title: Clinical predictors of prosthesis-patient mismatch after aortic valve replacement for aortic stenosis.
abstract: OBJECTIVE
  We sought to ascertain predictors of Patient Prosthesis Mismatch, an independent predictor of mortality, in patients with aortic stenosis using bioprosthetic valves.
  
  
  METHODS
  We analyzed 2,107 sequential surgeries. Patient Prosthesis Mismatch was calculated using the effective orifice area of the prosthesis divided by the patient's body surface area. We defined nonsignificant, moderate, and severe Patient Prosthesis Mismatch as effective orifice area indexes of .0.85 cm(2)/m, 0.85-0.66 cm(2)/m(2), and <0.65 cm(2)/m(2), respectively.
  
  
  RESULTS
  A total of 311 bioprosthetic patients were identified. The incidence of nonsignificant, moderate, and severe Patient Prosthesis Mismatch was 41%, 42, and 16%, respectively. Severe Patient Prosthesis Mismatch was significantly more prevalent in females (82%). In severe Patient Prosthesis Mismatch, the perfusion and the crossclamp times were considerably lower when compared with nonsignificant Patient Prosthesis Mismatch and moderate Patient Prosthesis Mismatch. Patients with severe Patient Prosthesis Mismatch had a significantly higher likelihood of spending time in the intensive care unit and a significantly longer length of stay in the hospital. Body surface area was not different in severe Patient Prosthesis Mismatch when compared with nonsignificant Patient Prosthesis Mismatch. In-hospital mortality in patients with nonsignificant, moderate, and severe Patient Prosthesis Mismatch was 2.3%, 6.1%, and 8%, respectively. Minimally invasive surgery was significantly associated with moderate Patient Prosthesis Mismatch in 49% of the patients, but not with severe Patient Prosthesis Mismatch.
  
  
  CONCLUSIONS
  Severe Patient Prosthesis Mismatch is more common in females, but not in those with minimal available body surface area. Though operative times were shorter in these patients, intensive care unit and hospital lengths of stay were longer. Surgeons and cardiologists should be cognizant of these clinical predictors and complications prior to valve surgery.
authors.affiliation: Columbia University Division of Cardiology, Mount Sinai Heart Institute, Miami Beach, Florida, USA.
authors.forename: Luis M
authors.initials: LM
authors.lastname: Astudillo
authors.forename: Orlando
authors.initials: O
authors.lastname: Santana
authors.forename: Pablo A
authors.initials: PA
authors.lastname: Urbandt
authors.forename: Alexandre M
authors.initials: AM
authors.lastname: Benjo
authors.forename: Lior U
authors.initials: LU
authors.lastname: Elkayam
authors.forename: Francisco O
authors.initials: FO
authors.lastname: Nascimento
authors.forename: Gervasio A
authors.initials: GA
authors.lastname: Lamas
authors.forename: Joseph
authors.initials: J
authors.lastname: Lamelas
mesh_terms: D000368:Aged; D001021:Aortic Valve / Q000473:pathology* / Q000601:surgery; D001024:Aortic Valve Stenosis / Q000601:surgery*; D001705:Bioprosthesis; D015992:Body Mass Index; D004812:Epidemiologic Methods; D005260:Female; D006350:Heart Valve Prosthesis / Q000009:adverse effects; D019918:Heart Valve Prosthesis Implantation / Q000379:methods*; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data; D008297:Male; D017755:Prosthesis Fitting / Q000009:adverse effects* / Q000401:mortality; D012307:Risk Factors; D016896:Treatment Outcome