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Updated: Sep 16, 2025
Upper-extremity Approach for Secondary Access in Transfemoral Transcatheter Aortic Valve Implantation
Published on: August 8, 2025
External Validation of Mortality Prediction Models in Japanese Transcatheter Aortic Valve Replacement Registry
Ryo Shibata1, Tomotsugu Seki1,2, Yuki Takeda1
1Department of Cardiology, Kyoto Prefectural University of Medicine, Kyoto, 602-8566, Japan.
Objectives:
Mortality prediction models (MPMs) play a crucial role in risk assessment for transcatheter aortic valve replacement (TAVR), but their external validity in Japanese patients remains unclear. This study evaluated the performance of existing short-term (30-day) and long-term (1-year) MPMs with Japanese TAVR patients.
Methods:
We analysed patients who underwent TAVR between 2016 and 2023 in the KPUM transcatheter aortic valve implantation (TAVI) registry, a prospective multicentre registry in Japan. Five short-term (30-day) MPMs (Society of Thoracic Surgeons Predicted Risk of Mortality [STS-PRoM], French Aortic National CoreValve and Edwards registry [FRANCE-2], Observational Study Of Appropriateness, Efficacy And Effectiveness of AVR-TAVR Procedures For the Treatment Of Severe Symptomatic Aortic Stenosis registry [OBSERVANT], American College of Cardiology-TAVI [ACC-TAVI], and Netherlands Heart Registration [NHR] models) and 3 long-term (1-year) MPMs (Optimized CathEter vAlvular iNtervention-TAVI [OCEAN-TAVI], Osaka University, and TAVR-Risk [TARI] models) were validated. Model performance was assessed using the area under the receiver operating characteristic curve (AU-ROC) for discrimination and calibration plots/slope/intercept for calibration. Intercept recalibration was performed for short-term MPMs.
Results:
Among 1756 patients analysed for short-term mortality, the mortality risk was 1.4% (n = 25), while among 1235 patients analysed for long-term mortality, the mortality risk was 14.5% (n = 179), respectively. Among short-term MPMs, NHR (AU-ROC: 0.82) and STS-PRoM (0.78) showed the highest discrimination, though all models overestimated mortality risk, which improved after intercept recalibration. Among long-term MPMs, the OCEAN-TAVI and Osaka University models (AU-ROC: 0.75) showed the highest discrimination, with the OCEAN-TAVI demonstrating the best calibration.
Conclusions:
In Japanese TAVR patients, STS-PRoM and NHR models showed superior short-term performance after recalibration, while OCEAN-TAVI demonstrated the best overall long-term performance. Future research should explore machine learning-based models to improve risk prediction accuracy and clinical applicability.
Insights
The Society of Thoracic Surgeons Predicted Risk of Mortality (STS-PRoM) and Netherlands Heart Registration (NHR) models showed the best short-term performance in Japanese transcatheter aortic valve replacement (TAVR) patients. The Optimized CathEter vAlvular iNtervention-TAVI (OCEAN-TAVI) model demonstrated the best long-term performance.
Area of Science:
- Cardiovascular Medicine
- Medical Statistics
- Health Services Research
Background:
- Mortality prediction models (MPMs) are vital for assessing transcatheter aortic valve replacement (TAVR) risk.
- The external validity of existing MPMs in Japanese TAVR populations is not well-established.
- This study aimed to validate short-term and long-term MPMs in Japanese TAVR patients.
Purpose of the Study:
- To evaluate the performance of established short-term (30-day) and long-term (1-year) mortality prediction models in a Japanese cohort undergoing TAVR.
- To assess the discrimination and calibration of these models using data from a prospective multicentre registry.
- To identify the most accurate models for risk stratification in this specific patient population.
Main Methods:
- Analysis of 1756 patients for short-term and 1235 patients for long-term mortality from the KPUM TAVI registry (2016-2023).
- Validation of five short-term MPMs (STS-PRoM, FRANCE-2, OBSERVANT, ACC-TAVI, NHR) and three long-term MPMs (OCEAN-TAVI, Osaka University, TARI).
- Performance assessment using Area Under the Receiver Operating Characteristic Curve (AU-ROC) for discrimination and calibration metrics; intercept recalibration applied to short-term models.
Main Results:
- Short-term mortality was 1.4% (25/1756), and long-term mortality was 14.5% (179/1235).
- For short-term mortality, NHR (AU-ROC: 0.82) and STS-PRoM (0.78) exhibited the highest discrimination; all models initially overestimated risk, improving post-recalibration.
- For long-term mortality, OCEAN-TAVI and Osaka University models showed the highest discrimination (AU-ROC: 0.75), with OCEAN-TAVI demonstrating superior calibration.
Conclusions:
- The STS-PRoM and NHR models demonstrated superior short-term predictive performance in Japanese TAVR patients following recalibration.
- The OCEAN-TAVI model exhibited the best overall long-term performance and calibration in this cohort.
- Future research should investigate machine learning-based models to enhance the accuracy and clinical utility of TAVR risk prediction.
