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◆ Journal of cardiovascular development and disease2026-09-01

Epicardial Adipose Tissue Shows No Significant Incremental Value for Discriminating Coronary Artery Disease in Adults Aged 80 Years and Older: A Machine Learning Analysis.

Jingyi Li, Ziwei Zhu, Xuefeng Ni, Hui Lian

原始摘要(英文原文)· Original abstract
Background: Epicardial adipose tissue (EAT) has been associated with coronary artery disease (CAD) in middle-aged and mixed-age populations, but its value in adults aged 80 years and older remains uncertain. This study investigated whether computed tomography (CT)-derived EAT volume provides incremental value for discriminating CAD in this very elderly population. Methods: We retrospectively included 155 patients aged ≥80 years who underwent coronary imaging evaluation between 2020 and 2022. EAT volume was quantified from non-contrast chest CT. Logistic regression, CatBoost modeling, and SHapley Additive exPlanations (SHAP) were used to assess the association of EAT with CAD, its discriminative value, and its relative contribution. Results: Forty-five patients (29.0%) had CAD. Median EAT volume did not differ between groups (p = 0.716) and was not associated with CAD after adjustment for age, sex, body mass index, diabetes, and glycated hemoglobin A1c (HbA1c). Adding EAT did not improve discrimination in logistic regression [area under the curve (AUC) 0.698 vs. 0.697; likelihood-ratio p = 0.945] or in cross-validated CatBoost analysis (AUC 0.623 vs. 0.614). SHAP ranked EAT eighth of eighteen predictors, below lipoprotein(a), total cholesterol, left atrial diameter, HbA1c, low-density lipoprotein cholesterol, diabetes, and atrial fibrillation. Conclusions: In adults aged 80 years and older, CT-derived EAT volume was not independently associated with CAD and added no discriminative value beyond conventional clinical risk factors. Total EAT volume may have limited utility as a CAD marker in very elderly adults.
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Epicardial Adipose Tissue Shows No Significant Incremental Value for Discriminating Coronary Artery Disease in Adults Aged 80 Years and Older: A Machine Learning Analysis. — 科研速览 Science Skim