Abstract
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.