OBJECTIVES: Cardiovascular disease (CVD) poses a major threat to global health. Evaluating atherosclerosis in asymptomatic individuals can help identify those at high risk of CVD. This study aims to establish an individualized nomogram prediction model to estimate the risk of vascular plaque formation in asymptomatic individuals. METHODS: A total of 5 655 participants who underwent CVD screening at the Health Management Center of The Third Xiangya Hospital, Central South University, between January 2022 and June 2024 we retrospectively enrolled. Using simple random sampling, participants were divided into a training set (n=4 524) and a validation set (n=1 131) in an 8꞉2 ratio. Demographic and clinical data were collected and compared between groups. Multivariate logistic regression analysis was used to identify independent factors associated with vascular plaques and to construct a nomogram prediction model. The predictive performance and clinical utility of the model were evaluated using receiver operating characteristic (ROC) curves, the Hosmer-Lemeshow goodness-of-fit test, calibration plots, and decision curve analysis (DCA). RESULTS: The mean age of participants was 52 years old. There were 3 400 males (60.12%). The overall detection rate of vascular plaque in the screening population was 49.87% (2 820/5 655). No statistically significant differences were observed in clinical indicators between the training and validation sets (all P>0.05). Multivariate Logistic regression analysis identified age, systolic blood pressure, high-density lipoprotein (HDL), low-density lipoprotein (LDL), lipoprotein(a), male sex, smoking history, hypertension history, and diabetes history as independent risk factors for vascular plaque in asymptomatic individuals (all P<0.05). The area under the curve (AUC) of the nomogram model for predicting vascular plaque risk were 0.778 (95% CI 0.765 to 0.791, P<0.001) in the training set and 0.760 (95% CI 0.732 to 0.787, P<0.001) in the validation set. The Hosmer-Lemeshow goodness-of-fit test indicated good model calibration (training set: P=0.628; validation set: P=0.561). The calibration curve plotted using the Bootstrap method demonstrated good agreement between predicted probabilities and actual probabilities. DCA showed that the nomogram provided a clinical net benefit for predicting vascular plaque risk when the threshold probability ranged from 0.02 to 0.99. CONCLUSIONS The nomogram prediction model for vascular plaque risk, constructed using readily available and cost-effective physical examination indicators, exhibited good predictive performance. This model can assist in the early identification and intervention of asymptomatic individuals at high risk for cardiovascular disease.
Humans ; Male ; Middle Aged ; Female ; Nomograms ; Retrospective Studies ; Risk Factors ; Plaque, Atherosclerotic/diagnosis* ; Aged ; Adult ; Physical Examination ; Logistic Models ; Cardiovascular Diseases/epidemiology* ; ROC Curve

PURPOSE: In this study, we aimed to evaluate whether nonalcoholic fatty liver disease (NAFLD) was associated with the presence and morphology of coronary atherosclerotic plaques shown by multidetector computed tomography (MDCT) in asymptomatic subjects without a history of cardiovascular disease. MATERIALS AND METHODS: We retrospectively enrolled 772 consecutive South Korean individuals who had undergone both dualsource 64-slice MDCT coronary angiography and hepatic ultrasonography during general routine health evaluations. The MDCT studies were assessed for the presence, morphology (calcified, mixed, and non-calcified), and severity of coronary plaques. RESULTS: Coronary atherosclerotic plaques were detected in 316 subjects (40.9%) by MDCT, and NAFLD was found in 346 subjects (44.8%) by hepatic ultrasonography. Subjects with NAFLD had higher prevalences of all types of atherosclerotic plaque and non-calcified, mixed, and calcified plaques than the subjects without NAFLD. However, the prevalence of significant stenosis did not differ between groups. After adjusting for age, smoking status, diabetes mellitus, hypertension, dyslipidemia, and metabolic syndrome, NAFLD remained a significant predictor for all types of coronary atherosclerotic plaque [odds ratio (OR): 1.48; 95% confidence interval (CI): 1.05-2.08; p=0.025] in binary logistic analysis, as well as for calcified plaques (OR: 1.70; 95% CI: 1.07-2.70; p=0.025) in multinomial regression analysis. CONCLUSION: Our study demonstrated that NAFLD was significantly associated with the presence and the calcified morphology of coronary atherosclerotic plaques detected by MDCT. Further prospective clinical studies are needed to clarify the exact physiopathologic role of NAFLD in coronary atherosclerosis.
Adult ; Aged ; Asian Continental Ancestry Group/statistics & numerical data ; Calcinosis/ethnology/*radiography ; Case-Control Studies ; Coronary Angiography/*methods ; Coronary Artery Disease/ethnology/pathology/*radiography ; Female ; Humans ; Male ; Middle Aged ; Multidetector Computed Tomography/*methods ; Non-alcoholic Fatty Liver Disease/epidemiology/*ultrasonography ; Odds Ratio ; Plaque, Atherosclerotic/*diagnosis/epidemiology ; Prevalence ; Regression Analysis ; Republic of Korea/epidemiology ; Retrospective Studies ; Risk Factors ; Ultrasonography