Back

Pathophysiological insights into machine-learning-based subphenotypes of acute heart failure with preserved ejection fraction: a biomarker analysis of PURSUIT-HFpEF registry

25 August 2023 (10:15 - 11:00)
Organised by: Logo
Congress Presentation Part of: Acute heart failure: imaging and haemodynamic Heart Failure with Preserved Ejection Fraction (HFpEF) ESC Professional Premium Access ESC Congress 2023 European Society of Cardiology

About the speaker

Photo
Assistant Professor Yohei Sotomi

Osaka University Graduate School of Medicine, Osaka (Japan)

8 More presentations in this session

Presentation thumbnail
Is a change of the current echocardiographic red flag for left ventricular wall thickness useful in cardiac amyloidosis screening?
Professor G. Polzl (Innsbruck, AT)
Abstract Slides Video
Presentation thumbnail
Hemodynamic profile of obesity in cardiogenic shock
Doctor M. Guglin (Indianapolis, US)
Abstract Slides Video
Presentation thumbnail
Hemodynamic forces analysis using transthoracic echocardiogram in acute heart failure
Doctor V. Vassia (Turin, IT)
Abstract Slides Video
Presentation thumbnail
Exosomal preconditioning of human iPSC-derived cardiomyocytes beneficially alter cardiac electrophysiology during hypoxia.
Mr O. Rosand (Trondheim, NO)
Abstract Slides Video
Presentation thumbnail
The prognostic impact of follow-up cardiac Metaiodobenzylguanidine imaging: relation to differential trajectories in left ventricular ejection fraction after acute decompensation
Doctor K. Kayama (Nagoya, JP)
Abstract Slides Video

Access the full session

Session thumbnail
Acute heart failure: imaging and haemodynamic

The Event

Event poster

ESC Congress 2023

25 August 2023 10:15 CET
You may be interested in
thumbnail
Congress Presentation
Phenogrouping HFpEF trajectories identifies early and end-stage subtypes: a multicentre study using natural language processing
thumbnail
Congress Presentation
Phenotyping in heart failure with reduced ejection fraction - A cluster analysis
thumbnail
Congress Presentation
Machine learning-derived phenotypes in heart failure with reduced ejection fraction: clinical implications beyond LVEF

ESC 365 is supported by

novartis Explore sponsored resources
novo-nordisk Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources
novo-nordisk Explore sponsored resources