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Table 1 Patient characteristics

From: Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification

 

Overall (n = 190)

Clinical

 Age (years)

57 ± 12

 Male gender

87% (165)

 Body surface area

2.0 ± 0.2

 Coronary Artery Disease Risk Factors

 

  Hypertension

47% (90)

   Hypercholesterolemia

54% (102)

  Diabetes mellitus

28% (53)

  Tobacco use

35% (66)

  Family history

30% (56)

 Cardiovascular Medications

 

  Beta-blocker

91% (173)

  ACEI/ARB

60% (113)

  Loop diuretic

15% (28)

  Statin

93% (177)

  Aspirin

98% (186)

  Thienopyridine

83% (158)

  Warfarin

5% (9)

  Nitroglycerin

13% (25)

Cardiac morphology/function

 Left Ventricle

  Ejection fraction (%)

52.2 ± 13.3

  LV dysfunction (EF < = 55%)

55% (105)

  End-diastolic volume (ml)

161.9 ± 49.2

  End-systolic volume (ml)

81.6 ± 46.4

  Myocardial mass (g)

137.9 ± 38.2

  Late gadolinium enhancement (present)

98% (186)

  Infarct size (% myocardium)

14.5 ± 10.4

 Aortic Valve

  Bileaflet

2% (3)

  Thickening/ fibrocalcific changes

12% (23)

  Stenosis

2% (4)

  Regurgitation

7% (13)

  1. ACEI angiotensin converting enzyme inhibitor, ARB angiotensive receptor blocker