Batch Enrollment for AI-Guided Intervention to Lower Neurologic Events in Unrecognized AF

Conditions

Atrial Fibrillation

Brief summary

This is a prospective study to test a novel artificial intelligence (AI)-enabled electrocardiogram (ECG)-based screening tool for improving the diagnosis of unrecognized atrial fibrillation (AF) and stroke prevention.

Peter A. Noseworthy, Zachi I. Attia, Emma Behnken, Rachel Giblon, Katherine A. Bews et al. (16 authors)

Circulation2022-11-08

10.1161/circ.146.suppl_1.10856

Artificial intelligence-guided screening for atrial fibrillation using electrocardiogram during sinus rhythm: a prospective non-randomised interventional trial.

Noseworthy PA, Attia ZI, Behnken EM, Giblon RE, Bews KA, Liu S, Gosse TA, Linn ZD, Deng Y, Yin J, Gersh BJ, Graff-Radford J, Rabinstein AA, Siontis KC, Friedman PA, Yao X.

2022-09-27145 citations

10.1016/s0140-6736(22)01637-3

Batch enrollment for an artificial intelligence-guided intervention to lower neurologic events in patients with undiagnosed atrial fibrillation: rationale and design of a digital clinical trial.

Yao X, Attia ZI, Behnken EM, Walvatne K, Giblon RE, Liu S, Siontis KC, Gersh BJ, Graff-Radford J, Rabinstein AA, Friedman PA, Noseworthy PA.

2021-05-2424 citations

10.1016/j.ahj.2021.05.006

Interventions

OTHERAI-enabled ECG-based Screening Tool for AF

A novel artificial intelligence (AI)-enabled electrocardiogram (ECG)-based screening tool to improve atrial fibrillation diagnosis and stroke prevention.

Study design

Observational model

COHORT

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

18 Years to No maximum

Healthy volunteers

No

Inclusion criteria

* Age ≥18 years * Had a 10-second 12-lead ECG done at Mayo Clinic * Men with CHA2DS2-VASc ≥2 or women with CHA2DS2-VASc ≥3

Exclusion criteria

* Diagnosed atrial fibrillation or atrial flutter * Missing date of birth or sex in the electronic health record (EHR) * A history of intracranial bleeding * A history of end-stage kidney disease * Have an implantable cardiac monitoring device, including a pacemaker, a defibrillator, or implanted loop recorder * Deemed by research personnel to have limitations that would prevent them from being able to provide informed consent, use the patch, or complete interviews will not be included.

Design outcomes

Primary

Measure	Time frame	Description
Diagnosis of Atrial Fibrillation as Detected by Patch Application	Three Months	The data will be used to examine the performance of the algorithm in detecting unrecognized atrial fibrillation (e.g. positive predictive value, negative predictive value, sensitivity, specificity, and area under the curve \[AUC\]).

Countries

United States

Outcome results

None listed