ORIGINAL RESEARCH article
Front. Cardiovasc. Med.
Sec. Intensive Care Cardiovascular Medicine
Volume 12 - 2025 | doi: 10.3389/fcvm.2025.1620664
This article is part of the Research TopicThe Role of Environmental and Metabolic Factors in Global Cardiovascular HealthView all 6 articles
Development and validation of a triglyceride-glucose integrated nomogram for acute kidney injury prediction in acute myocardial infarction patients: A multicenter database study
Provisionally accepted
- Jining NO.1 people's hospital, JiNing, China
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Background: Acute kidney injury (AKI) is a life-threatening complication in patients with acute myocardial infarction (AMI), leading to increased morbidity and mortality. Early prediction of highrisk patients remains a clinical challenge. Methods: We developed and validated a predictive model for AKI using data from two large critical care databases: MIMIC-IV (n = 1,227) and eICU (n = 1,954). Least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression were applied to identify independent predictors. A nomogram was constructed incorporating the triglyceride-glucose (TyG) index and clinical variables. Results: Seven predictors were included in the final model: TyG index, blood urea nitrogen (BUN), SOFA score, age, serum sodium, serum albumin and systolic blood pressure (SBP). The model demonstrated excellent discrimination with area under the curve (AUC) values of 0.85 in the training cohort, 0.83 in the internal validation cohort and 0.81 in the external validation cohort. Decision curve analysis showed clinical usefulness across a wide range of risk thresholds (22%-45%). The TyG index was independently associated with increased AKI risk (odds ratio 1.31; 95% CI: 1.07-1.60). The model also showed improved risk reclassification (net reclassification index: 0.22; p < 0.001). Conclusion: The TyG-based nomogram provides a practical and accurate tool for early prediction of AKI in AMI patients. By integrating metabolic, hemodynamic, and organ dysfunction markers, this model enables multidimensional risk stratification and may support timely preventive strategies in the ICU setting. 1 Introduction 2 Despite significant advancements in pharmacological and interventional therapies over the past decades, acute myocardial infarction (AMI) remains a leading cause of morbidity and mortality worldwide(1). Acute kidney injury (AKI) is a common and serious complication in patients with acute myocardial infarction (AMI) , with an incidence reaching 59% in hospitalized patients(2). The
Keywords: Triglyceride-glucose index, acute myocardial infarction, Acute Kidney Injury, nomogram, Insulin Resistance
Received: 30 Apr 2025; Accepted: 18 Aug 2025.
Copyright: © 2025 Zhang, Ding, Yang, Jiang, Feng, Qu, Qiao and Meng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Yuling Qiao, Jining NO.1 people's hospital, JiNing, China
Qiang Meng, Jining NO.1 people's hospital, JiNing, China
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