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Table 5 Univariate and multivariate logistic regression model for prediction of coronary atherosclerosis

From: Circulating ANGPTL3 and ANGPTL4 levels predict coronary artery atherosclerosis severity

Variable

Univariate analysis OR (95% CI)

P value

Multivariate analysis OR (95% CI)

P value

Age

0.940 (0.915-0.967)

< 0.001

0.591 (0.303-1.153)

0.123

Smoke

1.874 (1.100-3.195)

0.021

3.120 (1.440-6.757)

0.004

Diabetes mellitus

0.356 (0.177-0.716)

0.004

0.429 (0.181-1.014)

0.054

Hypertension

2.053 (1.257-3.353)

0.004

1.803 (0.916-3.551)

0.088

Overweight

0.732 (0.446-1.202)

0.217

0.926 (0.477-1.796)

0.819

CHD family history

0.708 (0.435-1.155)

0.167

1.767 (0.924-3.377)

0.085

LDL-C

1.559 (0.928-2.620)

0.093

1.198 (0.617-2.328)

0.594

HDL-C

1.472 (0.881-2.459)

0.140

1.109 (0.550-2.237)

0.773

ANGPTL3

0.138 (0.080-0.238)

< 0.001

0.189 (0.097-0.368)

< 0.001

ANGPTL4

5.181 (3.084-8.702)

< 0.001

3.625 (1.873-7.016)

< 0.001

  1. Coronary atherosclerosis: with one or more coronary stenosis 10 - 50% in diameter; BMI body mass index, Overweight BMI ≥ 24 kg/m2, CHD coronary heart diseases, LDL-C low-density lipoprotein-cholesterol, HDL-C high-density lipoprotein-cholesterol, ANGPTL angiopoietin-like proteins