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

Heart Failure Clinical Trial

Official title:

EvALuation of ECG Transmission and AI moDels Using Apple Watch ECGs and Symptoms Data Collected usiNg a Mayo iPhone App

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05324566
• Other study ID #: 21-001964
• Status: Recruiting
• Start date: May 5, 2021
• Est. completion date: June 2024

Study information

• Verified date: August 2023
• Source: Mayo Clinic
• Contact: Jennifer Dugan, BA
• Phone: 507-538-1125
• Email: dugan.jennifer[@]mayo.edu
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial 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.

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).

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 1000000
• Est. completion date: June 2024
• Est. primary completion date: June 2024
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

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

Exclusion Criteria:

• Inability to provide informed consent.

Related Conditions & MeSH terms

• Arrhythmias, Cardiac
• Health Care Utilization
• Heart Failure

Locations

Country	Name	City	State
United States	Mayo Clinic Rochester	Rochester	Minnesota

Sponsors (1)

Lead Sponsor	Collaborator
Mayo Clinic

Country where clinical trial is conducted

United States, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Number of patient-triggered Apple Watch ECGs recorded	Total number of patient-triggered Apple Watch ECGs recorded and uploaded by individual patients over the study period.	12 months
Primary	Frequency of medical providers accessing Apple Watch data	Number of times a medical provider accesses the Apple Watch data via electronic medical record-linked ECG dashboard.	12 months
Primary	Number of Apple Watch ECGs of acceptable quality	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.	12 months
Primary	Performance of Artificial Intelligence ECG algorithms for disease prediction with Apple Watch ECGs	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.	12 months

External Links

•   Mayo Clinic Clinical Trials