# Triglyceride-glucose index at ICU admission predicts hospital mortality in patients with acute coronary syndrome concomitant sepsis: a Bayesian network analysis of retrospective multicenter cohort study

## TL;DR

A higher Triglyceride-Glucose (TyG) index at ICU admission is linked to increased hospital mortality in patients with acute coronary syndrome and sepsis.

## Contribution

This study is the first to show the TyG index's independent predictive value and causal metabolic pathways in patients with concurrent ACS and sepsis.

## Key findings

- Hospital mortality increased significantly with higher TyG tertiles (54.5% to 73.1%).
- Each unit increase in the TyG index was independently associated with a 59% higher mortality risk.
- Bayesian networks identified age-related pathways (triglycerides and diabetes) and a direct link from TyG to mortality.

## Abstract

Critically ill patients with acute coronary syndrome (ACS) concomitant sepsis are at markedly increased risk of mortality. The Triglyceride-Glucose (TyG) index, a simple surrogate marker of insulin resistance, although its predictive in separate cardiovascular or septic cohorts, its prognostic utility and potential mechanistic pathways in the high-risk setting of concurrent ACS concomitant sepsis remain unknown. This study aimed to evaluate the association between the TyG index at ICU admission and hospital mortality in this population and to elucidate underlying metabolic pathways using Bayesian network analysis.

In a multicenter retrospective cohort of 200 critically ill adults with ACS concomitant sepsis (2013–2023), the TyG index was calculated at ICU admission and stratified into tertiles (T1: <8.81; T2: 8.81–9.45; T3: >9.45). The primary outcome was in-hospital mortality. Multivariable logistic regression and restricted cubic splines were used to assess the independent relationship between the TyG index and mortality. A Bayesian network (BN) model was constructed to infer causal interactions among metabolic variables, the TyG index and mortality.

Overall hospital mortality was 61.0% and increased significantly across TyG tertiles (T1: 54.5%; T2: 55.2%; T3: 73.1%; p = 0.044). After adjustment for confounders including age and peak procalcitonin, each unit increase in the TyG index was independently associated with higher mortality (adjusted odds ratio = 1.59; 95% confidence interval: 1.06–2.38; p = 0.026). A linear dose–response relationship was observed (p for nonlinearity = 0.549). The Bayesian network identified two primary metabolic pathways influencing TyG: Age→Triglycerides→TyG and Age→Diabetes→TyG. Importantly, a direct causal link from the TyG index to mortality (TyG → Mortality) was established. Setting the TyG index to its highest tertile alone predicted a mortality probability of 69.5%, with upstream metabolic factors providing minimal incremental prognostic value.

In critically ill patients with ACS concomitant sepsis, a higher TyG index at ICU admission, reflecting insulin resistance and metabolic dysfunction, is a strong and independent predictor of hospital mortality. It occupies a central position linking age-related metabolic deterioration to fatal outcomes. Incorporation of the TyG index into early risk stratification may help identify patients who could benefit from intensified metabolic monitoring and tailored nutritional therapeutic strategies.

Study design involves a multicenter retrospective cohort focusing on ICU mortality. The study includes 200 critically ill patients with ACS and sepsis, mean age 68.1, 79% male. The TyG Index stratification shows mortality trends and risk associations, with a causal pathway involving age, triglycerides, and diabetes affecting mortality. Statistical analysis uses multivariate logistic regression and Bayesian networks. Conclusion emphasizes the TyG Index as a predictor of hospital mortality, aiding in early risk stratification and management strategies.