Various Predictive Scales of Pretest Probability in Identifying Patients at Low Risk of Coronary Artery Disease
The estimation of pre-test probability (PTP) of coronary artery disease (CAD) is recommended in every patient with suspected CAD. It is important to identify patients with a low probability of CAD who do not require additional diagnostic testing. The aim of this study was to compare various PTP scales to identify patients with a low probability of CAD. The study included 60 patients aged 40 to 75 years (41 men and 19 women, mean age 61.5 ± 9.0 years) with suspected CAD who presented with chest pain for the first time. All patients were evaluated for PTP of CAD using three scales: ESC 2019 scale, CAD Consortium Clinical, and CAD Consortium Extended scales. Based on the results of each scale, 3 groups of patients with low PTP <15% were identified. Coronary computed tomography angiography was performed to assess the degree of coronary artery (CA) stenosis, and coronary artery calcium (CAC) was calculated using the Agatston score. Stress/rest single-photon emission computed tomography was performed to identify perfusion defects. In the 1st group, moderate stenosis was detected in almost one third of patients, but significant stress-induced myocardial perfusion deficit was observed in less than 10% of patients. The correlation between coronary calcification and the number of major risk factors (RFs) was revealed: the average CAC score in patients with 0, 1, 2, and 3 RFs was 0, 93, 208, and 523, respectively. In the 2nd group, moderate СA stenoses were detected 1.7 times less frequently than in the 1st group (16.7 vs 29.4%, respectively). All patients of the 3rd group had CAC score below 100, and CAC = 0 was noted in more than half of patients (58.3%). In this group moderate stenosis of CAs was detected only in 1 patient (4.2%) and only 1 patient (4.2%) had a significant stress-induced myocardial perfusion deficit (SDS = 5). Scales that include various risk factors for cardiovascular disease are more reliable in predicting obstructive CAD in symptomatic patients.