The atherosclerosis burden score

Autor: Salah D. Qanadli, Lucia Mazzolai, Michèle Depairon, Eric Eeckhout, Roger Darioli, E. Katz, Angeliki Koulouri
Rok vydání: 2021
Předmět:
Zdroj: Vasa. :1-6
ISSN: 1664-2872
0301-1526
DOI: 10.1024/0301-1526/a000949
Popis: Summary: Purpose: We carried out this study to evaluate the predictive value of atherosclerosis burden score (ABS) to predict coronary artery disease (CAD) among asymptomatic patients without known cardiovascular disease (CVD), as compared to other imaging or functional techniques, namely coronary artery calcium (CAC) score, carotid intima-media thickness (C-IMT), and ankle brachial index (ABI). Patients and methods: This prospective study included 198 asymptomatic consecutive patients referred for evaluation of their cardiovascular (CV) risk and for therapeutic advice. Traditional CV risk factors, ABS, CAC score, C-IMT, ABI and an ECG-synchronized coronary CT-angiography (CCTA) were performed for each patient. We compared the predictive values of these atherosclerosis markers to detect CAD defined as coronary stenosis ≥30% objectivated by CCTA. Results: Among the whole sample, the area under the receiver-operating characteristic curve (ROC-AUC) was significantly higher for CAC score (0.81, p=0.015) than for ABS, the reference (0.70) but these values were lower for C-IMT (0.60, p=0.16) and particularly for ABI (0.56, p=0.0015). However, among patients at intermediate risk of coronary heart disease (CHD), according to Framingham risk score (FRS), the differences between the ROC-AUC values for ABS (0.70) and CAC score (0.76, p=0.36) were less pronounced. Again, as compared to ABS, the ROC-AUC values were lower for C-IMT (0.60, p=0.21) and ABI (0.57, p=0.06). Conclusions: ABS, an ultrasonographic score based on the assessment of carotid and femoral plaque burden, predicts more accurately CAD than other non-radiation tools analyzed here, and has a similar performance to CAC in patients at intermediate CHD risk. Thus, ABS could be an appropriate non-invasive and safe method to improve the detection of high-risk patients who will benefit from a more intensive therapy for the primary prevention of CVD.
Databáze: OpenAIRE
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