AI-based prediction of left bundle branch block risk post-TAVI using pre-implantation clinical parameters.

Journal: Future cardiology
Published Date:

Abstract

BACKGROUND AND AIMS: Transcatheter Aortic Valve Implantation (TAVI) has revolutionized the treatment of severe aortic stenosis. Although its clinical efficacy is well established, the development of new-onset left bundle branch block (LBBB) following TAVI remains a frequent and concerning complication. This study aims to develop pre-implantation predictive models for new-onset LBBB after TAVI using both conventional machine learning (ML) algorithms and Large Language Models (LLMs).

Authors

  • Cheilas Vasileios
    Electophysiology Department, Onassis Cardiac Surgery Center, Athens, Greece.
  • Filandrianos Giorgos
    School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece.
  • Martinos Antonios
    Electophysiology Department, Onassis Cardiac Surgery Center, Athens, Greece.
  • Kostopoulou Anna
    Electophysiology Department, Onassis Cardiac Surgery Center, Athens, Greece.