Machine learning-based prediction of 1-year all-cause mortality in patients undergoing CRT implantation: validation of the SEMMELWEIS-CRT score in the European CRT Survey I dataset.

Autor:	Tokodi M; Heart and Vascular Centre, Semmelweis University, 68 Városmajor Street, 1122 Budapest, Hungary.; Department of Surgical Research and Techniques, Semmelweis University, 68 Városmajor Street, 1122 Budapest, Hungary., Kosztin A; Heart and Vascular Centre, Semmelweis University, 68 Városmajor Street, 1122 Budapest, Hungary., Kovács A; Heart and Vascular Centre, Semmelweis University, 68 Városmajor Street, 1122 Budapest, Hungary.; Department of Surgical Research and Techniques, Semmelweis University, 68 Városmajor Street, 1122 Budapest, Hungary., Gellér L; Heart and Vascular Centre, Semmelweis University, 68 Városmajor Street, 1122 Budapest, Hungary., Schwertner WR; Heart and Vascular Centre, Semmelweis University, 68 Városmajor Street, 1122 Budapest, Hungary., Veres B; Heart and Vascular Centre, Semmelweis University, 68 Városmajor Street, 1122 Budapest, Hungary., Behon A; Heart and Vascular Centre, Semmelweis University, 68 Városmajor Street, 1122 Budapest, Hungary., Lober C; Institut für Herzinfarktforschung, Ludwigshafen, Germany., Bogale N; Department of Heart Disease, Haukeland University Hospital, Bergen, Norway., Linde C; Division of Cardiology, Department of Medicine, Karolinska Institutet, Stockholm, Sweden., Normand C; Cardiology Division, Stavanger University Hospital, Stavanger, Norway.; Department of Quality and Health Technology, University of Stavanger, Stavanger, Norway., Dickstein K; Cardiology Division, Stavanger University Hospital, Stavanger, Norway.; Institute of Internal Medicine, University of Bergen, Bergen, Norway., Merkely B; Heart and Vascular Centre, Semmelweis University, 68 Városmajor Street, 1122 Budapest, Hungary.
Jazyk:	angličtina
Zdroj:	European heart journal. Digital health [Eur Heart J Digit Health] 2024 Jul 12; Vol. 5 (5), pp. 563-571. Date of Electronic Publication: 2024 Jul 12 (Print Publication: 2024).
DOI:	10.1093/ehjdh/ztae051
Abstrakt:	Aims: We aimed to externally validate the SEMMELWEIS-CRT score for predicting 1-year all-cause mortality in the European Cardiac Resynchronization Therapy (CRT) Survey I dataset-a large multi-centre cohort of patients undergoing CRT implantation. Methods and Results: The SEMMELWEIS-CRT score is a machine learning-based tool trained for predicting all-cause mortality in patients undergoing CRT implantation. This tool demonstrated impressive performance during internal validation but has not yet been validated externally. To this end, we applied it to the data of 1367 patients from the European CRT Survey I dataset. The SEMMELWEIS-CRT predicted 1-year mortality with an area under the receiver operating characteristic curve (AUC) of 0.729 (0.682-0.776), which concurred with the performance measured during internal validation [AUC: 0.768 (0.674-0.861), P = 0.466]. Moreover, the SEMMELWEIS-CRT score outperformed multiple conventional statistics-based risk scores, and we demonstrated that a higher predicted probability is not only associated with a higher risk of death [odds ratio (OR): 1.081 (1.061-1.101), P < 0.001] but also with an increased risk of hospitalizations for any cause [OR: 1.013 (1.002-1.025), P = 0.020] or for heart failure [OR: 1.033 (1.015-1.052), P < 0.001], a less than 5% improvement in left ventricular ejection fraction [OR: 1.033 (1.021-1.047), P < 0.001], and lack of improvement in New York Heart Association functional class compared with baseline [OR: 1.018 (1.006-1.029), P = 0.003]. Conclusion: In the European CRT Survey I dataset, the SEMMELWEIS-CRT score predicted 1-year all-cause mortality with good discriminatory power, which confirms the generalizability and demonstrates the potential clinical utility of this machine learning-based risk stratification tool. Competing Interests: Conflict of interest: M.T. was a former employee of Argus Cognitive. M.T. has also received consulting fees from CardioSight, outside the submitted work. A.Kosz. has received consulting fees from Medtronic and Biotronik and personal fees from Biotronik, Boehringer Ingelheim, Boston Scientific, AstraZeneca, Bayer, and Novartis, outside the submitted work. A.Kov. has received personal fees from Argus Cognitive and CardioSight, outside the submitted work. L.G. has received lecture fees from Medtronic, Biotronik, Johnson & Johnson Medical, and Abbott, outside the submitted work. C.L. has received research support from the Swedish Heart-Lung Foundation, Swedish Royal Society of Science, Stockholm County Council, consulting fees from AstraZeneca, Roche Diagnostics, speaker honoraria from Novartis, Astra, Bayer, Vifor Pharma, Medtronic, and Impulse Dynamics and has served on advisory boards for AstraZeneca. B.M. has received personal fees from Biotronik, Boehringer Ingelheim, Abbott, AstraZeneca, and Novartis, as well as grants from Medtronic, outside the submitted work. Other authors declare that they have no conflicts of interest regarding this manuscript. (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu