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Trial registered on ANZCTR
Registration number
ACTRN12617001374358
Ethics application status
Approved
Date submitted
31/08/2017
Date registered
27/09/2017
Date last updated
29/10/2018
Date data sharing statement initially provided
29/10/2018
Type of registration
Prospectively registered
Titles & IDs
Public title
Continuous monitoring of heart rhythm with a wearable device for detection of atrial fibrillation.
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Scientific title
Development and validation of a novel, wearable continuous ECG monitor for automated detection of atrial fibrillation in patients attending a hypertension outpatient clinic.
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Secondary ID [1]
291987
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DP03246
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Universal Trial Number (UTN)
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Trial acronym
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Linked study record
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Health condition
Health condition(s) or problem(s) studied:
Atrial fibrillation
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Cardiac arrhythmia
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Hypertension
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Stroke
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Condition category
Condition code
Cardiovascular
302779
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0
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Hypertension
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Stroke
302780
302780
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0
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Ischaemic
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Cardiovascular
302781
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0
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Other cardiovascular diseases
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Intervention/exposure
Study type
Observational
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Patient registry
False
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Target follow-up duration
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Target follow-up type
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Description of intervention(s) / exposure
Participants will be exposed to 24 hours of monitoring with a wearable ECG device.
The Alerte Digital Health ECG device is a small wrist watched sized device with two electrodes attached to their body. The device comprises of circuitry allowing live streaming to a smartphone via Bluetooth, and a rechargeable battery with approximate life of 24 hours. It has been developed to provide automated continuous, real time ECG interpretation with artificial intelligence and it has been configured for this study to focus on automated detection of atrial fibrillation.
The device has previously been validated for safety and accuracy in a laboratory environment, and subsequently in a clinical environment compared against a standard ward based hospital monitoring system.
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Intervention code [1]
298117
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Early Detection / Screening
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Comparator / control treatment
No control group
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Control group
Uncontrolled
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Outcomes
Primary outcome [1]
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Our goal is to produce automated continuous, real time ECG interpretation with artificial intelligence (AI), for detection of atrial fibrillation, utilising our wristwatch-sized ECG machine.
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Assessment method [1]
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Timepoint [1]
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Patients will be observed with 24 hours of continuous monitoring.
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Secondary outcome [1]
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To document the frequency and duration of atrial fibrillation, identified by the artificial intelligence, by applying the artificial intelligence to the ECG data acquired by the wristwatch sized ECG acquisition device. The ECG strips showing both sinus rhythm and atrial fibrillation will be independently adjudicated by a cardiologist blinded to the diagnosis made by the artificial intelligence. Accuracy of the AI system will be determined by comparing the AF and sinus rhythm diagnosis from the AI system against the cardiologist gold standard.
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Assessment method [1]
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Timepoint [1]
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Following 24 hours of monitoring.
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Secondary outcome [2]
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To document the frequency and duration of other arrhythmias, specifically supraventricular arrhythmias but not atrial fibrillation (including atrial flutter), ventricular arrhythmias (including ventricular ectopics), and artifact identified by the artificial intelligence. This will be measured by applying the artificial intelligence to the ECG data acquired by the wristwatch sized ECG acquisition device. The ECG strips showing supraventricular arrhythmias, ventricular arrhythmias and artifact will be independently adjudicated by a cardiologist blinded to the diagnosis made by the artificial intelligence. Accuracy of the AI system will be determined by comparing the atrial and ventricular arrhythmias and artifact diagnosis from the AI system against the cardiologist gold standard.
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Assessment method [2]
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Timepoint [2]
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Following 24 hours of monitoring.
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Secondary outcome [3]
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To document any discrepancy between the cardiologist scored ECG and the AI analysis. This data will be used to improve the training of the AI system.
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Assessment method [3]
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Timepoint [3]
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Following 24 hours of monitoring.
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Secondary outcome [4]
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The exact AF burden (paroxysmal and persistent) in patients wearing the device, helping identify those in need of further investigation and/or anticoagulant therapy
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Assessment method [4]
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Timepoint [4]
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After 24 hours of monitoring
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Secondary outcome [5]
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The heart rate in those with known persistent AF, to examine methods of using AI to devise a better surveillance strategy to detect (or prevent) early heart failure
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Assessment method [5]
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Timepoint [5]
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After 24 hours of monitoring
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Secondary outcome [6]
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Levels of anxiety / stress reported by patients through a questionnaire that will be used to determine the heart rate variability in response to stress.
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Assessment method [6]
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Timepoint [6]
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Before the 24 hours of monitoring, participants will be asked to complete a standardised medical questionnaire (DASS-21) to determine levels of stress or anxiety in their life. They will also be asked to complete a diary to record sleep quality and activities whilst wearing the device.
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Eligibility
Key inclusion criteria
Age over 18 and less than 80 years.
Ability to give informed consent in English without the need for a translator.
Attendance at the Royal Perth Hospital hypertension clinic.
Presence of sinus rhythm or atrial fibrillation.
Willingness to return devices to Royal Perth Hospital hypertension clinic.
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Minimum age
18
Years
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Maximum age
79
Years
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Sex
Both males and females
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Can healthy volunteers participate?
No
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Key exclusion criteria
Permanent pacemaker or defibrillator.
Presence of arrhythmias other than atrial fibrillation on baseline ECG. (Presence of ventricular ectopy is not an exclusion criteria).
Dementia or severe physical dependence.
Inability to attend on two consecutive days to allow for return of the monitoring system, or other social circumstances in which an ECG system and smart phone may not be practical.
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Study design
Purpose
Screening
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Duration
Cross-sectional
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Selection
Convenience sample
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Timing
Prospective
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Statistical methods / analysis
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Recruitment
Recruitment status
Recruiting
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Date of first participant enrolment
Anticipated
1/10/2017
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Actual
10/04/2018
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Date of last participant enrolment
Anticipated
1/12/2018
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Actual
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Date of last data collection
Anticipated
14/12/2018
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Actual
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Sample size
Target
50
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Accrual to date
40
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Final
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Recruitment in Australia
Recruitment state(s)
WA
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Recruitment hospital [1]
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Royal Perth Hospital - Perth
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Recruitment postcode(s) [1]
16085
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6000 - Perth
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Funding & Sponsors
Funding source category [1]
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Commercial sector/Industry
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Name [1]
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Alerte Digital Health
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Address [1]
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174 Reynolds Road
Mt Pleasant, Western Australia 6153
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Country [1]
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Australia
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Funding source category [2]
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Charities/Societies/Foundations
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Name [2]
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Royal Perth Hospital Medical Research Foundation
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Address [2]
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PO Box 2323
East Perth WA 6892
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Country [2]
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Australia
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Primary sponsor type
Commercial sector/Industry
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Name
Alerte Digital Health
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Address
174 Reynolds Road
Mt Pleasant, Western Australia 6153
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Country
Australia
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Secondary sponsor category [1]
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None
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Name [1]
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Address [1]
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Country [1]
295458
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Ethics approval
Ethics application status
Approved
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Ethics committee name [1]
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Royal Perth Hospital Human Research Ethics Committee
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Ethics committee address [1]
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Ethics committee country [1]
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Australia
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Date submitted for ethics approval [1]
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Approval date [1]
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26/05/2017
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Ethics approval number [1]
297724
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Summary
Brief summary
Our goal is to produce automated continuous, real time ECG interpretation with artificial intelligence (AI), utilising our wristwatch-sized ECG machine. Our initial AI system will be focused on automated detection of atrial fibrillation. We have already developed a prototype ECG detection device and trained our initial AI system, which has undergone validation testing in a clinical environment. This study is intended to further develop our ECG system to be suitable for more widespread use.
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Trial website
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Trial related presentations / publications
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Public notes
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Contacts
Principal investigator
Name
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Prof David Playford
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Address
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University of Notre Dame, Fremantle
Professor of Cardiology, Mount Hospital
Suite 41
Mount Medical Centre
146 Mounts Bay Road
PERTH WA 6000
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Country
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Australia
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Phone
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+61 8 9485 0945
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Fax
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Email
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[email protected]
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Contact person for public queries
Name
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David Playford
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Address
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University of Notre Dame, Fremantle
Professor of Cardiology, Mount Hospital
Suite 41
Mount Medical Centre
146 Mounts Bay Road
PERTH WA 6000
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Country
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Australia
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Phone
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+61 8 9485 0945
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Fax
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Email
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[email protected]
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Contact person for scientific queries
Name
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David Playford
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Address
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University of Notre Dame, Fremantle
Professor of Cardiology, Mount Hospital
Suite 41
Mount Medical Centre
146 Mounts Bay Road
PERTH WA 6000
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Country
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Australia
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Phone
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+61 8 9485 0945
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Fax
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Email
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[email protected]
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Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
Yes
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What data in particular will be shared?
The deidentified ECG data from each patient will be available on request.
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When will data be available (start and end dates)?
January 2019
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Available to whom?
Researchers requesting source data used to train the Alerte artificial intelligence system
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Available for what types of analyses?
Verification of type and nature of arrhythmia present on ECG traces
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How or where can data be obtained?
De-identified patient ECG file (single file, most likely in .edf format).
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What supporting documents are/will be available?
No Supporting Document Provided
Results publications and other study-related documents
Documents added manually
No documents have been uploaded by study researchers.
Documents added automatically
No additional documents have been identified.
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