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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