Withings Device for Atrial Fibrillation Detection
(WIBOFA Trial)
Recruiting in Palo Alto (17 mi)
Age: 18+
Sex: Any
Travel: May Be Covered
Time Reimbursement: Varies
Trial Phase: Academic
Recruiting
Sponsor: Withings
Disqualifiers: Pacemaker, Parkinson's, Recent MI, others
No Placebo Group
Trial Summary
What is the purpose of this trial?The aim of the study is to evaluate the performance of Withings SCT02 with embedded Withings ECG-app in the automatic detection of atrial fibrillation
Will I have to stop taking my current medications?
The trial information does not specify whether you need to stop taking your current medications. It is best to discuss this with the study staff for guidance.
What data supports the effectiveness of the Withings SCT02 treatment for atrial fibrillation detection?
Research shows that wearable devices using photoplethysmography (PPG) technology, similar to the Withings SCT02, are effective in detecting atrial fibrillation (AF) with high sensitivity and specificity. These devices can continuously monitor heart rhythms and have been shown to accurately identify AF, which can help in preventing strokes.
12345Is the Withings Device for Atrial Fibrillation Detection safe for humans?
The research articles reviewed focus on the effectiveness of wearable devices for detecting atrial fibrillation, but they do not provide specific safety data for the Withings Device or similar devices. Generally, wearable devices for heart monitoring are considered non-invasive and safe for human use.
15678How does the Withings SCT02 treatment for atrial fibrillation differ from other treatments?
The Withings SCT02 treatment is unique because it uses wearable technology to detect atrial fibrillation through non-invasive heart rate monitoring, which can be done anytime and anywhere. This approach allows for continuous monitoring and early detection of irregular heart rhythms, unlike traditional methods that require hospital visits and may miss sporadic episodes.
19101112Eligibility Criteria
This trial is for individuals who have or are suspected to have atrial fibrillation, a heart condition causing irregular heartbeat. Participants must be eligible based on specific criteria set by the researchers but these details were not provided.Inclusion Criteria
Subject able to read, understand, and provide written informed consent
Subject able to communicate effectively with and willing to follow instructions from the study staff
I am 22 years old or older.
+1 more
Exclusion Criteria
I have not had a heart attack in the last 90 days.
I have not had a lung clot or tissue death in the last 3 months.
Subject with an implanted electrical device (i.e. pacemaker, ICD …), whether active or inactive
+6 more
Trial Timeline
Screening
Participants are screened for eligibility to participate in the trial
2-4 weeks
ECG Recording
Simultaneous ECG recording of patients with investigational and reference devices
10 months
Follow-up
Participants are monitored for safety and effectiveness after ECG recordings
4 weeks
Participant Groups
The study is testing the accuracy of a new device called Withings SCT02 with an ECG-app in detecting atrial fibrillation against a standard reference device (Schiller Cardiovit FT-1) through 30-second heart rhythm recordings.
3Treatment groups
Experimental Treatment
Group I: Normal Sinus RhythmExperimental Treatment2 Interventions
Simultaneous ECG recording of patient with Normal Sinus Rhythm with investigational and reference devices
Group II: Atrial FibrillationExperimental Treatment2 Interventions
Simultaneous ECG recording of patient with Atrial Fibrillation with investigational and reference devices
Group III: Arrhythmia other than Atrial FibrillationExperimental Treatment2 Interventions
Simultaneous ECG recording of patient with Arrhythmia other than Atrial Fibrillation with investigational and reference devices
Find a Clinic Near You
Research Locations NearbySelect from list below to view details:
Diverse Clinical ResearchMiami, FL
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Who Is Running the Clinical Trial?
WithingsLead Sponsor
References
Apple Watch, Wearables, and Heart Rhythm: where do we stand? [2020]Atrial fibrillation (AF) poses a major health concern in the United States by affecting over 5 million people accounting for at least 15% to 25% of strokes. It can be asymptomatic or subclinical with its first presentation being stroke in 18%, and AF being only detected at the time of stroke. With evidence of subclinical AF associated with increased risk of ischemic stroke, recent developments indeed point towards wearables, especially smart watches, being quite effective and representing a novel method for screening for silent AF in the general population, and thereby reducing mortality and morbidity associated with it. This manuscript aims to review whether the photoplethysmography (PPG) technology, employed in the wearables to monitor heart rate, is accurate enough to aid in the diagnosis of AF that may remain asymptomatic or paroxysmal. It also explores the option of actually employing this method in the general population, the feasibility of this mode of diagnosis, sensitivity and specificity of this method compared to the conventional electrocardiogram (EKG), and the actual follow up with a practitioner and subsequent treatment of AF, if diagnosed. We conducted a Medline search using various combinations of "smart watch" "atrial fibrillation" "wearables", and "Kardia" to identify pivotal randomized trials published before June 1, 2019, for inclusion in this review. Concurrently, major practice guidelines, trial bibliographies, and pertinent reviews were examined to ensure inclusion of relevant trials. A consensus among the authors was used to choose items for narrative inclusion. The following section reviews data from pivotal trials to determine the effectiveness of smart watch technology in detecting AF in the general population. Trials reviewed evaluated apple watch, Kardia, Samsung wearables in diagnosis of AF. The fact that there is an increase in consumer use of wearables, smart devices, which can serve as health monitoring devices that can be used as a non-invasive, ambulatory assessment of heart rate and rhythm, is definitely novel. Intermittent short EKG recordings repeated over a longer-term period produced significantly better sensitivity for AF detection, with 4 times as many cases diagnosed compared with a single time-point measurement. Since there are limitations and further research into this new field is required, the wearable technology may not serve as the ultimate tool for diagnosis of AF, rather a nidus for the general population to seek medical advice for confirmation on being notified of having an irregular rhythm leading to prevention of morbidity and mortality associated with it.
Atrial Fibrillation Detection and Atrial Fibrillation Burden Estimation via Wearables. [2022]Atrial Fibrillation (AF) is an important cardiac rhythm disorder, which if left untreated can lead to serious complications such as a stroke. AF can remain asymptomatic, and it can progressively worsen over time; it is thus a disorder that would benefit from detection and continuous monitoring with a wearable sensor. We develop an AF detection algorithm, deploy it on a smartwatch, and prospectively and comprehensively validate its performance on a real-world population that included patients diagnosed with AF. The algorithm showed a sensitivity of 87.8% and a specificity of 97.4% over every 5-minute segment of PPG evaluated. Furthermore, we introduce novel algorithm blocks and system designs to increase the time of coverage and monitor for AF even during periods of motion noise and other artifacts that would be encountered in daily-living scenarios. An average of 67.8% of the entire duration the patients wore the smartwatch produced a valid decision. Finally, we present the ability of our algorithm to function throughout the day and estimate the AF burden, a first-of-this-kind measure using a wearable sensor, showing 98% correlation with the ground truth and an average error of 6.2%.
Validation of a Deep Learning Algorithm for Continuous, Real-Time Detection of Atrial Fibrillation Using a Wrist-Worn Device in an Ambulatory Environment. [2023]Background Wearable devices may be useful for identification, quantification and characterization, and management of atrial fibrillation (AF). To date, consumer wrist-worn devices for AF detection using photoplethysmography-based algorithms perform only periodic checks when the user is stationary and are US Food and Drug Administration cleared for prediagnostic uses without intended use for clinical decision-making. There is an unmet need for medical-grade diagnostic wrist-worn devices that provide long-term, continuous AF monitoring. Methods and Results We evaluated the performance of a wrist-worn device with lead-I ECG and continuous photoplethysmography (Verily Study Watch) and photoplethysmography-based convolutional neural network for AF detection and burden estimation in a prospective multicenter study that enrolled 117 patients with paroxysmal AF. A 14-day continuous ECG monitor (Zio XT) served as the reference device to evaluate algorithm sensitivity and specificity for detection of AF in 15-minute intervals. A total of 91 857 intervals were contributed by 111 subjects with evaluable reference and test data (18.3 h/d median watch wear time). The watch was 96.1% sensitive (95% CI, 92.7%-98.0%) and 98.1% specific (95% CI, 97.2%-99.1%) for interval-level AF detection. Photoplethysmography-derived AF burden estimation was highly correlated with the reference device burden (R2=0.986) with a mean difference of 0.8% (95% limits of agreement, -6.6% to 8.2%). Conclusions Continuous monitoring using a photoplethysmography-based convolutional neural network incorporated in a wrist-worn device has clinical-grade performance for AF detection and burden estimation. These findings suggest that monitoring can be performed with wrist-worn wearables for diagnosis and clinical management of AF. Registration Information URL: https://www.clinicaltrials.gov; Unique identifier: NCT04546763.
The WATCH AF Trial: SmartWATCHes for Detection of Atrial Fibrillation. [2020]The WATCH AF (SmartWATCHes for Detection of Atrial Fibrillation) trial compared the diagnostic accuracy to detect atrial fibrillation (AF) by a smartwatch-based algorithm using photoplethysmographic (PPG) signals with cardiologists' diagnosis by electrocardiography (ECG).
Smartphone electrographic monitoring for atrial fibrillation in acute ischemic stroke and transient ischemic attack. [2018]Rationale Paroxysmal atrial fibrillation is a common and preventable cause of devastating strokes. However, currently available monitoring methods, including Holter monitoring, cardiac telemetry and event loop recorders, have drawbacks that restrict their application in the general stroke population. AliveCor™ heart monitor, a novel device that embeds miniaturized electrocardiography (ECG) in a smartphone case coupled with an application to record and diagnose the ECG, has recently been shown to provide an accurate and sensitive single lead ECG diagnosis of atrial fibrillation. This device could be used by nurses to record a 30-s ECG instead of manual pulse taking and automatically provide a diagnosis of atrial fibrillation. Aims To compare the proportion of patients with paroxysmal atrial fibrillation detected by AliveCor™ ECG monitoring with current standard practice. Sample size 296 Patients. Design Consecutive ischemic stroke and transient ischemic attack patients presenting to participating stroke units without known atrial fibrillation will undergo intermittent AliveCor™ ECG monitoring administered by nursing staff at the same frequency as the vital observations of pulse and blood pressure until discharge, in addition to the standard testing paradigm of each participating stroke unit to detect paroxysmal atrial fibrillation. Study outcome Proportion of patients with paroxysmal atrial fibrillation detected by AliveCor™ ECG monitoring compared to 12-lead ECG, 24-h Holter monitoring and cardiac telemetry. Discussion Use of AliveCor™ heart monitor as part of routine stroke unit nursing observation has the potential to be an inexpensive non-invasive method to increase paroxysmal atrial fibrillation detection, leading to improvement in stroke secondary prevention.
Rationale and design of a home-based trial using wearable sensors to detect asymptomatic atrial fibrillation in a targeted population: The mHealth Screening To Prevent Strokes (mSToPS) trial. [2022]Efficient methods for screening populations for undiagnosed atrial fibrillation (AF) are needed to reduce its associated mortality, morbidity, and costs. The use of digital technologies, including wearable sensors and large health record data sets allowing for targeted outreach toward individuals at increased risk for AF, might allow for unprecedented opportunities for effective, economical screening. The trial's primary objective is to determine, in a real-world setting, whether using wearable sensors in a risk-targeted screening population can diagnose asymptomatic AF more effectively than routine care. Additional key objectives include (1) exploring 2 rhythm-monitoring strategies-electrocardiogram-based and exploratory pulse wave-based-for detection of new AF, and (2) comparing long-term clinical and resource outcomes among groups. In all, 2,100 Aetna members will be randomized 1:1 to either immediate or delayed monitoring, in which a wearable patch will capture a single-lead electrocardiogram during the first and last 2 weeks of a 4-month period beginning immediately or 4 months after enrollment, respectively. An observational, risk factor-matched control group (n = 4,000) will be developed from members who did not receive an invitation to participate. The primary end point is the incidence of new AF in the immediate- vs delayed-monitoring arms at the end of the 4-month monitoring period. Additional efficacy and safety end points will be captured at 1 and 3 years. The results of this digital medicine trial might benefit a substantial proportion of the population by helping identify and refine screening methods for undiagnosed AF.
Smartphone-based screening for atrial fibrillation: a pragmatic randomized clinical trial. [2023]Digital smart devices have the capability of detecting atrial fibrillation (AF), but the efficacy of this type of digital screening has not been directly compared to usual care for detection of treatment-relevant AF. In the eBRAVE-AF trial ( NCT04250220 ), we randomly assigned 5,551 policyholders of a German health insurance company who were free of AF at baseline (age 65 years (median; interquartile range (11) years, 31% females)) to digital screening (n = 2,860) or usual care (n = 2,691). In this siteless trial, for digital screening, participants used a certified app on their own smartphones to screen for irregularities in their pulse waves. Abnormal findings were evaluated by 14-day external electrocardiogram (ECG) loop recorders. The primary endpoint was newly diagnosed AF within 6 months treated with oral anti-coagulation by an independent physician not involved in the study. After 6 months, participants were invited to cross-over for a second study phase with reverse assignment for secondary analyses. The primary endpoint of the trial was met, as digital screening more than doubled the detection rate of treatment-relevant AF in both phases of the trial, with odds ratios of 2.12 (95% confidence interval (CI), 1.19-3.76; P = 0.010) and 2.75 (95% CI, 1.42-5.34; P = 0.003) in the first and second phases, respectively. This digital screening technology provides substantial benefits in detecting AF compared to usual care and has the potential for broad applicability due to its wide availability on ordinary smartphones. Future studies are needed to test whether digital screening for AF leads to better treatment outcomes.
Prospective blinded Evaluation of the smartphone-based AliveCor Kardia ECG monitor for Atrial Fibrillation detection: The PEAK-AF study. [2021]The AliveCor Kardia ECG monitor (ACK) offers a smartphone-based one-lead ECG recording for the detection of atrial fibrillation. We compared ACK lead I recordings with the 12-lead ECG and introduce a novel parasternal lead (NPL).
Role of digital health in detection and management of atrial fibrillation. [2022]Atrial fibrillation is a common arrhythmia associated with significant morbidity, mortality and decreased quality of life. Mobile health devices marketed directly to consumers capable of detecting atrial fibrillation through methods including photoplethysmography, single-lead ECG as well as contactless methods are becoming ubiquitous. Large-scale screening for atrial fibrillation is feasible and has been shown to detect more cases than usual care-however, controversy still exists surrounding screening even in older higher risk populations. Given widespread use of mobile health devices, consumer-driven screening is happening on a large scale in both low-risk and high-risk populations. Given that young people make up a large portion of early adopters of mobile health devices, there is the potential that many more patients with early onset atrial fibrillation will come to clinical attention requiring possible referral to genetic arrythmia clinic. Physicians need to be familiar with these technologies, and understand their risks, and limitations. In the current review, we discuss current mobile health devices used to detect atrial fibrillation, recent and upcoming trials using them for diagnosis of atrial fibrillation, practical recommendations for patients with atrial fibrillation diagnosed by a mobile health device and special consideration in young patients.
Diagnosis of Atrial Fibrillation Using Machine Learning With Wearable Devices After Cardiac Surgery: Algorithm Development Study. [2022]Some attempts have been made to detect atrial fibrillation (AF) with a wearable device equipped with photoelectric volumetric pulse wave technology, and it is expected to be applied under real clinical conditions.
Anytime ECG Monitoring through the Use of a Low-Cost, User-Friendly, Wearable Device. [2021]Every year cardiovascular diseases kill the highest number of people worldwide. Among these, pathologies characterized by sporadic symptoms, such as atrial fibrillation, are difficult to be detected as state-of-the-art solutions, e.g., 12-leads electrocardiogram (ECG) or Holter devices, often fail to tackle these kinds of pathologies. Many portable devices have already been proposed, both in literature and in the market. Unfortunately, they all miss relevant features: they are either not wearable or wireless and their usage over a long-term period is often unsuitable. In addition, the quality of recordings is another key factor to perform reliable diagnosis. The ECG WATCH is a device designed for targeting all these issues. It is inexpensive, wearable (size of a watch), and can be used without the need for any medical expertise about positioning or usage. It is non-invasive, it records single-lead ECG in just 10 s, anytime, anywhere, without the need to physically travel to hospitals or cardiologists. It can acquire any of the three peripheral leads; results can be shared with physicians by simply tapping a smartphone app. The ECG WATCH quality has been tested on 30 people and has successfully compared with an electrocardiograph and an ECG simulator, both certified. The app embeds an algorithm for automatically detecting atrial fibrillation, which has been successfully tested with an official ECG simulator on different severity of atrial fibrillation. In this sense, the ECG WATCH is a promising device for anytime cardiac health monitoring.
Detection of Recurrent Atrial Fibrillation Utilizing Novel Technology. [2022]The true prevalence of AF is likely underestimated because episodes are often sporadic and challenging to detect in a "real world" setting. This case report will describe a 58-year-old atrial fibrillation patient with multiple cardiac risk factors. After two ablations and one cardioversion, the patient failed to remain in normal sinus rhythm. Shortly after AF returned, the decision was made to perform a second cardioversion. Post-procedure, the patient was given a novel FDA-approved, wireless ECG monitoring device compatible with the iPhone®. This device has the capability of recording and transmitting a single-channel ECG. Within days, the patient began feeling symptomatic again and used his device to transmit an ECG to his healthcare provider. Recurrent AF was detected and the patient was directed to seek further evaluation. The success of this novel device to detect recurrent AF highlights the "real world" applicability of using mHealth technology more readily in patient care.