{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T06:21:29Z","timestamp":1783405289629,"version":"3.54.6"},"reference-count":34,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T00:00:00Z","timestamp":1783382400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Cardiovasc. Med."],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study was designed to investigate the dose-response relationship between the triglyceride-glucose (TyG) index and the occurrence of in-hospital major adverse cardiovascular events (MACE) in patients with acute myocardial infarction (AMI), and to examine whether a nonlinear association pattern exists.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This single-center retrospective cohort study consecutively enrolled 1,065 patients diagnosed with type 1 AMI who underwent coronary angiography at the Department of Cardiology, The Second Affiliated Hospital of Shenyang Medical College, between June 2022 and June 2025. Baseline data were collected from the electronic medical record system, and the TyG index was calculated using the formula: TyG\u2009=\u2009Ln [triglycerides (mg\/dL)\u2009\u00d7\u2009fasting plasma glucose (mg\/dL)]\/2. The primary outcome was in-hospital MACE (occurring during hospitalization, \u22647 days after admission), which was a composite of all-cause mortality, acute heart failure, malignant arrhythmia, recurrent myocardial infarction, and cardiogenic shock. Patients were categorized into three groups [T1 [low], T2 [medium], and T3 [high]] based on the overall tertiles of the TyG index. Multivariable logistic regression analysis was employed to construct hierarchical models (a base model, a parsimonious model, and a core model) and to analyze the association between TyG index groups and MACE. Model performance was evaluated by assessing discrimination (area under the curve, AUC), calibration, and clinical utility. Restricted cubic splines (RCS) were used to explore the potential nonlinear relationship between the TyG index (as a continuous variable) and MACE. The inflection point was identified, and piecewise regression analysis was performed. Subgroup analyses were conducted to assess the heterogeneity of the association.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      This study included 1,065 patients with AMI, who were stratified into T1 (low,\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009352), T2 (medium,\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009361), and T3 (high,\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009352) groups based on TyG index tertiles. Baseline analysis revealed significant differences among the three groups in body mass index (BMI), left ventricular ejection fraction (LVEF), age, diastolic blood pressure (DBP), heart rate (HR), fasting plasma glucose (FPG), serum creatinine (Scr), lipid profiles (total cholesterol [TC], triglycerides [TG], high-density lipoprotein cholesterol [HDL-C], low-density lipoprotein cholesterol [LDL-C]), peak cardiac troponin T (cTnT), peak N-terminal pro-B-type natriuretic peptide (NT-proBNP), prevalence of diabetes, and usage rates of angiotensin system inhibitors (ACEI\/ARB\/ARNI) and beta-blockers (all\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&amp;lt;\u20090.05). The overall incidence of in-hospital MACE was 21.13%. Notably, the T2 group exhibited a significantly higher incidence (26.04%) compared to the T1 group (16.76%,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.011). In the core multivariable logistic regression model (adjusted for age, sex, BMI, LVEF, diabetes, cTnT, NT-proBNP, etc.), the T2 group was associated with a 178% significantly increased risk of in-hospital MACE compared to the T1 group [odds ratio [OR]\u2009=\u20092.78, 95% confidence interval [CI]: 1.38\u20135.59,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.004]. The core model incorporating the TyG index groups demonstrated the best predictive performance [area under the receiver operating characteristic curve (AUC)\u2009=\u20090.79, 95% CI: 0.75\u20130.83], good calibration (Hosmer-Lemeshow test\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.883), and was confirmed to provide clinical net benefit by decision curve analysis. Restricted cubic spline analysis revealed a significant J-shaped relationship between the TyG index and the risk of in-hospital MACE, with an inflection point identified at TyG\u2009=\u20099.05. Piecewise regression analysis demonstrated that when the TyG index was &amp;lt;9.05, the MACE risk did not change significantly (OR\u2009=\u20091.04, 95% CI: 0.62\u20131.77,\n                      <jats:italic>P<\/jats:italic>\n                      \u2009=\u20090.875); however, for every 1-unit increase in the TyG index\u2009\u2265\u20099.05, the MACE risk significantly increased by 124% (OR\u2009=\u20092.24, 95% CI: 1.26\u20133.96,\n                      <jats:italic>P<\/jats:italic>\n                      \u2009=\u20090.006). Subgroup analyses (stratified by sex, smoking status, hypertension, diabetes, age, and BMI) revealed no significant heterogeneity in the association between the TyG index (\u2265inflection point vs. &amp;lt;inflection point) and MACE risk (all\n                      <jats:italic>p<\/jats:italic>\n                      for interaction\u2009&amp;gt;\u20090.05), supporting the consistency of this J-shaped association across the studied population subgroups.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This study demonstrates a significant J-shaped nonlinear association between the TyG index and the risk of in-hospital MACE, with an identified inflection point at 9.05. Notably, patients with a medium TyG level (T2 group) exhibited the highest MACE risk, which was significantly greater than that of patients with a low TyG level (T1 group). This finding challenges the conventional linear perception that a higher TyG index consistently correlates with greater risk. The core model incorporating TyG index stratification significantly improved the predictive performance for MACE. These findings collectively underscore the importance of considering the nonlinear effect of the TyG index in risk assessment for AMI patients, suggesting that individuals with medium TyG levels may represent a specific high-risk subgroup warranting particular attention.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fcvm.2026.1830398","type":"journal-article","created":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T05:48:35Z","timestamp":1783403315000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Unveiling a J-shaped association between the triglyceride-glucose index and in-hospital major adverse cardiovascular events in patients with acute myocardial infarction: a retrospective cohort study of 1,065 patients"],"prefix":"10.3389","volume":"13","author":[{"given":"Yikang","family":"Xu","sequence":"first","affiliation":[{"name":"Department of Cardiovascular Medicine, The Second Affiliated Hospital of Shenyang Medical College","place":["Shenyang, Liaoning Province, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jia","family":"Liu","sequence":"additional","affiliation":[{"name":"Geriatric Medical Center, Shenyang Fourth People\u2019s Hospital","place":["Shenyang, Liaoning Province, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Medicine, The Second Affiliated Hospital of Shenyang Medical College","place":["Shenyang, Liaoning Province, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Limin","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Medicine, The Second Affiliated Hospital of Shenyang Medical College","place":["Shenyang, Liaoning Province, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingru","family":"Ma","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Medicine, The Second Affiliated Hospital of Shenyang Medical College","place":["Shenyang, Liaoning Province, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiren","family":"Meng","sequence":"additional","affiliation":[{"name":"School of Public Health, Shenyang Medical College","place":["Shenyang, Liaoning Province, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuochao","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Public Health, Shenyang Medical College","place":["Shenyang, Liaoning Province, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yaxin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Public Health, Shenyang Medical College","place":["Shenyang, Liaoning Province, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lisheng","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Northeastern University","place":["Shenyang, Liaoning Province, China"]},{"name":"Key Laboratory of Medical Image Computing, Ministry of Education","place":["Shenyang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen E.","family":"Greenwald","sequence":"additional","affiliation":[{"name":"Blizard Institute, Barts & The London School of Medicine & Dentistry, Queen Mary University of London , London","place":["United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,7,7]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"e9","DOI":"10.1161\/CIR.0000000000001168","article-title":"2023 AHA\/ACC\/ACCP\/ASPC\/NLA\/PCNA guideline for the management of patients with chronic coronary disease: a report of the American Heart Association\/American College of Cardiology joint committee on clinical practice guidelines","volume":"148","author":"Virani","year":"2023","journal-title":"Circulation"},{"key":"B2","doi-asserted-by":"publisher","first-page":"e9349","DOI":"10.7759\/cureus.9349","article-title":"Global epidemiology of ischemic heart disease: results from the global burden of disease study","volume":"12","author":"Khan","year":"2020","journal-title":"Cureus"},{"key":"B3","doi-asserted-by":"publisher","first-page":"521","DOI":"10.3969\/j.issn.1000-3614.2025.06.001","article-title":"Summary of the China cardiovascular health and disease report 2024","volume":"40","year":"2025","journal-title":"Chin Circ J"},{"key":"B4","doi-asserted-by":"publisher","first-page":"e004425","DOI":"10.1136\/bmjopen-2013-004425","article-title":"Should patients with acute coronary disease be stratified for management according to their risk? 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