Evidence map›Paper›PMID 42856666›Full record

ArticleFrontiers in cardiovascular medicine2026

Triglyceride-glucose index trajectories and in-hospital mortality in heart failure: a retrospective cohort study.

Zongjun Hu, Xiangjun Kong, Quanwei Liu, Jianguo Chen, Xia Huang

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Article in Frontiers in cardiovascular medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 authors.

Zongjun Hu *Department of Critical Care Medicine, Chongqing University Three Gorges Hospital, Chongqing, China.
Xiangjun Kong *Department of Cardiology, The Second People's Hospital of Neijiang, Affiliated Neijiang Hospital of Southwest Medical University, Neijiang, China.
Quanwei Liu *Department of Cardiology, The Second People's Hospital of Neijiang, Affiliated Neijiang Hospital of Southwest Medical University, Neijiang, China.
Jianguo ChenDepartment of Critical Care Medicine, Chongqing University Three Gorges Hospital, Chongqing, China.
Xia HuangDepartment of Critical Care Medicine, Chongqing University Three Gorges Hospital, Chongqing, China.

Funding

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6 · The paper itself

Abstract

Background: High triglyceride-glucose (TyG) index levels are linked to poor prognosis in the heart failure (HF) population. However, existing studies have predominantly relied on static baseline measurements, and the association of dynamic TyG trajectories with outcomes in critically ill HF patients remains unclear. This study aimed to identify TyG index trajectories in critically ill patients with HF and evaluate their association with in-hospital mortality. Methods: This retrospective study used the MIMIC-IV (v3.1) as the derivation cohort and the eICU-CRD (v2.0) as the external validation cohort. Patients with HF admitted to the intensive care unit (ICU) were included. We applied group-based trajectory modeling (GBTM) to identify distinct TyG index trajectories during the first 7 days of ICU admission. Multivariable logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between TyG trajectories and in-hospital mortality. Complete-case analysis, Cox regression, and E-value calculation were conducted as sensitivity analyses. Results: This analysis included 2,180 patients from MIMIC-IV and 1,433 from eICU-CRD. GBTM identified three distinct TyG trajectories: Class 1 (low-level), Class 2 (moderate-level), and Class 3 (high-level). The high-level trajectory (Class 3) exhibited the highest in-hospital mortality in both cohorts. After full adjustment, Class 3 was associated with significantly increased mortality compared with Class 1 (MIMIC-IV: OR = 1.62, 95% CI: 1.13-2.31; eICU-CRD: OR = 2.73, 95% CI: 1.59-4.67). Class 2 showed a weaker and non-significant association (MIMIC-IV: OR = 1.17, 95% CI: 0.87-1.58; eICU-CRD: OR = 1.45, 95% CI: 0.97-2.17). Sensitivity analyses showed generally consistent trends. Conclusion: In critically ill patients with HF, a high-level TyG trajectory

Indexed as

heart failurein-hospital mortalityintensive care unittrajectoriestriglyceride-glucose index

Identifiers

PMID42856666
PMCPMC13649691

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