Georg Wolff1, Jasmin Shamekhi2, Baravan Al-Kassou2, Noriaki Tabata2, Claudio Parco3, Kathrin Klein3, Oliver Maier3, Alexander Sedaghat2, Amin Polzin3, Atsushi Sugiura2, Christian Jung3, Eberhard Grube2, Ralf Westenfeld3, Andrea Icks4, Tobias Zeus3, Jan-Malte Sinning2,5, Stephan Baldus6,5, Georg Nickenig2,5, Malte Kelm3,5, Verena Veulemans3. 1. Division of Cardiology, Pulmonology and Vascular Medicine, Department of Internal Medicine, Heinrich Heine University, Medical Faculty, Moorenstr. 5, 40225, Düsseldorf, Germany. Georg.Wolff@med.uni-duesseldorf.de. 2. Department of Medicine II, Heart Center Bonn, University Hospital Bonn, Bonn, Germany. 3. Division of Cardiology, Pulmonology and Vascular Medicine, Department of Internal Medicine, Heinrich Heine University, Medical Faculty, Moorenstr. 5, 40225, Düsseldorf, Germany. 4. Institute for Health Services Research and Health Economics, Centre for Health and Society, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany. 5. Transregio 259: Aortic Diseases-Scientific Network of University Heart Centers in Düsseldorf/Bonn/Cologne, Düsseldorf/Bonn/Cologne, Germany. 6. Division of Cardiology, Pneumology, Angiology and Intensive Care, Department of Internal Medicine III, University of Cologne, Cologne, Germany.
Abstract
BACKGROUND: 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. OBJECTIVE: 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. CONCLUSIONS: 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.
BACKGROUND: 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. OBJECTIVE: 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. CONCLUSIONS: 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.
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