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

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.

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Key information

Conditions

Heart Failure Arrhythmias, Cardiac Behavior Cardiovascular Diseases Health Behavior Health Care Utilization Heart Diseases Pathologic Processes Pathological Conditions, Signs and Symptoms Patient Acceptance of Health Care Treatment Adherence and Compliance

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Mayo Clinic Rochester

Rochester, Minnesota, 55905, United States

About this study

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).

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

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

Exclusion criteria

Inability to provide informed consent.

Treatment and study plan

Primary outcomes

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.

Sponsors and collaborators

Lead sponsor

Mayo Clinic

Other

Registry information

Important dates

Study start: 2021
Primary completion: 2024
Study completion: 2024
First posted: Apr 12, 2022
Registry last updated: Sep 19, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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