Coronary Artery Calcification on Chest Computed Tomography as a Predictor of Cardiovascular Adverse Events in Patients With COVID-19 -- A Multicenter Retrospective Study in Japan --

Abstract

BACKGROUND: Coronary artery calcification (CAC) detected through chest computed tomography (CT) strongly predicts cardiovascular events in asymptomatic individuals undergoing primary prevention. Few studies with limited sample sizes have investigated the predictive value of CAC for cardiovascular complications in COVID-19. This study examined the impact of CAC on cardiovascular complications using a large-scale COVID-19 database. METHODS AND RESULTS: This multicenter retrospective cohort study used data from the Japan COVID-19 Task Force database. After exclusion based on missing information, 1, 109 patients with COVID-19 were included. The Agatston score was used to evaluate CAC, dividing the population into 3 groups based on calcification degree (no, moderate, and severe CAC). The primary outcome was cardiovascular complications; the secondary outcome was critical outcomes. The severe CAC group had a higher rate of cardiovascular complications than the other groups. Multivariable analysis, considering COVID-19 severity factors, identified severe CAC as independently associated with cardiovascular complications but not with critical outcomes. Subgroup analysis revealed that, in patients without hypertension, diabetes, cardiovascular disease, or chronic kidney disease, severe CAC was significantly correlated with cardiovascular complications, whereas this association was not observed in patients with these underlying conditions. CONCLUSIONS: Patients with COVID-19 and severe CAC had increased cardiovascular complications, and identifying cardiovascular and pulmonary findings on chest CT is essential. Measuring CAC via non-electrocardiogram-gated CT helps predict patient risk.