Detection and Quantification of Atrial Fibrillation in High-risk Patients Using a Smartwatch Wearable (Apple Watch) (EQUAL)

Amsterdam University Medical Centers (UMC), Location Academic Medical Center (AMC)

Status: Enrolling

Conditions: Atrial Fibrillation; Wearable Electronic Devices

Treatments: Device: Apple Watch

Study type: Interventional

Funder types: Other

Identifiers

NCT05686330

2021_209

Details and patient eligibility

About

This is a Randomized Controlled trial to evaluate if continuous heart rate and -rhythm monitoring with a photoplethysmography (PPG) smartwatch wearable (Apple Watch series 5 or 8) can detect atrial fibrillation at an early stage in cardiac patients with a known high risk of developing AF (ChadsVasc score ≥ 2 men; ≥3 women; age ≥ 65). In this multicenter, single arm, prospective randomized controlled trial the investigators will enroll 306 patients (153 per arm). An absolute in between-group difference of 8.5% in diagnosing patients with new AF in favor of the interventional group during a six month study period is hypothesized.

Full description

This is a multicenter Randomized Controlled trial to evaluate if 6-month heart rate and -rhythm monitoring with a photoplethysmography (PPG) smartwatch wearable (Apple Watch series 5) can detect atrial fibrillation (AF) at an early stage in cardiac patients with a known high risk of developing AF (age ≥ 65), who are also at higher risk of developing stroke if AF would occur (ChadsVasc score ≥ 2 men; ≥3 women). The primary objective of this trial is to investigate whether continuous rhythm monitoring with a smartwatch wearable will result in a higher incidence of AF in patients at high risk for but without previously known AF, compared to standard care alone. The secondary outcomes are time to first AF episode, initiation of therapies for AF, the number of patients with major adverse cardiovascular events, and other cardiac arrhythmias than AF diagnosed by a cardiologist.

Patients will be randomized into either the intervention group (n=153), who will be loaned an Apple watch for use, or the control group (n=153), who will receive their standard care alone. Participants in the intervention group will receive the Apple Watch series 5 or 8 wearable and instructions to download a mobile app for the Apple iPhone. The smartwatch and the app on the smartphone are coupled. During the six-month study period, continuous monitoring for at least 12 hours a day of heart rate and -rhythm will be conducted using PPG. If an irregular heart rhythm is detected, the participant is requested through the smart application to record a single-lead ECG, using the smartwatch. Data obtained from the smartwatch will be transferred to the mobile app and will then be assessed with a proprietary certified AF algorithm. The ECG-data will be automatically uploaded in a secure environment of a data center, where it is accessible for the Telecure team who will analyze and interpret the recordings. As soon as AF is newly diagnosed, the patient and the treating cardiologist will be informed.

An implantable loop recorder (ILR) detects new-onset AF in 20.4% of high-risk patients within 6 months after implantation (12). It was estimated that wearing the AW for 12 hours daily would detect 50% of the cases detected with 24-hour monitoring using an ILR. Therefore, the estimated AF detection rate in the intervention arm in this study is 10.2%. Previous studies investigating AF detection with handheld devices, ILRs or patch monitors resulted in an average of 1.5 to 2.0 % AF detection in a control group within 6 months, resulting in an estimated AF detection rate of 1.7% in the control arm of this study. To achieve a 90% power to detect an absolute in-between group difference of 8.5% in diagnosing new onset AF, with a significance level of 5% in favour of the intervention group, a sample size of 306 patients (153 in each group) was required. During the study it was noticed that standard care rhythm monitoring was often initiated by the cardiologists, leading to a higher rate of AF detection in the control patients than was expected based on previous studies that were performed in primary care patients. Thus, on October 1 2023, the sample size was extended to 436 patients (218 per group) to further investigate the underlying factors influencing AF detection rates and time to diagnosis in this secondary care patient population.

Enrollment: 306 estimated patients

Sex: All

Ages: 65+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Age ≥ 65 years
• Chadsvasc score ≥2 for men and ≥ for women at the time of eligibility screening
• Written informed consent as documented by signature from the participant
• Possession of iPhone (6S or later)

Exclusion criteria

• Diagnosis of atrial fibrillation or atrial flutter
• Currently on anticoagulation therapy
• Cardiac implanted electronic device (pacemaker, ICD)
• Smartwatch cannot be worn due to comprehensible reasons (allergic reactions, wounds, amputations, other)
• Significant mental or cognitive impairment

Trial design

Primary purpose: Diagnostic

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: None (Open label)

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306 participants in 2 patient groups

Interventional group (Apple watch)

Experimental group

Description:

These participants will wear a smartwatch (Apple Watch) for 6 months during 12 hours a day. The smartwatch will alarm the participant if an irregular heart rhythm is detected. When a participant receives an irregular heartbeat notification, they can record an ECG with the smartwatch. The ECG will automatically be sent to the Telecure team for evaluation.

Treatment:

Device: Apple Watch

Control group

No Intervention group

Description:

These participants will be following standard care alone. These participants are instructed to notify the investigators when atrial fibrillation is detected or when they have visited the emergency department during these six months. At the end of the study period the investigator will either call the participant, or their treating physician to check for these outcome measures.