Association of Triglyceride-to-HDL-C Ratio, Triglyceride–Glucose Index, and Inflammatory Biomarkers with Mortality in Intensive Care Unit Patients with Sepsis

<b>Background/Objectives</b>: 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. <b>Methods</b>: 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. <b>Results</b>: Non-survivors exhibited significantly higher levels of TGI, TG/HDL-C, NLR, SII, and PIV compared to survivors (all <i>p</i> < 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, <i>p</i> < 0.001), TG/HDL-C > 3.95 (OR = 1.31, 95% CI: 1.08-1.59, <i>p</i> = 0.005), and PIV > 260 (OR = 1.49, 95% CI: 1.22-1.82, <i>p</i> < 0.001) as independent predictors of mortality. Integrating TGI and PIV with the SOFA score improved prognostic performance (ΔAUC = +0.04). <b>Conclusions</b>: 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.

Authors

Institutions

Publication Details

Journal
Diagnostics
Published
2026-03-12
DOI
https://doi.org/10.3390/diagnostics16060844
Primary Topic
Sepsis Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Association of Triglyceride-to-HDL-C Ratio, Triglyceride–Glucose Index, and Inflammatory Biomarkers with Mortality in Intensive Care Unit Patients with Sepsis

Mesher Ensarioğlu, Cihan Döğer, Nazan Has Selmi, Semih Aydemir et al.
Diagnostics
Sepsis Diagnosis and Treatment
article

Association of Triglyceride-to-HDL-C Ratio, Triglyceride–Glucose Index, and Inflammatory Biomarkers with Mortality in Intensive Care Unit Patients with Sepsis

Mesher Ensarioğlu, Cihan Döğer, Nazan Has Selmi, Semih Aydemir, İbrahim Ertaş, Yavuz Kutay Gökçe, Gökçen Terzi, Nilgün Şahin
article en

Abstract

<b>Background/Objectives</b>: 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. <b>Methods</b>: 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. <b>Results</b>: Non-survivors exhibited significantly higher levels of TGI, TG/HDL-C, NLR, SII, and PIV compared to survivors (all <i>p</i> < 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, <i>p</i> < 0.001), TG/HDL-C > 3.95 (OR = 1.31, 95% CI: 1.08-1.59, <i>p</i> = 0.005), and PIV > 260 (OR = 1.49, 95% CI: 1.22-1.82, <i>p</i> < 0.001) as independent predictors of mortality. Integrating TGI and PIV with the SOFA score improved prognostic performance (ΔAUC = +0.04). <b>Conclusions</b>: 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.

DiagnosticsVol. 16(6)
Güven Hospital (TR), Sağlık Bilimleri Üniversitesi (TR), Türk Anesteziyoloji ve Reanimasyon Derneği (TR), University of Health Sciences Antigua (AG)
Reduced inequalities
Openalex Percentile: Top 26%
Sepsis Diagnosis and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.