Cited 7 times since 2018 (1.2 per year) source: EuropePMC European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery, Volume 53, Issue 6, 1 1 2018, Pages 1272-1278 Twenty-year experience with stentless biological aortic valve and root replacement: informing patients of risks and benefits. Schneider AW, Putter H, Hazekamp MG, Holman ER, Bruggemans EF, Versteegh MIM, Schalij MJ, Varkevisser RRB, Klautz RJM, Braun J
Objectives
The aim of this study was to provide predictive data on the performance of the Freestyle stentless bioprosthesis that can be used to support and improve the shared decision-making process of prosthetic valve choice for aortic valve replacement.
Methods
Between 1993 and 2014, 604 patients received the Freestyle stentless bioprosthesis (143 subcoronary, 58 root inclusion and 403 full-root replacement). Perioperative data were collected retrospectively, and follow-up data were collected prospectively from 2015. Follow-up was 96% complete (median 4.3 years), with 114 (19%) patients having a follow-up period exceeding 10 years. A competing risks regression model was developed to predict the probability of mortality, structural valve deterioration (SVD) and reoperation for other causes than SVD.
Results
The median age of patients was 64 years, 91 (15%) patients had undergone previous aortic valve replacement and 351 (58%) underwent concomitant procedures. The 15-year probability of SVD, reoperation for other causes and death were 16.9%, 8.1% and 47.7%, respectively. Linearized occurrence rates for prosthesis endocarditis, thromboembolic events and bleeding were 0.5%, 0.9% and 0.1% per patient-year, respectively. The constructed predictive model, including age, renal function and implantation technique as significant covariates, had good to fair predictive performance up to 19 years.
Conclusions
The Freestyle stentless bioprosthesis is an efficient prosthesis for aortic valve replacement or root replacement, with low incidences of SVD and valve-related events at long-term follow-up. The predictive model designed in this study can be used to fully inform patients about their expected individual trajectory after implantation of this prosthesis. This improves the shared decision-making process between patients and clinicians.
