Risk modelling in cardiac surgery patients
Research type
Research Study
Full title
Prediction models using perioperative data for post-procedural support
IRAS ID
357892
Contact name
Ceri Jones
Contact email
Sponsor organisation
University Hospital Southampton NHS Foundation Trust
Duration of Study in the UK
2 years, 0 months, 0 days
Research summary
The ability to reliably predict post-operative mortality and morbidity in patients undergoing cardiac surgery helps support shared decision making and risk stratification. This is especially important to clinicians when attempting to determine the most appropriate treatment option for each patient. The application of clinical prediction models (CPMs) in cardiac surgery has helped to improve patient selection and risk-adjusted performance measurement, and has been a key feature in both institutional benchmarking and quality improvement programmes. CPMs developed to predict post-operative outcomes in patients undergoing cardiac surgery have typically used pre-operative variables only, because they are primarily used as part of the pre-operative decision-making process. Several CPMs for cardiac surgery that include intra-operative variables have previously been developed but none are widely used in clinical practice. The objective of this study is to evaluate existing models for performance and fit using the Southampton cardiac surgical patient population. We are also developing a new model, potentially in Southampton data and validating it with Manchester data.
REC name
North of Scotland Research Ethics Committee 2
REC reference
25/NS/0116
Date of REC Opinion
25 Sep 2025
REC opinion
Favourable Opinion