https://doi.org/10.4081/ejtm.2026.15842
A study on the predictive value of CT plain scan of pericoronal fat thickness combined with clinical indicators for young patients with coronary atherosclerotic heart disease
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Accepted: 24 August 2026
Published: 2 October 2026
This study aimed to investigate whether chest CT scans could predict the incidence of atherosclerotic heart disease in patients aged ≤40 years. Convenience sampling was used to select 296 patients aged ≤ 40 years with Acute Coronary Syndrome (ACS), and their general information and CT data were collected. According to the results of coronary CTA, patients were divided into a diseased group (134) and an untreated group (162). Single and multiple logistic regression were used to analyze variables, and different variable combination models and single variable models were established to analyze the clinical value of different models. The results showed systolic blood pressure, diastolic blood pressure Thick1 and BMI. There is a statistically significant relationship between fasting blood glucose and the occurrence of coronary artery plaques. After single factor logistic regression analysis, multiple factor logistic analysis was carried out for indicators with P values less than 0.05. The results showed that gender (OR: 2.1, 95% CI: 1.031-4.292, p=0.04), systolic blood pressure (OR: 1.02, 95% CI: 1.01-1.036, p=0.000), diastolic blood pressure (OR: 1.04, 95% CI: 1.017-1.054, p=0.000), Chol (OR: 1.26, 95% CI: 1.056-1.495, p=0.01), TG (OR: 1.35, 95% CI: 1.09-1.678, p=0.01), FBG (OR: 1.11, 95% CI: 1.009-1.213, p=0.03), Thick1 (OR: 1.5, 95% CI: 1.337-1.682, p=0.000) and coronary atherosclerosis. The area under the curve of the prediction model based on the thickness of coronal fat (Thick1), as well as the area under the curve of the prediction model based on systolic blood pressure, diastolic blood pressure, and FBG, show that the effectiveness of the Thick1 model is much higher than that of the clinical indicator model. Chest CT scans hold clinical significance in predicting coronary atherosclerosis in patients aged ≤40 years with ACS.
Downloads
1. Shen Qin, Zhang Xiao, Wu Ting, et al. The evaluation value of coronary CT angiography calcification score for coronary artery lesions and prognosis in patients with chronic angina pectoris. J Pract Clin Med 2022;26:1-4, 8
2. Kim WJ, Lim HJ, Moon JY, et al. Sex differences in the impact of body mass index on outcomes of coronary artery disease in Koreans. J Coron Artery Dis 2024;35:193-200. DOI: https://doi.org/10.1097/MCA.0000000000001346
3. Torii S, Chiang CE, Hong SJ, et al. Asian perspective on the recently published practice guideline for acute coronary syndrome by ESCJ. Eur Heart J Acute Cardiovasc Care 2024;13:162-4. DOI: https://doi.org/10.1093/ehjacc/zuad126
4. Lin C, Miao Z, Xiancheng X, et al. Research on the current situation and influencing factors of health-promoting lifestyles in young and middle-aged patients with acute coronary syndrome. J Hubei Univ Medicine 2023;42:82-7.
5. Xueqi W, Lanting Z, Chunyan M. Research progress on the correlation between carotid and lower extremity atherosclerosis and coronary heart disease. J Pract Clin Med 2022;26:125-9.
6. Doughty A, Keane G, Wadley AJ, et al. Plasma concentrations of thioredoxin, thioredoxin reductase and peroxiredoxin-4 can identify high risk patients and predict outcome in patients with acute coronary syndrome: A clinical observation. Int J Cardiol 2024;403:131888. DOI: https://doi.org/10.1016/j.ijcard.2024.131888
7. Yuan Y, Shi J, Sun W, et al. The positive association between the atherogenic index of plasma and the risk of new-onset hypertension: a nationwide cohort study in China. Clin Exp Hypertens 2024;46:2303999. DOI: https://doi.org/10.1080/10641963.2024.2303999
8. Rozenbaum Z, Klein E, Cohen T, et al. Temporal trends in management and outcomes of patients with acute coronary syndrome according to body mass index. Eur Heart J Acute Cardiovasc Care 2021;10:170-5. DOI: https://doi.org/10.1177/2048872619825569
9. Glovaci D, Fan W, Wong ND. Epidemiology of diabetes mellitus and cardiovascular disease. Curr Cardiol Rep 2019:21:21. DOI: https://doi.org/10.1007/s11886-019-1107-y
10. de Koning L, Merchant AT, Pogue J, et al. Waist circumference and waist-to-hip ratio as predictors of cardiovascular events: meta-regression analysis of prospective studies. Eur Heart J 2007;28:850-6. DOI: https://doi.org/10.1093/eurheartj/ehm026
11. Sanyang T, Xusong W, Zhangping L, et al. Serum triglyceride-glycemic index, glycated serum protein and retinol-binding protein 4 levels are correlated with the degree of coronary artery disease. J Intern Med Critical Care 2022;28:46-9.
12. Fukuoka Y, Oh YJ. Perceived heart attack likelihood in adults with a high diabetes risk. Heart Lung 2022;52:42-7. DOI: https://doi.org/10.1016/j.hrtlng.2021.11.007
13. Zhuo C, Blayin Y, Ying G, et al. Establishment and validation of predictive models for the risk of coronary atherosclerotic heart disease by SCI, TyG, and AIP. Joint Milit Med 2023;37:924-30.
14. Lian X, Gollasch M. A clinical perspective: contribution of dysfunctional perivascular adipose tissue (PVAT) to cardiovascular risk. Curr Hypertens Rep 2016;18:82. DOI: https://doi.org/10.1007/s11906-016-0692-z
15. Boyuk B, Cetin SI, Erman H, et al. Evaluation of serum endocan levels in relation to epicardial fat tissue thickness in metabolic syndrome patients. Arch Med Sci Atheroscler Dis 2020;5:e290-6. DOI: https://doi.org/10.5114/amsad.2020.103031
16. Yin R, Tang X, Wang T, et al. Cardiac CT scanning in coronary artery disease: Epicardial fat volume and its correlation with coronary artery lesions and left ventricular function. Exp Ther Med 2020;20:2961-8. DOI: https://doi.org/10.3892/etm.2020.9064
17. Wall C, Weir-McCall J, Tweed K, et al. CT pericoronary adipose tissue density predicts coronary allograft vasculopathy and adverse clinical outcomes after cardiac transplantation. Eur Heart J Cardiovasc Imaging 2024;25:1018-27. DOI: https://doi.org/10.1093/ehjci/jeae069
18. Ying Z, Botao W, Jiangjun Q, et al. Texture analysis technique for evaluating the changes of pericoronal adipose tissue in patients with coronary atherosclerosis. J Molecular Imaging 2023;46:257-61.
CRediT authorship contribution
Lihua Zhang and Aichao Ruan conceived and designed the study. Lihua Zhang and Yang Gu collected and analyzed the data. Lihua Zhang drafted the manuscript. Aichao Ruan critically revised the manuscript for important intellectual content. All authors read and approved the final manuscript.
Supporting Agencies
Data Availability Statement
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
How to Cite
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.