ACC/AHA Risk Score for Predicting the Presence and Severity of Coronary Artery Disease in a Chinese Population: A Cross-Sectional Study
Coronary artery disease (CAD) remains the leading cause of mortality globally, accounting for approximately 17.3 million deaths in 2013. This figure has increased since 1990, highlighting the growing burden of cardiovascular diseases (CVD) worldwide. The American College of Cardiology (ACC)/American Heart Association (AHA) risk score is a widely recognized model for estimating the 10-year risk of a first hard atherosclerotic cardiovascular disease (ASCVD) event. This study aimed to evaluate the association between the ACC/AHA risk score and the Gensini Score (GS) system, a measure of CAD severity, and to determine whether the ACC/AHA score could predict the presence and severity of CAD in a Chinese population.
The study was conducted as a single-center, cross-sectional observational study at Sir Run Run Shaw Hospital, Zhejiang University, from January 2007 to July 2019. A total of 16,155 subjects were enrolled, with inclusion criteria requiring participants to be aged between 40 and 79 years and not to have undergone any coronary angiography prior to the inpatient period. Patients with severe valve diseases, severe heart failure, acute coronary artery syndrome, stroke, previous myocardial infarction, or other procedures were excluded. The study protocol adhered to the Declaration of Helsinki and was approved by the hospital’s ethics committee. Written informed consent was obtained from all participants.
Participants were categorized into different groups based on their GS values, which were used to assess the severity of CAD. Clinical variables, including gender, age, systolic blood pressure (BP), hypertension, smoking status, diabetes mellitus (DM), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), total bilirubin (TB), white blood cell (WBC) count, mean platelet volume (MPV), and C-reactive protein (CRP), were analyzed for their association with the presence and severity of CAD. Univariate and multivariate logistic regression analyses were performed to identify independent indicators for both the presence and severity of CAD.
The ACC/AHA risk scores were calculated using coefficients for both white and black populations. Linear and logistic regression analyses were employed to assess the relationship between the ACC/AHA risk score and the presence and severity of CAD. The results indicated that the ACC/AHA risk score was an independent predictor of both the presence and severity of CAD, regardless of whether white or black coefficients were used.
To further validate the predictive power of the ACC/AHA risk score, receiver operating characteristic (ROC) curves were constructed, and the area under the curve (AUC) values were calculated. The ACC/AHA risk score demonstrated superior performance compared to the Framingham risk score (FRS) in predicting the presence of CAD, with a statistically significant difference in AUC values. However, for predicting the severity of CAD, the FRS outperformed the ACC/AHA risk score.
The study identified potential cut-off values for the ACC/AHA risk score in the Chinese population. An ACC/AHA risk score of 8.45% (using white coefficients) or 8.76% (using black coefficients) could serve as a threshold for determining the presence of CAD. For predicting the need for percutaneous coronary intervention (PCI), a cut-off value of 10.71% (white coefficients) or 12.74% (black coefficients) was proposed.
The findings of this study are significant as they provide evidence that the ACC/AHA risk score can be effectively used to predict both the presence and severity of CAD in a Chinese population. The study’s large sample size and rigorous methodology lend credibility to the identified cut-off values, which could be valuable in clinical decision-making. Additionally, the comparison with the Framingham risk score highlights the strengths and limitations of each model in different contexts.
Several other risk scoring systems, such as the Framingham risk score, the Multi-Ethnic Study of Atherosclerosis (MESA), and the Systematic COronary Risk Evaluation (SCORE), have been explored in previous studies. These models have demonstrated varying degrees of success in predicting CAD presence and severity. For example, the Framingham risk score has been shown to correlate with CAD severity in some populations, while the MESA model has outperformed the Framingham risk score in others. The SCORE model has also been found to have a slightly better performance than the Framingham risk model in certain studies.
In addition to traditional risk scoring systems, some studies have combined various risk factors to develop novel statistical models for predicting CAD. For instance, a severe prediction scoring model based on age, gender, aortic valve calcification, echocardiography, DM status, and lipid levels has been proposed. Another modified Framingham score has shown promise in estimating the probability of CAD in stable patients with suspected CAD.
The study also highlights the potential for combining inflammatory factors with the ACC/AHA risk score to predict acute coronary syndrome in the future. This approach could enhance the predictive power of existing models and provide more accurate risk stratification for patients undergoing PCI.
In conclusion, the ACC/AHA risk score is a valuable tool for predicting the presence and severity of CAD in a Chinese population aged 40 to 79 years. The identified cut-off values offer practical thresholds for clinical decision-making, particularly in determining the need for PCI. While the ACC/AHA risk score outperforms the Framingham risk score in predicting CAD presence, the latter remains superior for assessing CAD severity. These findings underscore the importance of tailoring risk prediction models to specific populations and clinical contexts.
doi.org/10.1097/CM9.0000000000001123
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