title: What We Are Learning From Transcatheter Aortic Valve Replacement Risk Prediction Models.
authors.affiliation: Division of Cardiology, Lahey Hospital & Medical Center, Burlington, Massachusetts; Harvard Clinical Research Institute, Boston, Massachusetts. Electronic address: matthew.reynolds@hcri.harvard.edu.
authors.forename: Mathew R
authors.initials: MR
authors.lastname: Reynolds
authors.affiliation: Division of Cardiac Surgery, University of British Columbia, Vancouver, British Columbia; Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
authors.forename: Jonathan C
authors.initials: JC
authors.lastname: Hong
mesh_terms: D001021:Aortic Valve / Q000601:surgery*; D001024:Aortic Valve Stenosis / Q000601:surgery; D006350:Heart Valve Prosthesis; D012306:Risk; D012307:Risk Factors; D012720:Severity of Illness Index; D065467:Transcatheter Aortic Valve Replacement; D016896:Treatment Outcome
keywords: aortic stenosis; frailty; mortality; prediction models; quality of life