Predictive ability of coronary computed tomography angiography parameters in patients suspected of obstructive coronary artery disease: a single-center cross-sectional study

OBJECTIVE: Coronary computed tomography angiography (CCTA) is becoming increasingly useful for the diagnosis of coronary artery disease (CAD). Coronary calcium score (CCS), epicardial fat volume (EFV), and number of coronary plaques (NoP) add important information for the risk stratification and prognosis prediction of these patients. However, evidence about their ability to predict obstructive CAD is limited. We sought to evaluate the ability of CCTA parameters in predicting obstructive CAD. PATIENTS AND METHODS: We conducted a cross-sectional, single-center study on patients at risk to develop CAD. CCS, EFV and NoP were determined by CCTA. CAD was defined as coronary stenosis > 50%. CCS was then ranked 5 severity groups: 0, 1-99, 100-399.400-999, and 21000. NoPs were classified in four categories: no plaques, 1-5, 6-10 and >= 10. Logistic regression analyses were performed, and statistical analysis was considered significant if p<0.05. RESULTS: Off all 540 patients (55.8 +/- 11.1 years) who met the enrolment criteria. 98 had obstructive CAD. CCS, EFV and NoP were significantly associated with the presence of obstructive CAD (p<0.0001). The area under the receiver operating characteristics (ROC) analysis revealed significant cut-off values (p<0.0001) of CCS (70.3). EFV (40.8). NoP (4) for predicting obstructive CAD. Their association proved to have an AUC of 0.969, and a specificity of 95%. A scoring system based on regression coefficients which proved to have statistical significance for obstructive CAD as further constructed. It included EFV, CCS and left ventricular ejection fraction. This scoring system significantly predicted obstructive CAD for a cut-off value of 62.46, with a NPV of 96.3%. CONCLUSIONS: The combined use of CCS, EFV and NoPs increases the predictive ability for obstructive CAD of each parameter used alone. These could be useful for developing a novel scoring system.

Automated summary

The combination of CCS, EFV, and NoPs increases the predictive ability for obstructive CAD of each parameter used alone, which could be useful for developing a novel scoring system.