PARADISE

  • Research type

    Research Study

  • Full title

    Predicting AF after Cardiac Surgery - the PARADISE Score. A Clinical Prediction Rule for Post-operative Atrial Fibrillation in Patients Undergoing Cardiac Surgery

  • IRAS ID

    296508

  • Contact name

    Peter Watkinson

  • Contact email

    ccrg.research@ndcn.ox.ac.uk

  • Sponsor organisation

    University of Oxford / Clinical Trials and Research Governance

  • Duration of Study in the UK

    2 years, 0 months, 31 days

  • Research summary

    Atrial Fibrillation (AF) is a common heart problem causing an irregular heartbeat that occurs in many individuals. It may make the heart beat more rapidly and reduce the heart’s ability to pump blood to the body. It allows blood clots to form in the heart, which can cause strokes if they are pumped to the brain. Avoiding AF is important.

    People who develop AF whilst in hospital seem to stay longer in the Intensive Care Unit after surgery, are more likely to develop complications and have a higher risk of dying.

    About 30-50% of people having heart surgery develop AF shortly after the operation. Different preventative treatments such as beta blockers and amiodarone reduce the likelihood of developing AF, along with an individual’s lifestyle including what they eat and how active they are.

    Preventative treatments carry risks, so it is important to identify people most likely to benefit from them (i.e. the benefits are bigger than the risks). Currently there are no good tools (mathematical models) to predict who will get AF after heart surgery. Previous tools are not used in clinical practice, partly because there are weaknesses in how they were developed. For example, some do not include modern data like ultrasound pictures of the heart that are now routine before surgery. A modern reliable prediction model is needed.

    We will develop two reliable prediction models to identify which patients are at greatest risk of developing Atrial Fibrillation (AF) following heart surgery. One will predict the risk at assessment prior to surgery, and the second will predict who may develop AF after surgery. Two models are needed as changes during surgery may alter the risk of AF.

  • REC name

    East of England - Cambridge East Research Ethics Committee

  • REC reference

    21/EE/0166

  • Date of REC Opinion

    25 Aug 2021

  • REC opinion

    Further Information Favourable Opinion