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

N/ACompletedNCT04208971

Mayo Clinic1,225 enrolled

Overview

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.

Study Type

OBSERVATIONAL

Enrollment

1,225

Conditions

Atrial Fibrillation

Interventions

AI-enabled ECG-based Screening Tool for AFOTHER

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

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

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.

Locations (1)

Mayo Clinic

Rochester, Minnesota, United States

Outcomes

Primary Outcomes

Diagnosis of Atrial Fibrillation as Detected by Patch Application

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 \[AUC\]).

Time frame: Three Months

Data from ClinicalTrials.gov

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