Validation of Software for Assessment of Atrial Fibrillation From Data Acquired by a Wearable Smartwatch

Completed

• Conditions: Atrial Fibrillation
• Interventions: Diagnostic Test: Electrocardiogram

• Registration Number: NCT04176926
• Lead Sponsor: Fitbit LLC

Brief Summary

The goal of this study is to validate the Fitbit ECG software algorithm's ability to detect atrial fibrillation using data derived from a Fitbit wrist-worn consumer device that features a single lead ECG. The performance of the software application will be measured against centralized Core Lab physician-adjudicated 12-lead ECG tracings from FDA cleared ECG monitors as reference standards. The Fitbit software is intended as a pre-screening technology. It should identify candidates who may benefit from further evaluation. The software is not intended to be a diagnostic system.

Detailed Description

Not available

Study Timeline

• Study Start: 2019-10-29
• Study First Submitted: 2019-11-21
• Study First Submitted QC: 2019-11-22
• Study First Posted: 2019-11-25
• Primary Completion: 2019-12-20
• Study Completion: 2020-03-02
• Status Verified: 2020-04
• Last Update Submitted: 2020-04-07
• Last Update Posted: 2020-04-09

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 472

Inclusion Criteria

• Women and men 22 years of age or older
• Capable of giving informed consent
• Sufficient manual dexterity to capture an ECG from the Fitbit wrist-worn device.
• Subjects in the atrial fibrillation (AF) cohort must have a known history of AF and must be in -AF at the time of enrollment based on the screening ECG

Exclusion Criteria

• Anti-arrhythmic (rhythm control) medication use (such as amiodarone or flecainide)
• Cardiac pacemaker or implantable cardioverter-defibrillator
• History of a life-threatening rhythm such as ventricular tachycardia or ventricular fibrillation
• Subjects in the sinus rhythm (SR) cohort should not have any history of atrial fibrillation and should not be in atrial fibrillation or other atrial arrhythmia at the time of enrollment based on the screening ECG

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
Group 1: SR	Electrocardiogram	Group 1: Subjects in the sinus rhythm (SR) cohort should not have any history of atrial fibrillation and should not be in atrial fibrillation or other atrial arrhythmia at the time of enrollment based on the screening ECG.
Group 2: AF	Electrocardiogram	Group 2: Subjects in the atrial fibrillation (AF) cohort must have a known history of AF and must be in AF at the time of enrollment based on the screening ECG.

Primary Outcome Measures

Name	Time	Method
Evaluate the software algorithm's ability to classify a heart rhythm as sinus rhythm or atrial fibrillation from a waveform equivalent to a Lead I ECG.	Through study completion, an average of 4 months	Sensitivity and specificity of the software algorithm in classifying sinus rhythm and atrial fibrillation from the equivalent of a Lead I ECG waveform, compared with physician's interpretation of a standard 12-lead ECG. Performance goals are 90% (sensitivity) and 92% (specificity)

Secondary Outcome Measures

Name	Time	Method
Confirm the software's ability to produce a waveform clinically equivalent to a Lead I ECG from a clinical reference device (12-lead ECG).	Through study completion, an average of 4 months	Qualitative assessment of the software produced waveform to reference Lead I from 12-lead ECG. Goal is \>0.80 of strips appear to overlay to the unaided eye.; Comparison of R-wave amplitudes between the Fitbit waveform and the clinical reference. Goal is \>0.80 of R-wave amplitudes to be within 2mm.

Trial Locations

Locations (10)

MedStar Washington Hospital Center; 🇺🇸 Washington, District of Columbia, United States

Bioclinica Research The Villages; 🇺🇸 The Villages, Florida, United States

Bioclinica Research Orlando; 🇺🇸 Orlando, Florida, United States

PMG Research of Dupage; 🇺🇸 Winfield, Illinois, United States

PMG Research of McFarland; 🇺🇸 Ames, Iowa, United States

PMG Research of Rocky Mount; 🇺🇸 Rocky Mount, North Carolina, United States

PMG Research of Piedmont Healthcare; 🇺🇸 Statesville, North Carolina, United States

PMG Research of Wilmington; 🇺🇸 Wilmington, North Carolina, United States

PMG Research of Charleston; 🇺🇸 Mount Pleasant, South Carolina, United States

Onassis Cardiac Surgery Center; 🇬🇷 Kallithea, Greece