EFFECTS OF CORONARY ARTERY CALCIFIED PLAQUE AND STENT ON SEVERITY AND SURVIVAL OF COVID-19 PATIENTS: A DECISION TREE MODEL STUDY

Abstract

Aim We aimed to investigate the relationship between the presence of calcified plaques and stents in coronary arteries as evaluated by the chest computed tomography severity score (CT-SS) and mortality rates in patients with COVID-19. Material and methods A single-center retrospective analysis was conducted of 492 patients (>= 18 yrs) who were hospitalized between March and June 2020. All included patients had RT-PCR tests positive for COVID-19. A radiologist recorded pulmonary imaging findings and the presence of coronary calcified plaque and/or stent, sternotomy wires, and cardiac valve replacement on initial non-contrast chest CT. Also, cardiothoracic ratios (CTR) were calculated on chest CTs. Data were analyzed using univariate and multivariate analyses and a chi-squared automatic interaction detection (CHAID) tree analysis, which was developed as a predictive model for survival of COVID-19 patients according to chest CT findings. Results The mean CT-SS value of the patients with coronary plaque was 11.88 +/- 7.88, and a significant relationship was found between CT-SS with coronary calcified plaque (p<0.001). No statistical difference was found between CT-SS and coronary stent (p=0.296). In multivariate analysis, older age was associated with 1.69-fold (p<0.001), the presence of coronary calcified plaque 1.943-fold (p=0.034) and higher CT- SS 1.038-fold (p=0.042) higher risk of mortality. In the CHAID tree analysis, the highest mortality rate was seen in patients with coronary plaque and CTR>0.57. Conclusion The presence of coronary artery calcified plaque and cardiomegaly were high risks for severe prognosis and mortality in COVID-19 patients and may help to predict the survival of patients.