Division of Cardiology, Pulmonology and Vascular Medicine, Department of Internal Medicine, Heinrich Heine University, Medical Faculty, Moorenstr. 5, 40225, Düsseldorf, Germany.
Department of Medicine II, Heart Center Bonn, University Hospital Bonn, Bonn, Germany.
Clin Res Cardiol. 2021 Mar;110(3):368-376. doi: 10.1007/s00392-020-01731-9. Epub 2020 Aug 26.
Surgical risk prediction models are routinely used to guide decision-making for transcatheter aortic valve replacement (TAVR). New and updated TAVR-specific models have been developed to improve risk stratification; however, the best option remains unknown.
To perform a comparative validation study of six risk models for the prediction of 30-day mortality in TAVR METHODS AND RESULTS: A total of 2946 patients undergoing transfemoral (TF, n = 2625) or transapical (TA, n = 321) TAVR from 2008 to 2018 from the German Rhine Transregio Aortic Diseases cohort were included. Six surgical and TAVR-specific risk scoring models (LogES I, ES II, STS PROM, FRANCE-2, OBSERVANT, GAVS-II) were evaluated for the prediction of 30-day mortality. Observed 30-day mortality was 3.7% (TF 3.2%; TA 7.5%), mean 30-day mortality risk prediction varied from 5.8 ± 5.0% (OBSERVANT) to 23.4 ± 15.9% (LogES I). Discrimination performance (ROC analysis, c-indices) ranged from 0.60 (OBSERVANT) to 0.67 (STS PROM), without significant differences between models, between TF or TA approach or over time. STS PROM discriminated numerically best in TF TAVR (c-index 0.66; range of c-indices 0.60 to 0.66); performance was very similar in TA TAVR (LogES I, ES II, FRANCE-2 and GAVS-II all with c-index 0.67). Regarding calibration, all risk scoring models-especially LogES I-overestimated mortality risk, especially in high-risk patients.
Surgical as well as TAVR-specific risk scoring models showed mediocre performance in prediction of 30-day mortality risk for TAVR in the German Rhine Transregio Aortic Diseases cohort. Development of new or updated risk models is necessary to improve risk stratification.
外科风险预测模型常用于指导经导管主动脉瓣置换术（TAVR）的决策。已经开发了新的和更新的 TAVR 特定模型来改善风险分层；然而，最佳选择仍不清楚。
对六种用于预测 TAVR 30 天死亡率的风险模型进行比较验证研究。
共纳入 2008 年至 2018 年期间来自德国莱茵河主动脉疾病队列的 2946 例经股（TF，n=2625）或经心尖（TA，n=321）TAVR 患者。评估了六种外科和 TAVR 特定的风险评分模型（LogES I、ES II、STS PROM、FRANCE-2、OBSERVANT、GAVS-II）对 30 天死亡率的预测。观察到 30 天死亡率为 3.7%（TF 为 3.2%；TA 为 7.5%），平均 30 天死亡率风险预测从 5.8%±5.0%（OBSERVANT）到 23.4%±15.9%（LogES I）不等。区分性能（ROC 分析，c 指数）范围为 0.60（OBSERVANT）至 0.67（STS PROM），模型之间、TF 或 TA 方法之间或随时间推移均无显著差异。STS PROM 在 TF TAVR 中数字上区分度最好（c 指数 0.66；c 指数范围为 0.60 至 0.66）；TA TAVR 中的性能非常相似（LogES I、ES II、FRANCE-2 和 GAVS-II 的 c 指数均为 0.67）。关于校准，所有风险评分模型，尤其是 LogES I，高估了 TAVR 30 天死亡率风险，尤其是在高危患者中。
在德国莱茵河主动脉疾病队列中，外科和 TAVR 特定的风险评分模型在预测 TAVR 30 天死亡率风险方面表现不佳。需要开发新的或更新的风险模型来改善风险分层。
