Withings Device for Atrial Fibrillation Detection

(WIBOFA Trial)

Overseen By Aline Criton

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Withings

Disqualifiers: Pacemaker, Parkinson's, Recent MI, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

371 Participants Needed

Trial Summary

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. ^{1 2 3 4 5}

Is 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. ^{1 5 6 7 8}

How 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. ^{1 9 10 11 12}

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

Eligibility 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.

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

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

Treatment Details

Interventions

• Withings SCT02

Trial Overview 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.

Participant Groups

Group I: Normal Sinus Rhythm Experimental Treatment 2 Interventions

Simultaneous ECG recording of patient with Normal Sinus Rhythm with investigational and reference devices

Group II: Atrial Fibrillation Experimental Treatment 2 Interventions

Simultaneous ECG recording of patient with Atrial Fibrillation with investigational and reference devices

Group III: Arrhythmia other than Atrial Fibrillation Experimental Treatment 2 Interventions

Simultaneous ECG recording of patient with Arrhythmia other than Atrial Fibrillation with investigational and reference devices

Who Is Running the Clinical Trial?

Withings

Lead Sponsor

Trials

23

Recruited

6,100+

Findings from Research

Wearable technology, particularly smartwatches using photoplethysmography (PPG), shows promise in effectively screening for asymptomatic atrial fibrillation (AF), which is crucial since AF can lead to strokes in individuals who may not even know they have it.

While smartwatches can increase the detection of AF cases compared to traditional methods, they should be viewed as a preliminary screening tool rather than a definitive diagnostic method, necessitating follow-up with healthcare professionals for confirmation and treatment.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Apple Watch, Wearables, and Heart Rhythm: where do we stand? Raja, JM., Elsakr, C., Roman, S., et al.[2020]

The developed smartwatch algorithm for detecting Atrial Fibrillation (AF) demonstrated high sensitivity (87.8%) and specificity (97.4%) in a real-world population, indicating its effectiveness for continuous monitoring of this cardiac condition.

The algorithm not only functions well during daily activities but also accurately estimates AF burden, achieving a 98% correlation with ground truth measurements, which highlights its potential for practical use in managing AF.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Atrial Fibrillation Detection and Atrial Fibrillation Burden Estimation via Wearables. Zhu, L., Nathan, V., Kuang, J., et al.[2022]

The Verily Study Watch, a wrist-worn device using continuous ECG and photoplethysmography, demonstrated high sensitivity (96.1%) and specificity (98.1%) for detecting atrial fibrillation (AF) in a study of 117 patients, making it a promising tool for continuous AF monitoring.

The device's estimation of AF burden closely matched that of a standard 14-day ECG monitor, indicating its potential for accurate clinical management of AF, which is a significant advancement over existing consumer devices that only perform periodic checks.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Validation of a Deep Learning Algorithm for Continuous, Real-Time Detection of Atrial Fibrillation Using a Wrist-Worn Device in an Ambulatory Environment. Poh, MZ., Battisti, AJ., Cheng, LF., et al.[2023]

The WATCH AF trial demonstrated that a smartwatch-based algorithm for detecting atrial fibrillation (AF) achieved a high sensitivity of 93.7% and specificity of 98.2%, indicating it is a highly accurate tool for AF detection in hospitalized patients.

Despite the promising accuracy, the study faced challenges with signal quality, leading to a significant dropout rate, suggesting that improvements in real-time signal quality checks are necessary for better applicability in long-term AF screening.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The WATCH AF Trial: SmartWATCHes for Detection of Atrial Fibrillation. Dörr, M., Nohturfft, V., Brasier, N., et al.[2020]

The AliveCor™ heart monitor, a smartphone-integrated ECG device, can accurately detect paroxysmal atrial fibrillation in stroke patients, potentially improving diagnosis compared to traditional methods like 12-lead ECG and Holter monitoring.

In a study involving 296 patients, the use of the AliveCor™ monitor by nursing staff could enhance the detection of atrial fibrillation, offering a cost-effective and non-invasive approach to improve stroke prevention strategies.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Smartphone electrographic monitoring for atrial fibrillation in acute ischemic stroke and transient ischemic attack. Tu, HT., Chen, Z., Swift, C., et al.[2018]

This trial aims to determine if using wearable sensors for targeted screening can more effectively diagnose asymptomatic atrial fibrillation (AF) compared to routine care, involving 2,100 participants randomized to immediate or delayed monitoring.

The study will also explore two different rhythm-monitoring strategies and assess long-term clinical outcomes, potentially improving screening methods for undiagnosed AF in the general population.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

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. Steinhubl, SR., Mehta, RR., Ebner, GS., et al.[2022]

In the eBRAVE-AF trial involving 5,551 participants, digital screening using a smartphone app significantly increased the detection rate of treatment-relevant atrial fibrillation (AF) compared to usual care, with odds ratios of 2.12 and 2.75 in the first and second phases, respectively.

This study suggests that digital screening for AF is not only effective but also has the potential for widespread use due to its accessibility on smartphones, although further research is needed to determine if it improves treatment outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Smartphone-based screening for atrial fibrillation: a pragmatic randomized clinical trial. Rizas, KD., Freyer, L., Sappler, N., et al.[2023]

The AliveCor Kardia ECG monitor (ACK) demonstrated a 100% sensitivity and 94% specificity for detecting atrial fibrillation when interpreted by electrophysiologists using lead I recordings, indicating it is highly effective for this purpose.

However, the ACK's built-in diagnostic algorithm showed lower sensitivity (55-70%) and specificity (60-69%), particularly struggling with cases of atrial flutter and patients with ventricular pacemakers, suggesting that while the device is useful for initial screening, further review by specialists is often necessary.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Prospective blinded Evaluation of the smartphone-based AliveCor Kardia ECG monitor for Atrial Fibrillation detection: The PEAK-AF study. Wegner, FK., Kochhäuser, S., Ellermann, C., et al.[2021]

Mobile health devices that detect atrial fibrillation are becoming widely used and can identify more cases than traditional care, but there is ongoing debate about the appropriateness of screening, especially in younger populations.

Physicians need to be aware of the capabilities and limitations of these devices, as increased detection may lead to more referrals for genetic evaluation in younger patients with early-onset atrial fibrillation.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Role of digital health in detection and management of atrial fibrillation. Tooley, JE., Perez, MV.[2022]

In a study involving 79 cardiac surgery patients, 34.2% developed atrial fibrillation (AF), and the Apple Watch's pulse rate measurements showed a strong correlation with AF events, indicating its potential for real-time monitoring.

The machine learning algorithm developed for diagnosing AF from pulse data achieved a high diagnostic accuracy of 94.16%, suggesting that wearable devices like the Apple Watch could be effective tools for early AF detection in clinical settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Diagnosis of Atrial Fibrillation Using Machine Learning With Wearable Devices After Cardiac Surgery: Algorithm Development Study. Hiraoka, D., Inui, T., Kawakami, E., et al.[2022]

The ECG WATCH is an innovative, portable device designed to monitor heart health by recording single-lead ECGs in just 10 seconds, making it user-friendly and accessible without medical expertise.

In tests with 30 participants, the ECG WATCH demonstrated high-quality recordings comparable to certified electrocardiographs and includes an app with an algorithm for automatically detecting atrial fibrillation, indicating its potential for effective long-term cardiac monitoring.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Anytime ECG Monitoring through the Use of a Low-Cost, User-Friendly, Wearable Device. Randazzo, V., Ferretti, J., Pasero, E.[2021]

A 58-year-old patient with atrial fibrillation (AF) experienced recurrent episodes after multiple treatments, highlighting the challenges in detecting AF in real-world settings.

The use of a novel FDA-approved wireless ECG monitoring device allowed for timely detection of recurrent AF, demonstrating the potential of mobile health technology to improve patient care and monitoring.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Detection of Recurrent Atrial Fibrillation Utilizing Novel Technology. Hickey, KT., Dizon, J., Frulla, A.[2022]

References

1. China pubmed.ncbi.nlm.nih.gov

Apple Watch, Wearables, and Heart Rhythm: where do we stand? [2020]

2. United States pubmed.ncbi.nlm.nih.gov

Atrial Fibrillation Detection and Atrial Fibrillation Burden Estimation via Wearables. [2022]

3. England pubmed.ncbi.nlm.nih.gov

Validation of a Deep Learning Algorithm for Continuous, Real-Time Detection of Atrial Fibrillation Using a Wrist-Worn Device in an Ambulatory Environment. [2023]

4. United States pubmed.ncbi.nlm.nih.gov

The WATCH AF Trial: SmartWATCHes for Detection of Atrial Fibrillation. [2020]

5. United States pubmed.ncbi.nlm.nih.gov

Smartphone electrographic monitoring for atrial fibrillation in acute ischemic stroke and transient ischemic attack. [2018]

6. United States pubmed.ncbi.nlm.nih.gov

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]

7. United States pubmed.ncbi.nlm.nih.gov

Smartphone-based screening for atrial fibrillation: a pragmatic randomized clinical trial. [2023]

8. Netherlands pubmed.ncbi.nlm.nih.gov

Prospective blinded Evaluation of the smartphone-based AliveCor Kardia ECG monitor for Atrial Fibrillation detection: The PEAK-AF study. [2021]

9. England pubmed.ncbi.nlm.nih.gov

Role of digital health in detection and management of atrial fibrillation. [2022]

10. Canada pubmed.ncbi.nlm.nih.gov

Diagnosis of Atrial Fibrillation Using Machine Learning With Wearable Devices After Cardiac Surgery: Algorithm Development Study. [2022]

11. Switzerland pubmed.ncbi.nlm.nih.gov

Anytime ECG Monitoring through the Use of a Low-Cost, User-Friendly, Wearable Device. [2021]

12. United States pubmed.ncbi.nlm.nih.gov

Detection of Recurrent Atrial Fibrillation Utilizing Novel Technology. [2022]