AI and post-TAVI outcomes

  • Research type

    Research Study

  • Full title

    To use Artificial Intelligence to identify factors contributing to, and improve morbidity and mortality in, patients undergoing Transcatheter Aortic Valve Implantation

  • IRAS ID

    317364

  • Contact name

    Andreas Baumbach

  • Contact email

    a.baumbach@qmul.ac.uk

  • Sponsor organisation

    Queen Mary University of London, Charterhouse Square

  • Duration of Study in the UK

    0 years, 10 months, 1 days

  • Research summary

    The aortic valve of the heart can stop working properly over time, in fact it’s the commonest valve problem in the Western world. Keyhole surgery to fix it (called transcatheter aortic valve implantation operation, TAVI) is becoming more common. Like with every operation, people who have a TAVI operation are at risk from post-operative problems (e.g. having a stroke after their TAVI) or of dying after their operation.
    Aims of study – To see if computer software (Artificial Intelligence) can help reduce the chance of a patient who has had a TAVI from having a post-operative problem or dying afterwards.
    How research will be done – To use computer software to see if there are any predictors about which patients will have a problem or die after their TAVI.
    Information research will provide – To be able to tell patients who are thinking about having a TAVI if they are more likely than others also thinking about having a TAVI, to have problem or die after their TAVI. To propose theories on how this higher risk can be reduced.

  • REC name

    North East - Newcastle & North Tyneside 2 Research Ethics Committee

  • REC reference

    24/NE/0069

  • Date of REC Opinion

    15 Apr 2024

  • REC opinion

    Unfavourable Opinion