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Title:

Automatic ECG-based detection of left ventricular hypertrophy and its predictive value in haemodialysis patients.

Document type:
Journal Article; Research Support, Non-U.S. Gov't
Author(s):
Letz, Theresa; Hörandtner, Carina; Braunisch, Matthias C; Gundel, Peter; Matschkal, Julia; Bachler, Martin; Lorenz, Georg; Körner, Andreas; Schaller, Carolin; Lattermann, Moritz; Holzinger, Andreas; Heemann, Uwe; Wassertheurer, Siegfried; Schmaderer, Christoph; Mayer, Christopher C
Abstract:
Objective.Left ventricular hypertrophy (LVH) is one of the most severe risk factors in patients with end-stage kidney disease (ESKD) regarding all-cause and cardiovascular mortality. It contributes to the risk of sudden cardiac death which accounts for approximately 25% of deaths in ESKD patients. Electrocardiography (ECG) is the least expensive way to assess whether a patient has LVH, but manual annotation is cumbersome. Thus, an automated approach has been developed to derive ECG-based LVH par...     »
Journal title abbreviation:
Physiol Meas
Year:
2023
Journal volume:
44
Journal issue:
7
Fulltext / DOI:
doi:10.1088/1361-6579/acdfb3
Pubmed ID:
http://view.ncbi.nlm.nih.gov/pubmed/37336235
Print-ISSN:
0967-3334
TUM Institution:
Professur für Nephrologie (Prof. Heemann)
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