Abstract Aims Echocardiographic global longitudinal strain (GLS) and mechanical dispersion (MD) improve risk prediction in heart failure. To facilitate clinical implementation, we aimed to develop...
<p><strong>Tác giả:</strong> Daniela Melichova, John Nyberg, Thuy Mi Nguyen, Ivar Mjåland Salte, Øyvind Olav Salvesen, Håvard Dalen, Lasse Løvstakken, Harald Brunvand, Kristina Hermann Haugaa, Thor Edvardsen, Andreas Østvik, Bjørnar Leangen Grenne</p>
<p>Abstract Aims Echocardiographic global longitudinal strain (GLS) and mechanical dispersion (MD) improve risk prediction in heart failure. To facilitate clinical implementation, we aimed to develop a deep learning-based method for fast, fully automated GLS and MD and validate its ability to predict ventricular arrhythmia (VA) and all-cause mortality. Methods and results This prospective observational study included 568 patients (73 ± 13 years, 67% male) with first diagnosis of heart failure an...</p>
<p>📄 DOI: <a href="https://doi.org/https://doi.org/10.1093/ehjimp/qyag178" target="_blank" rel="noopener">https://doi.org/10.1093/ehjimp/qyag178</a></p>
<p>📖 <a href="https://doi.org/https://doi.org/10.1093/ehjimp/qyag178" target="_blank" rel="noopener">Xem bài báo đầy đủ</a></p>
Bài viết được biên soạn lại bởi LIFVietnam. Nguồn tham khảo: OpenAlex