AUTHOR=Zhao Sijie , Lian Zizhu , Wang Xiaoning , Mei Na 

TITLE=Inflammation-related biomarkers for intracardiac thrombosis in acute myocardial infarction: predictive value and mechanistic implications of NLR and LDL-C

JOURNAL=Frontiers in Medicine

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2025.1643933

DOI=10.3389/fmed.2025.1643933

ISSN=2296-858X

ABSTRACT=BackgroundInflammatory pathways critically contribute to the pathogenesis of intracardiac thrombosis (ICT) following acute myocardial infarction (AMI) patients. This study evaluated the predictive value of inflammation biomarkers for ICT.MethodsThis retrospective case–control study included 8,999 AMI patients hospitalized at the First Affiliated Hospital of Xi’an Jiaotong University from January 2018 to December 2022, among whom 88 developed ICT. To address class imbalance, 891 non-ICT patients were randomly selected as controls using a 1:10 ratio. Inflammation-related biomarkers were screened using univariate and multivariate logistic regression, and a risk heatmap was generated based on key predictors.ResultsMultivariate logistic regression identified elevated neutrophil-to-lymphocyte ratio (NLR), N-terminal pro–B-type natriuretic peptide (NT-proBNP), low-density lipoprotein cholesterol (LDL-C), and reduced albumin-to-globulin ratio (AGR) as independent risk factors for ICT. NLR demonstrated the highest discriminatory capacity, demonstrating superior predictive performance [receiver operating characteristic (ROC) curve, area under the curve (AUC) = 0.774, 95% confidence interval (CI): 0.724–0.823, p < 0.001] that persisted after full covariate adjustment, and remained significant after full adjustment [odds ratio (OR) = 2.54, 95% CI: 1.98–3.15, p = 0.002]. Integration of NLR and LDL-C into a sex-stratified risk stratification matrix significantly enhanced diagnostic accuracy (AUC = 0.838, 95% CI: 0.799–0.878).ConclusionThis study established NLR as a robust indicator for ICT assessment and presents a practical, visual risk heatmap that may facilitate personalized thromboprophylaxis in AMI management.