Clinical trial NCT05255224: PARADISE: Predicting AF After Cardiac Surgery
Official title: Predicting AF After Cardiac Surgery - the PARADISE Score. A Clinical Prediction Rule for Post-operative Atrial Fibrillation in Patients Undergoing Cardiac Surgery
Study type: OBSERVATIONAL
Overall status: ACTIVE_NOT_RECRUITING
Conditions: Atrial Fibrillation New Onset
Keywords: New Onset Atrial Fibrillation
Cardiac Surgery
Lead sponsor: University of Oxford
Sponsor class: OTHER
Collaborators: name: St. Bartholomew's Hospital
name: University College, London
name: Liverpool Heart and Chest Hospital NHS Foundation Trust
name: Brigham and Women's Hospital
name: Oxford University Hospitals NHS Trust
First posted: 2022-02-24
Enrollment: 13684
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: OTHER
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients who have undergone cardiac surgery

Brief summary: The PARADISE study aims to develop and validate prediction tools to identify patients at risk of Atrial Fibrillation (AF) after cardiac surgery.

Detailed description: Atrial Fibrillation (AF) is a common abnormal heart rhythm. AF causes the heart to beat irregularly and sometimes very rapidly. About 30-50% of patients develop AF after heart surgery. These patients stay longer on the Intensive Care Unit (ICU) after surgery, are more likely to develop complications and have a higher risk of dying. Avoiding AF is important.

Some drugs, including beta blockers and amiodarone may help prevent AF if given after surgery. However, these may also lead to complications (such as lung damage). It is therefore important to identify which patients are most likely to benefit from these treatments (i.e., where the benefits outweigh the risks). There are existing tools designed to predict the risk of suffering AF after heart surgery. However, they are unreliable and therefore not used in clinical practice. A modern, reliable risk prediction tool is needed.

The PARADISE study will develop and test new prediction tools to identify which patients are most at risk of developing AF after heart surgery. The investigators will focus our tools on those patients who most commonly develop AF, such as those who have had surgery to repair a valve or blood vessel in their heart.

To do this the investigators will:

* Review the medical literature and assemble a panel of medical experts to create a list of known factors that affect patients' risk of AF after heart surgery
* Use a large UK general practice database (CALIBER) to see whether the investigators can find new risk factors.
* Ask the expert panel to agree a list of known and new risks factors to be included in the prediction tool.
* Develop two new prediction tools using an existing American cardiac surgery database (the Partners research Database). The first will be used before surgery, the second immediately following surgery. Two models are needed as events during surgery may alter the risk of AF.
* Test how reliably our new tools predict which patients suffer AF after surgery, with data from large UK (United Kingdom) NHS (National Health Service) heart centres, one US Hospital (Brigham) and a UK clinical trial (Tight-K).
* The investigators will work with two charities (AF Alliance and StopAfib) to share our results with patients and the wider public.

Eligibility criteria: Inclusion Criteria:

* Patients 18 years or over
* Admitted to hospital for any cardiac surgery

Exclusion Criteria:

* Patients who have requested that their data not be used for research (e.g. NHS Opt-out)

Primary outcomes:
measure: Model discrimination (c-statistic) to predict Atrial Fibrillation in external data set
timeFrame: Within 7 days of cardiac surgery
measure: Model calibration (intercept) to predict Atrial Fibrillation in external data set
timeFrame: Within 7 days of cardiac surgery
measure: Model calibration (slope) to predict Atrial Fibrillation in external data set
timeFrame: Within 7 days of cardiac surgery
Secondary outcomes:
measure: Additional model performance metrics to predict Atrial Fibrillation in external data set
timeFrame: Within 7 days of cardiac surgery
measure: Candidate risk factors for inclusion in new onset atrial fibrillation prognostic models
timeFrame: Within 7 days of cardiac surgery
Other outcomes:
Locations:
city: Oxford
country: United Kingdom
facility: Critical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford
state: Oxfordshire
Study officials:
affiliation: University of Oxford
name: Peter Watkinson, MD
role: PRINCIPAL_INVESTIGATOR
affiliation: Deutsches Herzzentrum der Charité
name: Benjamin O'Brien, MD
role: PRINCIPAL_INVESTIGATOR
References: