Abstract
Cardiovascular disease, primarily coronary artery disease (CAD), is the leading cause of mortality worldwide. Accurate diagnosis of CAD often requires pre-test probability (PTP) estimation, traditionally performed using scoring systems like the Diamond-Forrester (DF) and European Society of Cardiology (ESC) models. However, the applicability of such models in specific populations may vary. This study compares the performance of DF and PTP scores in the Brazilian context, using coronary computed tomography angiography (CCTA) as a reference standard. PTP for obstructive CAD was calculated using DF and ESC scores in 409 symptomatic patients without known CAD who underwent CCTA between 2019 and 2022. Predicted PTP was compared with actual CAD prevalence. DF overestimated CAD prevalence across age and symptom categories, while ESC showed better alignment with actual prevalence. Our study confirms that the ESC PTP model is more appropriate than the DF model for determining PTP in the Brazilian population.
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