Continuously Iterative Perioperative Holistic Evaluation of Risk and Hypotension Prediction Index

It is known that some patients have a prolonged and difficult recovery after major surgery, which impacts their long-term health and wellbeing. A major issue is that scores for predicting recovery are typically generated only once in the period before surgery, but subsequent events during and immediately after surgery can also alter the likelihood of a prolonged and difficult recovery.

One such event appears to be low blood pressure (hypotension). Hypotension Prediction Index can be calculated from routine blood pressure measurements, and is an indicator of blood pressure instability. The investigators propose that Hypotension Prediction Index during and immediately after surgery may be used to improve their accuracy of scores that predict postoperative problems.

To explore this, the investigators will collect information about the health and care needs, surgery and postoperative recovery of adult patients' requiring major surgery. This data will be taken from hospital information systems, a bedside monitor, test reports, a questionnaire and National Databases. The investigators will then use statistical models to determine whether Hypotension Prediction Index improves the accuracy of preoperative scores for predicting postoperative problems.

Ultimately, the investigators hope to create a tool for predicting how well a patient will recover based on the information available at any given point in time. Healthcare professionals will be able to use this tool to identify and support the needs of patients who need extra help recovering from major surgery.