Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Apr 4:16:1513898.
doi: 10.3389/fendo.2025.1513898. eCollection 2025.

Association between triglyceride glucose-body mass index and 365-day mortality in patients with critical coronary heart disease

Jing Tian  1 , Yan Dong  1 , Zhongping Xu  1 , Jin Ke  1 , Hongyang Xu  1
Affiliations

Association between triglyceride glucose-body mass index and 365-day mortality in patients with critical coronary heart disease

Jing Tian et al. Front Endocrinol (Lausanne). .

Abstract

Objectives: The aim of this study was to analyze the association between TyG-BMI and 365-day mortality in critically ill patients with CHD.

Methods: Patient data were extracted from the MIMIC-IV database. All patients were categorized into 3 groups based on TyG-BMI index: Low TyG-BMI index group, Medium TyG-BMI index group, and High TyG-BMI index group. Outcomes included primary and secondary outcomes, with the primary outcome being 365-day mortality and the secondary outcomes being hospital survival, intensive care unit (ICU) survival, and 28-day, 90-day, and 180-day mortality. The Kaplan-Meier survival curves were used to compare the outcomes of the three groups. The relationship between TyG-BMI index and 365-day mortality was assessed using multivariate Cox proportional risk regression models and restricted cubic spline curves (RCS).

Results: 889 critically ill patients with CHD were analyzed. Among them, 600 (67.50%) were male patients with a mean age of 68.37 years and 289 (32.50%) were female patients with a mean age of 73.91 years. Patients with a medium TyG-BMI index had the best 365-day prognostic outcome and the highest survival rate compared with patients in the Low and High TyG-BMI index groups [201 (67.68%) vs. 166 (56.08%), 188 (63.51%); P=0.013]. After fully adjusted modeling analysis, the hazard ratio (HR) for 365-day mortality was found to be 0.71 (95% CI 0.54-0.93, P=0.012) for the Medium TyG-BMI index group. Meanwhile, RCS analysis showed an L-shaped relationship between TyG-BMI index and 365-day mortality.

Conclusions: The TyG-BMI index is significantly associated with 365-day mortality in patients with severe CHD.

Keywords: coronary heart disease (CHD); insulin resistance; mortality; prognosis; triglyceride glucose-body mass index (TyG-BMI).

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flowchart of the selection of patients. Quartile 1, Low TyG-BMI index (<235.33) Quartile 2, Medium TyG-BMI index (235.33-294.40) Quartile 3, High TyG-BMI index (>294.40).
Figure 2
Figure 2
Survival rates associated with patients with different TyG-BMI index. (A) In-hospital survival rate of patients with different TyG-BMI index. (B) ICU survival rate of patients with different TyG-BMI index.
Figure 3
Figure 3
Kaplan−Meier survival curves for 28 days mortality in patients with different TyG-BMI index.
Figure 4
Figure 4
Kaplan−Meier survival curves for 90 days mortality in patients with different TyG-BMI index.
Figure 5
Figure 5
Kaplan−Meier survival curves for 180 days mortality in patients with different TyG-BMI index.
Figure 6
Figure 6
Kaplan−Meier survival curves for 365 days mortality in patients with different TyG-BMI index.
Figure 7
Figure 7
Restricted cubic spline curve for the TyG-BMI index hazard ratio.
See this image and copyright information in PMC

Comment in

Similar articles

See all similar articles

Cited by

References

    1. Falk E. Pathogenesis of atherosclerosis. J Am Coll Cardiol. (2006) 47:C7–C12. doi: 10.1016/j.jacc.2005.09.068 - DOI - PubMed
    1. Poznyak AV, Bharadwaj D, Prasad G, Grechko AV, Sazonova MA, Orekhov AN. Renin-angiotensin system in pathogenesis of atherosclerosis and treatment of CVD. Int J Mol Sci. (2021) 22:6702. doi: 10.3390/ijms22136702 - DOI - PMC - PubMed
    1. Cui H, Liu Q, Wu Y, Cao L. Cumulative triglyceride-glucose index is a risk for CVD: a prospective cohort study. Cardiovasc Diabetol. (2022) 21:22. doi: 10.1186/s12933-022-01456-1 - DOI - PMC - PubMed
    1. Zhao D, Liu J, Wang M, Zhang X, Zhou M. Epidemiology of cardiovascular disease in China: current features and implications. Nat Rev Cardiol. (2019) 16:203–12. doi: 10.1038/s41569-018-0119-4 - DOI - PubMed
    1. Vaduganathan M, Mensah GA, Turco JV, Fuster V, Roth GA. Global burden of cardiovascular diseases and risk factors, 1990–2019. J Am Coll Cardiol. (2020) 76:2982–3021. doi: 10.1016/j.jacc.2022.11.005 - DOI - PMC - PubMed

LinkOut - more resources