Table 2.

Multivariate regression analysis for the prediction of major adverse cardiovascular events (MACE)

Independent variables	OR (95% CI)	p value
A. Multivariate Cox regression model for the prediction of MACE, adjusted for cardiovascular risk factors and obstructive CAD on CCTA
BMI	1.127 (1.050–1.209)	0.001
Obstructive CAD	4.980 (2.132–11.630)	< 0.001
FAI[RCA] > − 70.1	2.874 (1.280–6.450)	0.010
B. Multivariate Cox regression model for the prediction of MACE, adjusted for cardiovascular risk factors, obstructive CAD on CCTA, and reversible perfusion defect by SPECT-MPI
BMI	1.106 (1.026–1.192)	0.008
Hypercholesterolemia	2.349 (0.945–5.837)	0.066
Obstructive CAD	4.154 (1.759–9.809)	0.001
FAI[RCA] > − 70.1	2.733 (1.220–6.123)	0.015
C. Multivariate Cox regression model for the prediction of MACE, adjusted for cardiovascular risk factors, obstructive CAD on CCTA, and reversible perfusion defect by SPECT-MPI and CACS
Hypercholesterolemia	2.790 (1.073–7.255)	0.035
Obstructive CAD	3.360 (1.137–9.926)	0.028
Reversible perfusion defect	2.478 (0.934–6.573)	0.068

A–C, the stepwise method was performed among age, body mass index (BMI), sex, previous percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG), diabetes mellitus, hypercholesterolemia, hypertension, family history of CAD, current smoking, and fat attenuation index of the right coronary artery (FAI[RCA] > − 70.1). Only variables staying in the final model are presented

CACS, coronary artery calcium score; CAD, coronary artery disease; CI, confidence interval; OR, odds ratio; SPECT, single-photon emission computed tomography; MPI, myocardial perfusion imaging; CCTA, coronary computed tomography angiography; RCA, right coronary artery