Correlation of TIMI and GRACE Risk Scores with Coronary Artery Disease Extent Assessed by SYNTAX Score in Patients with Stable Coronary Artery Disease

Abstract

Objectives: To evaluate the correlation between established clinical risk scores, including TIMI and GRACE, and the anatomical extent of coronary artery disease, as assessed by the SYNTAX score, in patients with stable coronary artery disease undergoing elective coronary angiography. Methodology: This descriptive cross-sectional study was conducted at a tertiary-care cardiology center over a six-month period. A total of 73 consecutive patients with stable coronary artery disease undergoing coronary angiography were included. TIMI and GRACE risk scores were calculated using standard validated criteria, while coronary angiographic complexity was assessed using the SYNTAX score. Pearson’s correlation analysis was performed to evaluate associations between clinical risk scores and SYNTAX score. Multiple linear regression analysis was used to identify independent predictors of coronary anatomical complexity. Results: The mean age of participants was 58.4 ± 10.2 years, with males comprising 71.2% of the cohort. Mean TIMI, GRACE, and SYNTAX scores were 3.8 ± 1.5, 112.3 ± 28.5, and 22.4 ± 8.9, respectively. TIMI score demonstrated a moderate positive correlation with SYNTAX score (r = 0.45, p < 0.001), whereas GRACE score showed a stronger correlation (r = 0.66, p < 0.001). On multivariable regression analysis, both GRACE score (β = 0.45, p < 0.001) and TIMI score (β = 0.25, p = 0.02) independently predicted SYNTAX score, while traditional cardiovascular risk factors were not independently associated. Conclusion: Both TIMI and GRACE risk scores are positively correlated with the anatomical complexity of coronary artery disease in patients with stable coronary artery disease. GRACE demonstrated superior predictive performance compared with TIMI. These clinical risk scores may serve as practical tools for anticipating coronary disease severity and guiding revascularization planning in resource-limited settings.