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NCT04657900

Predicting Patient-level New Onset Atrial Fibrillation

Completed Last updated 8 May 2024
What this trial tests

trial testing Observational in Atrial Fibrillation in 140,000 participants. Completed in 31 October 2023.

Timeline
2 November 2020
Primary endpoint
31 October 2023
31 October 2023

Quick facts

Lead sponsorUniversity of Leeds
StatusCompleted
Study typeOBSERVATIONAL
Enrollment140,000
Start date2 November 2020
Primary completion31 October 2023
Estimated completion31 October 2023
Sites1 location across United Kingdom

Drugs / interventions tested

Conditions studied

Sponsor

University of Leeds

Who can join

18 and older, any sex, with Atrial Fibrillation. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

Atrial fibrillation (AF) is a major cardiovascular health problem: it is common, chronic and incurs substantial health-care expenditure as a result of stroke, sudden death, heart failure and unplanned hospitalisation. There is a compelling argument for the early diagnosis of AF, before the first complication occurs, but population-based screening is not recommended. Strategies to identify individuals at higher risk of new onset AF are required. previous risk scores have been limited by data and methodology. The investigators will use routinely collected hospital-linked primary care data and focus on the use of artificial intelligence methods to develop and validate a model for the prediction of incident AF. Specifically, the investigators will investigate how population-based data may be used for precision medicine using a deep neural networks learning model. Using clinical factors readily accessible in primary care, the investigators will provide a method for the identification of individuals in the community who are at risk of AF, as well as when incident AF will occur in those at risk, thus accelerating research assessing technologies for the improvement of risk prediction, and the targeting of high-risk individuals for preventive measures and screening.

Publications & conference data

2 peer-reviewed publications reference this trial (live from Europe PMC):

  1. Predicting patient-level new-onset atrial fibrillation from population-based nationwide electronic health records: protocol of FIND-AF for developing a precision medicine prediction model using artificial intelligence.
    Nadarajah R, Wu J, Frangi AF, Hogg D, et al · · 2021 · cited 20× · PMID 34728455 · DOI 10.1136/bmjopen-2021-052887
  2. What is next for screening for undiagnosed atrial fibrillation? Artificial intelligence may hold the key.
    Nadarajah R, Wu J, Frangi AF, Hogg D, et al · · 2022 · cited 4× · PMID 34940849 · DOI 10.1093/ehjqcco/qcab094

Verify or expand the search:

Other trials of Observational

Trials testing the same drug.

Other recruiting trials for Atrial Fibrillation

Currently open trials in the same condition.

Other University of Leeds trials

Trials by the same sponsor.

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Data sources for this page

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Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing