Table 2.

Logistic regression analysis to predict severe CAD.

Variables	Model 1: No adjustment		Model 2: Age and sex-adjusted		Model 3: Multivariate
	OR (95%CI)	P	OR (95%CI)	P	OR (95%CI)	P
Age	0.995 (0.978–1.012)	0.546	-	-	-	-
Male vs. Female	2.253 (1.521–3.336)	<0.001	-	-	1.658 (1.048–2.624)	0.031
Smoking	1.680 (1.169–2.416)	0.005	1.204 (0.791–1.833)	0.385	-	-
Diabetes	2.487 (1.706–3.627)	<0.001	2.550 (1.733–3.751)	<0.001	2.444 (1.509–3.958)	<0.001
TG	1.323 (1.101–1.590)	0.003	1.340 (1.109–1.620)	0.002	1.182 (0.947–1.475)	0.139
HDL-C	0.149 (0.069–0.318)	<0.001	0.184 (0.082–0.412)	<0.001	0.232 (0.091–0.593)	0.002
Scr	1.009 (1.000–1.019)	0.057	1.004 (0.995–1.012)	0.391	-	-
FBG	1.126 (1.040–1.219)	0.004	1.146 (1.056–1.243)	0.001	1.002 (0.909–1.104)	0.971
hsTnI	1.004 (1.000–1.008)	0.071	1.000(1.000–1.001)	0.210	-	-
hsCRP	0.987 (0.932–1.046)	0.667	0.984 (0.928–1.044)	0.597	-	-
IL-4	0.750 (0.607–0.927)	0.008	0.747 (0.605–0.923)	0.007	0.971 (0.750–1.256)	0.820
IL-12p70	0.551 (0.452–0.672)	<0.001	0.566 (0.464–0.691)	<0.001	0.572 (0.454–0.720)	<0.001
IL-17	0.907 (0.870–0.946)	<0.001	0.913 (0.876–0.952)	<0.001	0.930 (0.886–0.976)	0.003
IFN-α	0.840 (0.750–0.942)	0.003	0.837 (0.746–0.939)	0.002	0.977 (0.848–1.124)	0.741

The dependent variable of logistics regression is whether patients have severe CAD, and the independent variables are age, sex, BMI, smoking, diabetes, TG, HDL-C, Scr, FBG, hsTnI, hsCRP, IL-4, IL-12p70, IL-17, IFN-α.

Model 1: Univariate logistic regression.

Model 2: Logistic regression after adjusted age and gender.

Model 3: Parameters with p <0.05 in Model 2 were subsequently entered into multivariate regression analysis.

Bold values signifies the statistical significance in logistics regression.