Predictive Role of Pretest Factors and Cardiovascular Risk Factors in Obstructive Coronary Artery Disease

Background: The impact of cardiovascular risk factors—such as hypertension, diabetes, smoking, dyslipidemia, and family history of premature cardiovascular disease—on the pretest probability of coronary artery disease remains a critical area of investigation. However, data specific to the Vietnamese population regarding pretest risk factors and their influence on the diagnosis of obstructive chronic coronary artery disease remain scarce. To address this gap, we conducted a study titled “The Role of an Extended Model in Predicting Obstructive Coronary Artery Disease.” Materials and Methods: We enrolled 198 patients who underwent invasive coronary angiography at Nguyen Trai Hospital between September 1, 2020, and August 30, 2022. This cross-sectional study aimed to explore associations between risk factors and the likelihood of obstructive coronary artery disease. Results: Among the study cohort, 99 cases (50%) were diagnosed with chronic obstructive coronary artery disease, while the remaining 99 cases had non-chronic obstructive disease. The median age was 66 years (interquartile range, 57–73), with 56% of participants being male. Notably, obesity was observed in 34.3% of the cohort. Multivariable logistic regression analysis revealed statistically significant independent associations between the following factors and chronic obstructive coronary artery disease: Age, Smoking status, Diabetes, Hypertension, History of dyslipidemia, Characteristics of chest pain, LDL-cholesterol levels, ST-T abnormalities and pathological Q waves on electrocardiogram. The classical model demonstrated an area under the receiver operating characteristic (ROC) curve of 0.75 (95% CI 0.67–0.81), while the clinical model achieved an area under the ROC curve of 0.82 (95% CI 0.77–0.88). However, our extended model outperformed both, exhibiting the highest predictive value for obstructive coronary artery disease with an area under the ROC curve of 0.86 (95% CI 0.8–0.92, p < 0.001). Conclusions: Our extended model not only demonstrated a robust discriminatory ability but also provided valuable tools for clinicians. By enhancing risk assessment and aiding in patient follow-up planning, this model contributes to more informed clinical decision-making.