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Be Part of Research - Trial Details - Predicting Risk of Atrial Fibrillation and Association With Other Diseases

Predicting Risk of Atrial Fibrillation and Association With Other Diseases

Completed

Open to: ALL

Age: 30.0 - N/A

Medical Conditions

Atrial Fibrillation
Cardiovascular Diseases
Heart Diseases
Arrhythmias, Cardiac
Pathologic Processes
Disease


This information is provided directly by researchers, and we recognise that it isn't always easy to understand. We are working with researchers to improve the accessibility of this information. In some summaries, you may come across links to external websites. These websites will have more information to help you better understand the study.


Atrial fibrillation (AF) is a major public health issue: it is increasingly common, incurs substantial healthcare expenditure, and is associated with a range of adverse outcomes. There is rationale for the early diagnosis of AF, before the first complication occurs. Previous AF screening research is limited by low yields of new cases and strokes prevented in the screened populations. For AF screening to be clinically and cost-effective, the efficiency of identification of newly diagnosed AF needs to be improved and the intervention offered may have to extend beyond oral anticoagulation for stroke prophylaxis. Previous prediction models for incident AF have been limited by their data sources and methodologies. An accurate model that utilises existing routinely-collected data is needed to inform clinicians of patient-level risk of AF, inform national screening policy and highlight opportunities to improve patient outcomes from AF screening beyond that of only stroke prevention. The investigators will use routinely-collected hospital-linked primary care data to develop and validate a model for prediction of incident AF within a short prediction horizon, incorporating both a machine learning and traditional regression method. They will also investigate how atrial fibrillation risk is associated with other diseases and death. Using only clinical factors readily accessible in the community, the investigators will provide a method for the identification of individuals in the community who are at risk of AF, thus accelerating research assessing whether atrial fibrillation screening is clinically effective when targeted to high-risk individuals.

Start dates may differ between countries and research sites. The research team are responsible for keeping the information up-to-date.  

The recruitment start and end dates are as follows:

Nov 2020 Oct 2023

OBSERVATIONAL

Intervention Type : OTHER
Intervention Description : Development of an algorithm to predict the risk of new onset Atrial Fibrillation




You can take part if:



You may not be able to take part if:


This is in the inclusion criteria above


Below are the locations for where you can take part in the trial. Please note that not all sites may be open.

  • University of Leeds
    Leeds
    West Yorkshire
    LS2 9NL


The study is sponsored by University of Leeds and is in collaboration with British Heart Foundation; Clalit Health Services; Ben-Gurion University of the Negev.




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Read full details for Trial ID: NCT05837364
Last updated 07 May 2024

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