European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery · 2025
External Validation of Mortality Prediction Models in Japanese Transcatheter Aortic Valve Replacement Registry.
СтатьяМногоцентровое исследованиеВалидационное исследованиеНаблюдательное исследованиеНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Shibata Ryo, Seki Tomotsugu, Takeda Yuki, Iwaya Takuma, Kataoka Eisuke, Kitada Tatsuya, Takahara Motoyoshi, Tani Ryotaro, Nakamura Shunsuke, Fujimoto Tomotaka, Yashige Masaki, Takamatsu Kazuaki, Ito Nobuyasu, Kuwabara Kensuke, Nagata Yoji, Yamano Michiyo, Yamano Tetsuhiro, Nakamura Takeshi, Matoba Satoaki, Zen Kan
Аннотация
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.
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.