Triglyceride‐Glucose Index‐Based Nomogram for Predicting Short‐Term Mortality in Sepsis Patients

The triglyceride-glucose (TyG) index, a marker of insulin resistance, is associated with outcomes in critical illness; however, its predictive role for 28-day mortality in Asian patients with sepsis has not been established. To address this, the current investigation was designed to evaluate its prognostic significance and to construct a risk prediction model for short-term mortality. This retrospective study analyzed sepsis patients admitted to the intensive care unit (ICU) of the Second Hospital of Lanzhou University from January 1, 2018 to December 31, 2023. Participants were randomly split into training/validation cohorts (7:3 ratio). Multivariate logistic regression identified independent predictors. A nomogram was constructed by these predictors and it was validated using ROC curves (ROC), calibration plots, and decision curve analysis (DCA). A nomogram integrating seven variables-age, respiratory failure within 48 h, multiple organ dysfunction syndrome (MODS) within 48 h, international normalized ratio (INR), lactate level, prognostic nutrition index (PNI), and TyG index-predicted 28-day mortality with AUCs of 0.855 (training, 95% CI: 0.818-0.891) and 0.826 (validation, 95% CI: 0.764-0.887), outperforming SOFA and APACHE II scores. Calibration curves confirmed alignment with actual outcomes, and DCA demonstrated broad clinical utility. The TyG index is an independent predictor of 28-day sepsis mortality. The validated nomogram based on the TyG index enhances risk stratification, aiding clinicians in early decision-making to improve patient outcomes and care quality.

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Publication Details

Journal
The Kaohsiung Journal of Medical Sciences
Published
2026-04-02
DOI
https://doi.org/10.1002/kjm2.70199
Primary Topic
Sepsis Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00

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article

Triglyceride‐Glucose Index‐Based Nomogram for Predicting Short‐Term Mortality in Sepsis Patients

Yujing Jiang, Tong‐Qin Li, Jing Zhang, Li Ma
The Kaohsiung Journal of Medical Sciences
Sepsis Diagnosis and Treatment
article

Triglyceride‐Glucose Index‐Based Nomogram for Predicting Short‐Term Mortality in Sepsis Patients

Yujing Jiang, Tong‐Qin Li, Jing Zhang, Li Ma
article en

Abstract

The triglyceride-glucose (TyG) index, a marker of insulin resistance, is associated with outcomes in critical illness; however, its predictive role for 28-day mortality in Asian patients with sepsis has not been established. To address this, the current investigation was designed to evaluate its prognostic significance and to construct a risk prediction model for short-term mortality. This retrospective study analyzed sepsis patients admitted to the intensive care unit (ICU) of the Second Hospital of Lanzhou University from January 1, 2018 to December 31, 2023. Participants were randomly split into training/validation cohorts (7:3 ratio). Multivariate logistic regression identified independent predictors. A nomogram was constructed by these predictors and it was validated using ROC curves (ROC), calibration plots, and decision curve analysis (DCA). A nomogram integrating seven variables-age, respiratory failure within 48 h, multiple organ dysfunction syndrome (MODS) within 48 h, international normalized ratio (INR), lactate level, prognostic nutrition index (PNI), and TyG index-predicted 28-day mortality with AUCs of 0.855 (training, 95% CI: 0.818-0.891) and 0.826 (validation, 95% CI: 0.764-0.887), outperforming SOFA and APACHE II scores. Calibration curves confirmed alignment with actual outcomes, and DCA demonstrated broad clinical utility. The TyG index is an independent predictor of 28-day sepsis mortality. The validated nomogram based on the TyG index enhances risk stratification, aiding clinicians in early decision-making to improve patient outcomes and care quality.

The Kaohsiung Journal of Medical Sciences
Lanzhou University Second Hospital (CN), Lanzhou University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 22%
Sepsis Diagnosis and Treatment
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