Diagnostic Accuracy Improvement of an Updated HEART Score to Predict Coronary Artery Disease as Detected by Coronary Computed Tomography Angiography

Background: The HEART score is a widely used risk-stratification tool in suspected acute coronary syndrome (ACS), but it still suffers from several limitations. We aim to assess its diagnostic accuracy for predicting coronary computed tomography angiography (CCTA) findings and explore possible enhancement by integrating additional clinical variables. Methods: In this retrospective, observational study, consecutive patients presenting to the Emergency Department with suspected ACS and undergoing CCTA were analyzed. The study assessed the HEART score’s diagnostic accuracy for predicting significant coronary artery stenosis (defined as ≥70% stenosis at CCTA) and explored improvements by integrating additional clinical variables for low-to-moderate-risk patients. Results: Three hundred seventy-nine patients were enrolled (age: 61 ± 15 years; male: 57%). According to the HEART score, 27% were at low risk, 67% moderate risk, and 6% high risk, with a prevalence of significant CAD of 7%, 27%, and 67%, respectively. The area under the curve (AUC) of the HEART score to predict significant CAD was 0.68. Male gender (OR = 1.76, 95% CI 1.03–3.02), right bundle branch block (OR = 4.15, 95% CI 1.66–10.40), and hemoglobin (OR = 1.21) and glucose levels (OR = 1.01) independently predicted significant coronary stenosis at CCTA in patients at low-to-moderate risk. Integrating these variables into the HEART score, the AUC improved from 0.68 to 0.74 (p = 0.004), with a net reclassification improvement of 13.5% (p = 0.032). Conclusions: Integrating additional clinical variables into the HEART score improves its accuracy to predict significant coronary artery stenosis at CCTA in suspected ACS patients at low-to-moderate risk. Tailoring assessments with these variables supports more accurate patient management and highlights the potential for more comprehensive diagnostic approaches.