Treatment selection and long-term survival in patients aged 50 to < 75 years undergoing valve reintervention for failed surgical aortic bioprostheses: insights from the Netherlands Heart Registration

Abstract Objectives To describe real-world treatment allocation and observed long-term survival in patients aged 50 to < 75 years with failed surgical aortic bioprostheses who underwent reintervention through valve-in-valve transcatheter aortic valve implantation (ViV-TAVI) or redo surgical aortic valve replacement (redo-SAVR) in the Netherlands. Methods Patients aged 50 to < 75 years who underwent ViV-TAVI or redo-SAVR for a failing surgical bioprosthesis between 2015 and 2020 were identified from the Netherlands Heart Registration. Baseline characteristics and Dutch surgical-risk categories were compared by treatment strategy. Multivariable logistic regression was used to identify factors associated with ViV-TAVI selection. Kaplan–Meier analysis described survival, and treatment-specific Cox models explored factors associated with all-cause mortality. Results Of 345 patients, 41% underwent ViV-TAVI and 59% redo-SAVR. Patients selected for ViV-TAVI were older (median 71 vs. 67 years, p < 0.001), had higher surgical risk (EuroSCORE II: 6.2% vs. 4.6%, p = 0.014), and had a greater comorbidity burden than redo-SAVR patients. Despite these baseline risk differences, estimated survival within the ViV-TAVI cohort was 94.2% at 30 days, 89.6% at 2 years, and 74.4% at 4 years; corresponding redo-SAVR estimates were 96.1%, 89.8%, and 88.4%. Left ventricular ejection fraction ≤ 30% and chronic lung disease were associated both with ViV-TAVI selection (OR: 8.04, 95% CI: 2.16–29.92 and OR: 3.25, 95% CI: 1.53–6.92, respectively) and with all-cause mortality after redo-SAVR (HR: 15.70, 95% CI: 2.49–67.14 and HR: 4.23, 95% CI: 1.53–13.14, respectively). Conclusion In this Dutch observational registry, ViV-TAVI was predominantly selected for patients with a higher-risk clinical phenotype, while redo-SAVR was more often used in lower-risk reintervention candidates and showed higher observed long-term survival. These data describe contemporary treatment selection and prognosis but do not establish comparative superiority of either strategy.

Authors

Institutions

Publication Details

Journal
Clinical Research in Cardiology
Published
2026-10-19
DOI
https://doi.org/10.1007/s00392-026-03045-8
Primary Topic
Cardiac Valve Diseases and Treatments
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Treatment selection and long-term survival in patients aged 50 to < 75 years undergoing valve reintervention for failed surgical aortic bioprostheses: insights from the Netherlands Heart Registration

Nicolas M. Van Mieghem, Pim A.L. Tonino, Rutger-Jan M. Nuis, Michiel Voskuil et al.
Clinical Research in Cardiology
Cardiac Valve Diseases and Treatments
article

Treatment selection and long-term survival in patients aged 50 to < 75 years undergoing valve reintervention for failed surgical aortic bioprostheses: insights from the Netherlands Heart Registration

Nicolas M. Van Mieghem, Pim A.L. Tonino, Rutger-Jan M. Nuis, Michiel Voskuil, Isabella Kardys, Marijke J. C. Timmermans, Fabiano Porta, Lucas Uchoa de Assis, Arend de Weger, Jenna van Niekerk, Antigone Kostea, Rik Adrichem
article en

Abstract

Abstract Objectives To describe real-world treatment allocation and observed long-term survival in patients aged 50 to < 75 years with failed surgical aortic bioprostheses who underwent reintervention through valve-in-valve transcatheter aortic valve implantation (ViV-TAVI) or redo surgical aortic valve replacement (redo-SAVR) in the Netherlands. Methods Patients aged 50 to < 75 years who underwent ViV-TAVI or redo-SAVR for a failing surgical bioprosthesis between 2015 and 2020 were identified from the Netherlands Heart Registration. Baseline characteristics and Dutch surgical-risk categories were compared by treatment strategy. Multivariable logistic regression was used to identify factors associated with ViV-TAVI selection. Kaplan–Meier analysis described survival, and treatment-specific Cox models explored factors associated with all-cause mortality. Results Of 345 patients, 41% underwent ViV-TAVI and 59% redo-SAVR. Patients selected for ViV-TAVI were older (median 71 vs. 67 years, p < 0.001), had higher surgical risk (EuroSCORE II: 6.2% vs. 4.6%, p = 0.014), and had a greater comorbidity burden than redo-SAVR patients. Despite these baseline risk differences, estimated survival within the ViV-TAVI cohort was 94.2% at 30 days, 89.6% at 2 years, and 74.4% at 4 years; corresponding redo-SAVR estimates were 96.1%, 89.8%, and 88.4%. Left ventricular ejection fraction ≤ 30% and chronic lung disease were associated both with ViV-TAVI selection (OR: 8.04, 95% CI: 2.16–29.92 and OR: 3.25, 95% CI: 1.53–6.92, respectively) and with all-cause mortality after redo-SAVR (HR: 15.70, 95% CI: 2.49–67.14 and HR: 4.23, 95% CI: 1.53–13.14, respectively). Conclusion In this Dutch observational registry, ViV-TAVI was predominantly selected for patients with a higher-risk clinical phenotype, while redo-SAVR was more often used in lower-risk reintervention candidates and showed higher observed long-term survival. These data describe contemporary treatment selection and prognosis but do not establish comparative superiority of either strategy.

Clinical Research in Cardiology
Leiden University Medical Center (NL), Catharina Ziekenhuis (NL), Erasmus MC (NL), Medisch Centrum Leeuwarden (NL), University Medical Center Utrecht (NL), Netherlands Heart Registration (NL), Erasmus University Rotterdam (NL)
Openalex Percentile: Top 12%
Cardiac Valve Diseases and Treatments
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.