Document Type : Original Article
1 Department of Radiology, Medical School, Isfahan University of Medical Sciences, Isfahan, Iran
2 Medical Students’ Research Centre, Isfahan University of Medical Sciences, Isfahan, Iran
3 Department of Epidemiology and Biostatistics, School of Health, Behavioral Sciences Research Center, Isfahan University of Medical Sciences, Iran.
4 Alzahra Research Institute, Alzahra University Hospital, Isfahan University of Medical Sciences, Isfahan, Iran
Introduction: Coronary computed tomography angiography (CCTA) is a non-invasive modality of cardiovascular imaging by which coronary artery calcifications (CAC), a marker of subclinical atherosclerosis, can be visualized. Due to the different calcification patterns in patients with chronic kidney disease (CKD) from the general population, the current study aims to present diagnostic cut-off values for CAC to detect early CAD in CKD patients.
Methods: The current cross-sectional study included a total of 807 patients, 407 cases with chronic kidney disease, and 400 healthy controls, undergone CCTA during 2019-21. The CAC score measurements were done for all the left main coronary arteries to investigate coronary artery disease(CAD). To determine the value of CAC, coronary artery disease reporting and data system (CAD-RADS) was used as the gold standard, and diagnostic values were measured.
Results: At the cut-off point of 85, the CAC score had the sensitivity and specificity of 84.7% and 83% among the patients with CKD to diagnose CAD, respectively (AUC: 0.919, 95%CI: 0.89-0.94; P-value<0.001). Considering a cut-point of 85 for CAC, the frequency of healthy subjects with CAD-RADS less than 2 was remarkably more than the cases(P-value=0.012), while the two groups were similar regarding CAD-RADS 3-5(P-value=0.83).
Conclusion: The CAC score is a valuable mean to figure out CAD among CKD subjects. There is no significant difference in CAC of patients with significant CAD-RADS in CKD and non-CKD patients. The cut-point of 85 for the CAC score was found valuable to diagnose CAD with over 80% of sensitivity and specificity.