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Evaluation of ECG Transmission and AI Models Using Apple Watch ECGs and Symptoms Data Collected Using a Mayo iPhone App

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Know the risks and potential benefits of clinical studies and talk to your health care provider before participating. Read our disclaimer for details. Identifier: NCT05324566
Recruitment Status : Recruiting
First Posted : April 12, 2022
Last Update Posted : April 12, 2022
Information provided by (Responsible Party):
Paul A. Friedman, Mayo Clinic

Brief Summary:
The purpose of the study is to determine if the Electrocardiograms (ECGs) and symptoms data obtained from an Apple Watch and transmitted to Mayo Clinic are of sufficient quality to guide a person's care.

Condition or disease
Heart Failure Arrhythmias, Cardiac Health Care Utilization

Detailed Description:
  1. Patients who have the Mayo Clinic patient app and iOS 14 or higher who are 18 years of age or older will be invited to enroll.
  2. Patient will undergo email survey to assess ownership of Apple Watch v4 or later, and subsequent willingness to participate in the study. Those who agree will undergo digital consent and enrollment.
  3. A customized Mayo Clinic Study App will be available to download to their iOS device and will be used to test whether it is feasible to access ECGs and symptoms data patients have collected using their personal Apple watch that are saved on the patient's phone. The study app will facilitate transmission of past and future patient-recorded watch ECGs.
  4. The patient ECGs and self-reported symptoms data will be uploaded to the AI Dashboard in the patient's medical record (ECG rhythm classification facilitated by Apple ECG program).
  5. We will perform a retrospective review of electronic medical record data from enrolled subjects to assess the quality of the Apple Watch obtained ECGs, assess the results from the AI-ECG dashboard using obtained watch ECGs, and compare these results to prior or subsequently obtained 12 lead ECGs.
  6. Data analysis will be performed with steps to ensure patient confidentiality. Data will be transmitted using similar protocols as with current app data, and all data will be saved in the secure Mayo Clinic electronic environment (called the UDP).
  7. All patients' watch data will be compared to AI dashboard data. Additionally, clinical data in the EMR (such as blood tests, echocardiograms, and other data recorded for routine medical care) will be used to assess the utility of the watch ECG quality for AI algorithms (such as determining whether a weak heart pump is present, for example).

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Study Type : Observational [Patient Registry]
Estimated Enrollment : 1000000 participants
Observational Model: Cohort
Time Perspective: Prospective
Target Follow-Up Duration: 12 Months
Official Title: EvALuation of ECG Transmission and AI moDels Using Apple Watch ECGs and Symptoms Data Collected usiNg a Mayo iPhone App
Actual Study Start Date : May 5, 2021
Estimated Primary Completion Date : June 29, 2023
Estimated Study Completion Date : June 29, 2023

Patients with ECG-capable Apple Watch
Patients who own an Apple Watch series 4 or later willing to record and upload personal ECGs to our study App

Primary Outcome Measures :
  1. Number of patient-triggered Apple Watch ECGs recorded [ Time Frame: 12 months ]
    Total number of patient-triggered Apple Watch ECGs recorded and uploaded by individual patients over the study period.

  2. Frequency of medical providers accessing Apple Watch data [ Time Frame: 12 months ]
    Number of times a medical provider accesses the Apple Watch data via electronic medical record-linked ECG dashboard.

  3. Number of Apple Watch ECGs of acceptable quality [ Time Frame: 12 months ]
    A sample of Apple Watch ECGs will undergo manual review by ECG technicians and rated using a standard data form for signal quality and diagnostic utility, summarized as the percent of "acceptable" ECGs.

  4. Performance of Artificial Intelligence ECG algorithms for disease prediction with Apple Watch ECGs [ Time Frame: 12 months ]
    Artificial Intelligence ECG algorithms to predict various cardiac pathologies will be applied to Apple Watch ECGs. Accuracy and performance of AI algorithm models will be assessed by comparing AI predicted disease and patient's given medical diagnosis in the electronic medical record.

Information from the National Library of Medicine

Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the contacts provided below. For general information, Learn About Clinical Studies.

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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   Yes
Sampling Method:   Non-Probability Sample
Study Population
Patients in the general public who own ECG-capable Apple Watches

Inclusion Criteria:

- Using the Mayo patient iPhone app. (determined automatically via Mayo software).

Exclusion Criteria:

- Inability to provide informed consent.

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its identifier (NCT number): NCT05324566

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Contact: Jennifer Dugan, BA 507-538-1125

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United States, Minnesota
Mayo Clinic Rochester Recruiting
Rochester, Minnesota, United States, 55905
Contact: Jennifer Dugan, BA    507-538-1125   
Sponsors and Collaborators
Mayo Clinic
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Principal Investigator: Paul Friedman, MD Mayo Clinic
Additional Information:
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Responsible Party: Paul A. Friedman, Principal Investigator, Mayo Clinic Identifier: NCT05324566    
Other Study ID Numbers: 21-001964
First Posted: April 12, 2022    Key Record Dates
Last Update Posted: April 12, 2022
Last Verified: April 2022
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No
Plan Description: Due to patient confidentiality and IRB rules, we will not make individual patient data available

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by Paul A. Friedman, Mayo Clinic:
digital health
artificial intellegence
neural network
wearable device
Additional relevant MeSH terms:
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Arrhythmias, Cardiac
Heart Diseases
Cardiovascular Diseases
Pathologic Processes