FIND-AF Study: Understanding Atrial Fibrillation Risk
Author Information
Author(s): Wahab Ali, Nadarajah Ramesh, Reynolds Catherine, Bennett Sheena, Ambakederemo Edisemi, Harris Mohammad, Younsi Tanina, Joseph Tobin, Raveendra Keerthenan, Smith Adam, Bhatty Asad, Lip Gregory Y H, Swoboda Peter P, Wu Jianhua, Gale Chris P
Primary Institution: University of Leeds
Hypothesis
The FIND-AF longitudinal cohort study aims to characterize individuals at risk of atrial fibrillation and understand the impact of comorbidities on AF genesis.
Conclusion
The FIND-AF study will provide insights into preventing atrial fibrillation and may serve as a platform for future clinical trials.
Supporting Evidence
- The FIND-AF algorithm accurately predicts the risk of atrial fibrillation.
- Participants will undergo home-based ECG monitoring to assess their heart health.
- The study aims to recruit 1955 participants to understand atrial fibrillation better.
- Multi-modal phenotyping will include physical exams and imaging techniques.
- Longitudinal data will be collected to track health outcomes over time.
Takeaway
This study is like a big health check for people who might get a heart problem called atrial fibrillation, helping doctors find ways to stop it before it starts.
Methodology
Participants aged 30 and above at risk of atrial fibrillation will be recruited for home-based ECG monitoring and multi-modal phenotypic characterization.
Potential Biases
There is a risk of selection bias as participants may decline recruitment into a randomized controlled trial after entering the observational cohort.
Limitations
The study may face limitations such as a relatively small sample size and potential selection bias during recruitment.
Participant Demographics
Participants are aged 30 years and above, without known atrial fibrillation, and eligible for oral anticoagulation.
Statistical Information
P-Value
<0.05
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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