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. Author manuscript; available in PMC: 2022 Dec 8.
Published in final edited form as: Circ Cardiovasc Imaging. 2021 Dec 8;14(12):1100–1108. doi: 10.1161/CIRCIMAGING.121.013075

Table 5:

Univariable Cox Model for Predictors of Incident Cardiovascular events

HR (95% CI) p
COA mean gradient, per 1 mmHg 1.26 (0748–2.54) 0.5
Aortic mean gradient, per 1 mmHg 1.08 (0.91–1.12) 0.3
LV GLS, per unit increment 0.91 (0.85–0.97) 0.008
LV mass index, per 5 g/m2 1.11 (1.02–1.25) 0.009
Atrial fibrillation 2.02 (1.28–4.04) <0.001
Hypertension 1.53 (1.18–2.33) 0.01
Coronary artery disease 1.96 (1.24–4.16) 0.004
GFR, per 5-unit increment 0.93 (0.84–1.01) 0.06
COA intervention* 1.42 (0.81–1.83) 0.5
Age at time of COA repair, years 1.03 (0.89–1.21) 0.4
LVOT intervention 0.92 (0.80–1.06) 0.3
Mitral valve intervention 1.31 (0.92–1.74) 0.4

COA: Coarctation of aorta; LV: Left ventricle; GLS: Global longitudinal strain; GFR: Glomerular filtration rate; HR: Hazard rate; CI: Confidence interval, LVOT: Left ventricular outflow tract

COA intervention* denotes surgical COA repair or transcatheter intervention; LVOT intervention† denotes surgical resection of subaortic stenosis or aortic valve replacement; Mitral valve intervention‡ denotes mitral valve repair or replacement

The variables with p<0.25 were then used to create the multivariable Cox model in Table 6