivariable logistic regression model were applied to determine prognostic performance. Results: Non-survivors exhibited significantly higher levels of TGI, TG/HDL-C, NLR, SII, and PIV compared to survivors (all p < 0.001). In ROC analysis, TGI (AUC = 0.75, 95% CI: 0.71-0.79), TG/HDL-C (AUC = 0.72, 95% CI: 0.68-0.76), and PIV (AUC = 0.78, 95% CI: 0.74-0.82) demonstrated good discriminative power for predicting 28-day mortality. Multivariate logistic regression identified TGI > 8.95 (OR = 1.44, 95% CI: 1.19-1.74, p < 0.001), TG/HDL-C > 3.95 (OR = 1.31, 95% CI: 1.08-1.59, p = 0.005), and PIV > 260 (OR = 1.49, 95% CI: 1.22-1.82, p < 0.001) as independent predictors of mortality. Integrating TGI and PIV with the SOFA score improved prognostic performance (ΔAUC = +0.04). Conclusions: Both TGI and TG/HDL-C are independent predictors of short-term mortality in septic ICU patients, reflecting the contribution of metabolic dysregulation to disease severity. The PIV demonstrated comparable predictive ability to conventional severity scores. Combining metabolic and inflammatory biomarkers with established clinical indices may enhance early risk stratification and guide personalized management strategies in sepsis.