Machine-learning versus traditional methods for prediction of all-cause mortality after transcatheter aortic valve implantation: a systematic review and meta-analysis.

Journal: Open heart
PMID: 39842939

Abstract

BACKGROUND: Accurate mortality prediction following transcatheter aortic valve implantation (TAVI) is essential for mitigating risk, shared decision-making and periprocedural planning. Surgical risk models have demonstrated modest discriminative value for patients undergoing TAVI and are typically poorly calibrated, with incremental improvements seen in TAVI-specific models. Machine learning (ML) models offer an alternative risk stratification that may offer improved predictive accuracy.

Authors

  • Ammar Zaka
    Health and Information, Australia.
  • Cecil Mustafiz
    Griffith University, Brisbane, Queensland, Australia.
  • Daud Mutahar
    Bond University Faculty of Health Sciences and Medicine, Gold Coast, Queensland, Australia.
  • Shreyans Sinhal
    The University of Adelaide Faculty of Health and Medical Sciences, Adelaide, South Australia, Australia.
  • James Gorcilov
    Royal Adelaide Hospital, Adelaide, South Australia, Australia.
  • Benjamin Muston
    Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia.
  • Shaun Evans
    SA Health, Adelaide, SA, 5000, Australia.
  • Aashray Gupta
    Adelaide Medical School, The University of Adelaide, Adelaide, South Australia, Australia.
  • Brandon Stretton
    Faculty of Health and Medical Sciences, Adelaide Medical School, University of Adelaide, Adelaide, SA 5000 Australia.
  • Joshua Kovoor
    Faculty of Health and Medical Sciences, Adelaide Medical School, University of Adelaide, Adelaide, SA 5000 Australia.
  • Naim Mridha
    The Prince Charles Hospital, Chermside, Queensland, Australia.
  • Gopal Sivagangabalan
    Cardiology Department, Westmead Hospital, Westmead, New South Wales, Australia.
  • Aravinda Thiagalingam
    Westmead Hospital, Westmead, New South Wales, Australia.
  • Fabio Ramponi
    Yale School of Medicine, New Haven, Connecticut, USA.
  • Justin Chan
    Department of Neurosurgery, Keck School of Medicine of the University of Southern California, Los Angeles, California, USA.
  • Jayme Bennetts
    Monash University, Melbourne, Victoria, Australia.
  • Dale J Murdoch
    The Prince Charles Hospital, Chermside, Queensland, Australia.
  • Sarah Zaman
    Westmead Hospital, Westmead, New South Wales, Australia.
  • Clara K Chow
    The University of Sydney, Sydney Medical School, Sydney, New South Wales, Australia.
  • Rohan Jayasinghe
    Gold Coast Hospital and Health Service, Southport, Queensland, Australia.
  • Pramesh Kovoor
    University of Sydney, Westmead Hospital, Sydney, New South Wales, Australia.
  • Stephen Bacchi
    Faculty of Health and Medical Sciences, Adelaide Medical School, University of Adelaide, Adelaide, SA 5000 Australia.

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