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.|
|ClinicalTrials.gov Identifier: NCT05324566|
Recruitment Status : Recruiting
First Posted : April 12, 2022
Last Update Posted : April 12, 2022
|Condition or disease|
|Heart Failure Arrhythmias, Cardiac Health Care Utilization|
- 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.
- 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.
- 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.
- 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).
- 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.
- 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).
- 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).
|Study Type :||Observational [Patient Registry]|
|Estimated Enrollment :||1000000 participants|
|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
- 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.
- 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.
- 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.
- 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.
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 ClinicalTrials.gov identifier (NCT number): NCT05324566
|Contact: Jennifer Dugan, BAemail@example.com|
|United States, Minnesota|
|Mayo Clinic Rochester||Recruiting|
|Rochester, Minnesota, United States, 55905|
|Contact: Jennifer Dugan, BA 507-538-1125 firstname.lastname@example.org|
|Principal Investigator:||Paul Friedman, MD||Mayo Clinic|