Association of the triglyceride glucose-body mass index with the extent of coronary artery disease in patients with acute coronary syndromes

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Abstract

Background

Studies have shown that insulin resistance is strongly associated with the development of cardiovascular disease, and the triglyceride glucose-body mass index (TyG-BMI index) is considered to be a reliable surrogate marker of insulin resistance. There are limited studies on the relationship between TyG-BMI index and the extent of coronary artery disease in patients with acute coronary syndrome (ACS). This study aimed to investigate the relationship between TyG-BMI index and the extent of coronary artery disease in patients with ACS.

Methods

Overall, 2,317 patients with ACS who underwent percutaneous coronary intervention at the Affiliated Hospital of Zunyi Medical University were included in this study. The TyG-BMI index was grouped according to the tertile method. The extent of coronary artery disease in patients with ACS was quantitatively assessed using the SYNTAX score, which was categorised as low (≤ 22), intermediate (23–32), and high risk (≥ 33).

Results

In the overall population, multivariate logistic regression analyses showed that TyG-BMI index was associated with mid/high SYNTAX score in patients with ACS (odds ratio [OR] = 1.0041; 95% confidence interval [CI] = 1.0000–1.0079; p = 0.0310). Subgroup analyses showed that TyG-BMI index was an independent risk factor for mid/high SYNTAX score in female ACS patients after adjusting for multiple confounders (OR = 1.0100; 95% CI = 1.0000–1.0200; p = 0.0050), and that the risk of mid/high SYNTAX score was 2.49 times higher in the T3 group (OR = 2.4900; 95% CI = 1.2200–5.0600; p = 0.0120). Restricted cubic spline analysis showed a linear correlation between TyG-BMI index and complex coronary artery disease (SYNTAX score > 22) in women with ACS. In female ACS patients, inclusion of the TyG-BMI index did not improve the predictive power of the underlying risk model (net reclassification improvement: 0.0867 [-0.0256–0.1989], p = 0.1301; integrated discrimination improvement: 0.0183 [0.0038–0.0329], p = 0.0135).

Conclusions

TyG-BMI index is linearly associated with the degree of complex coronary artery disease in female ACS patients. However, the inclusion of the TyG-BMI index did not improve the predictive power of the underlying risk model for female ACS patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-024-02124-2.

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Most cited references 42

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Heart Disease and Stroke Statistics—2022 Update: A Report From the American Heart Association

Connie Tsao, Aaron Aday, Zaid I Almarzooq … (2022)

Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). Methods: The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year’s worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year’s edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy. Results: Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. Conclusions: The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

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Use and abuse of HOMA modeling.

T Wallace, J Levy, D. Matthews (2004)

Homeostatic model assessment (HOMA) is a method for assessing beta-cell function and insulin resistance (IR) from basal (fasting) glucose and insulin or C-peptide concentrations. It has been reported in >500 publications, 20 times more frequently for the estimation of IR than beta-cell function. This article summarizes the physiological basis of HOMA, a structural model of steady-state insulin and glucose domains, constructed from physiological dose responses of glucose uptake and insulin production. Hepatic and peripheral glucose efflux and uptake were modeled to be dependent on plasma glucose and insulin concentrations. Decreases in beta-cell function were modeled by changing the beta-cell response to plasma glucose concentrations. The original HOMA model was described in 1985 with a formula for approximate estimation. The computer model is available but has not been as widely used as the approximation formulae. HOMA has been validated against a variety of physiological methods. We review the use and reporting of HOMA in the literature and give guidance on its appropriate use (e.g., cohort and epidemiological studies) and inappropriate use (e.g., measuring beta-cell function in isolation). The HOMA model compares favorably with other models and has the advantage of requiring only a single plasma sample assayed for insulin and glucose. In conclusion, the HOMA model has become a widely used clinical and epidemiological tool and, when used appropriately, it can yield valuable data. However, as with all models, the primary input data need to be robust, and the data need to be interpreted carefully.

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A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group.

A S Levey, J Bosch, J. B. Lewis … (1999)

Serum creatinine concentration is widely used as an index of renal function, but this concentration is affected by factors other than glomerular filtration rate (GFR). To develop an equation to predict GFR from serum creatinine concentration and other factors. Cross-sectional study of GFR, creatinine clearance, serum creatinine concentration, and demographic and clinical characteristics in patients with chronic renal disease. 1628 patients enrolled in the baseline period of the Modification of Diet in Renal Disease (MDRD) Study, of whom 1070 were randomly selected as the training sample; the remaining 558 patients constituted the validation sample. The prediction equation was developed by stepwise regression applied to the training sample. The equation was then tested and compared with other prediction equations in the validation sample. To simplify prediction of GFR, the equation included only demographic and serum variables. Independent factors associated with a lower GFR included a higher serum creatinine concentration, older age, female sex, nonblack ethnicity, higher serum urea nitrogen levels, and lower serum albumin levels (P < 0.001 for all factors). The multiple regression model explained 90.3% of the variance in the logarithm of GFR in the validation sample. Measured creatinine clearance overestimated GFR by 19%, and creatinine clearance predicted by the Cockcroft-Gault formula overestimated GFR by 16%. After adjustment for this overestimation, the percentage of variance of the logarithm of GFR predicted by measured creatinine clearance or the Cockcroft-Gault formula was 86.6% and 84.2%, respectively. The equation developed from the MDRD Study provided a more accurate estimate of GFR in our study group than measured creatinine clearance or other commonly used equations.

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Author and article information

Contributors

Yi Ma: mayimayizmc@126.com

Journal

Journal ID (nlm-ta): Cardiovasc Diabetol

Journal ID (iso-abbrev): Cardiovasc Diabetol

Title: Cardiovascular Diabetology

Publisher: BioMed Central (London )

ISSN (Electronic): 1475-2840

Publication date (Electronic): 13 January 2024

Publication date PMC-release: 13 January 2024

Publication date Collection: 2024

Volume: 23

Electronic Location Identifier: 24

Affiliations

Department of Cardiovascular Medicine, Affiliated Hospital of Zunyi Medical University, ( https://ror.org/00g5b0g93) No. 149 Dalian Road, Zunyi, Guizhou 563099 China

Article

Publisher ID: 2124

DOI: 10.1186/s12933-024-02124-2

PMC ID: 10790264

PubMed ID: 38218893

SO-VID: b260187a-ceb5-4772-a8f3-978c0fd1ec28

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 15 November 2023

Date accepted : 5 January 2024

Funding

Funded by: Biomedical Joint Funding of Guizhou Provincial Science and Technology Department

Award ID: No. Qiankehe LH Zi [2017] 7109

Custom metadata

ScienceOpen disciplines: Endocrinology & Diabetes

Keywords: acute coronary syndrome,triglyceride glucose-body mass index,cardiovascular disease,insulin resistance,syntax score

Data availability:

ScienceOpen disciplines: Endocrinology & Diabetes

Keywords: acute coronary syndrome, triglyceride glucose-body mass index, cardiovascular disease, insulin resistance, syntax score

Association of the triglyceride glucose-body mass index with the extent of coronary artery disease in patients with acute coronary syndromes

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Abstract

Background

Methods

Results

Conclusions

Supplementary Information

Related collections

Journal of the ASEAN Federation of Endocrine Societies

Most cited references 42

Heart Disease and Stroke Statistics—2022 Update: A Report From the American Heart Association

Use and abuse of HOMA modeling.

A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group.

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