Clinical Research Directory

The Clinical Likelihood (CL) model-based diagnostic strategy utilizes two models: the RF-CL model and the CACS-CL model. These models assess the pre-test probability of obstructive coronary artery disease (CAD) based on patient factors such as age, sex, symptoms, and traditional cardiovascular risk factors like smoking, diabetes, and hypertension. The CACS-CL model incorporates coronary artery calcium scoring to further refine the risk assessment. Patients identified with a low likelihood of CAD may avoid unnecessary diagnostic testing, such as cardiac CT, while maintaining diagnostic accuracy and safety. This approach aims to optimize resource use, reduce patient burden, and focus on other potential causes of symptoms when CAD is unlikely.

Patients will follow the standard diagnostic pathway, which includes the use of cardiac CT and other advanced diagnostic procedures based on clinical guidelines. This approach is the current standard of care for patients with suspected obstructive coronary artery disease (CAD). The control group allows for comparison of outcomes with those in the intervention arm, particularly in terms of resource utilization, patient safety, and diagnostic accuracy.