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Title:

Markers of Myocardial Damage Predict Mortality in Patients With Aortic Stenosis.

Document type:
Article; Journal Article; Research Support, Non-U.S. Gov't
Author(s):
Kwak, Soongu; Everett, Russell J; Treibel, Thomas A; Yang, Seokhun; Hwang, Doyeon; Ko, Taehoon; Williams, Michelle C; Bing, Rong; Singh, Trisha; Joshi, Shruti; Lee, Heesun; Lee, Whal; Kim, Yong-Jin; Chin, Calvin W L; Fukui, Miho; Al Musa, Tarique; Rigolli, Marzia; Singh, Anvesha; Tastet, Lionel; Dobson, Laura E; Wiesemann, Stephanie; Ferreira, Vanessa M; Captur, Gabriella; Lee, Sahmin; Schulz-Menger, Jeanette; Schelbert, Erik B; Clavel, Marie-Annick; Park, Sung-Ji; Rheude, Tobias; Hadamitzky, Ma...     »
Abstract:
BACKGROUND: Cardiovascular magnetic resonance (CMR) is increasingly used for risk stratification in aortic stenosis (AS). However, the relative prognostic power of CMR markers and their respective thresholds remains undefined. OBJECTIVES: Using machine learning, the study aimed to identify prognostically important CMR markers in AS and their thresholds of mortality. METHODS: Patients with severe AS undergoing AVR (n = 440, derivation; n = 359, validation cohort) were prospectively enrolled acro...     »
Journal title abbreviation:
J Am Coll Cardiol
Year:
2021
Journal volume:
78
Journal issue:
6
Pages contribution:
545-558
Fulltext / DOI:
doi:10.1016/j.jacc.2021.05.047
Pubmed ID:
http://view.ncbi.nlm.nih.gov/pubmed/34353531
Print-ISSN:
0735-1097
TUM Institution:
Institut für Radiologie und Nuklearmedizin; Klinik für Herz- und Kreislauferkrankungen im Erwachsenenalter (Prof. Schunkert)
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