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Effect of a Home-Based Wearable Continuous ECG Monitoring Patch on Detection of Undiagnosed Atrial Fibrillation: The mSToPS Randomized Clinical Trial
Open accessAbstract
Importance: Opportunistic screening for atrial fibrillation (AF) is recommended, and improved methods of early identification could allow for the initiation of appropriate therapies to prevent the adverse health outcomes associated with AF. Objective: To determine the effect of a self-applied wearable electrocardiogram (ECG) patch in detecting AF and the clinical consequences associated with such a detection strategy. Design, Setting, and Participants: A direct-to-participant randomized clinical trial and prospective matched observational cohort study were conducted among members of a large national health plan. Recruitment began November 17, 2015, and was completed on October 4, 2016, and 1-year claims-based follow-up concluded in January 2018. For the clinical trial, 2659 individuals were randomized to active home-based monitoring to start immediately or delayed by 4 months. For the observational study, 2 deidentified age-, sex- and CHA2DS2-VASc-matched controls were selected for each actively monitored individual. Interventions: The actively monitored cohort wore a self-applied continuous ECG monitoring patch at home during routine activities for up to 4 weeks, initiated either immediately after enrolling (n = 1364) or delayed for 4 months after enrollment (n = 1291). Main Outcomes and Measures: The primary end point was the incidence of a new diagnosis of AF at 4 months among those randomized to immediate monitoring vs delayed monitoring. A secondary end point was new AF diagnosis at 1 year in the combined actively monitored groups vs matched observational controls. Other outcomes included new prescriptions for anticoagulants and health care utilization (outpatient cardiology visits, primary care visits, or AF-related emergency department visits and hospitalizations) at 1 year. Results: The randomized groups included 2659 participants (mean [SD] age, 72.4 [7.3] years; 38.6% women), of whom 1738 (65.4%) completed active monitoring. The observational study comprised 5214 (mean [SD] age, 73.7 [7.0] years; 40.5% women; median CHA2DS2-VASc score, 3.0), including 1738 actively monitored individuals from the randomized trial and 3476 matched controls. In the randomized study, new AF was identified by 4 months in 3.9% (53/1366) of the immediate group vs 0.9% (12/1293) in the delayed group (absolute difference, 3.0% [95% CI, 1.8%-4.1%]). At 1 year, AF was newly diagnosed in 109 monitored (6.7 per 100 person-years) and 81 unmonitored (2.6 per 100 person-years; difference, 4.1 [95% CI, 3.9-4.2]) individuals. Active monitoring was associated with increased initiation of anticoagulants (5.7 vs 3.7 per 100 person-years; difference, 2.0 [95% CI, 1.9-2.2]), outpatient cardiology visits (33.5 vs 26.0 per 100 person-years; difference, 7.5 [95% CI, 7.2-7.9), and primary care visits (83.5 vs 82.6 per 100 person-years; difference, 0.9 [95% CI, 0.4-1.5]). There was no difference in AF-related emergency department visits and hospitalizations (1.3 vs 1.4 per 100 person-years; difference, 0.1 [95% CI, -0.1 to 0]). Conclusions and Relevance: Among individuals at high risk for AF, immediate monitoring with a home-based wearable ECG sensor patch, compared with delayed monitoring, resulted in a higher rate of AF diagnosis after 4 months. Monitored individuals, compared with nonmonitored controls, had higher rates of AF diagnosis, greater initiation of anticoagulants, but also increased health care resource utilization at 1 year. Trial Registration: ClinicalTrials.gov Identifier: NCT02506244.
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In the citing paper
“One pioneering trial used a 'band-aid' patch sensor for detecting atrial fibrillation; the sensor was mailed to participants who were enrolled remotely, without the use of any clinical sites, and set the foundation for digitized clinical trials 37 .”
From Multimodal biomedical AI (2022) · cites this paper as [37]
Experimental — accuracy not yet measuredIn the citing paper
“AF screening via ECG patches in selected high-risk individuals is feasible and clinically valuable50”
From Smart wearable devices in cardiovascular care: Where we are and how to move forward (2021) · cites this paper as [50]
In the citing paper
“The study showed that ECG monitoring led to a higher rate of new AF diagnosis at 4 months and 1 year and was associated with the increased initiation of anticoagulation therapy and outpatient cardiology and primary care visits in patients without previously known AF50.”
From Smart wearable devices in cardiovascular care: Where we are and how to move forward (2021) · cites this paper as [50]
In the citing paper
“For example, iRhythm's single-use Zio patch monitors electrical pulses from the heart for 14 days, and is more effective than intermittent hospital check-ups at detecting abnormal rhythms 4 .”
From Skin sensors are the future of health care (2019) · cites this paper as [4]
In the citing paper
“For example, iRhythm's single-use Zio patch monitors electrical pulses from the heart for 14 days, and is more effective than intermittent hospital check-ups at detecting abnormal rhythms 4 .”
From Skin sensors are the future of health care (2019) · cites this paper as [4]
In the citing paper
“For instance, in the mSTOP trial, the information from the device was communicated to the patient and their primary physician, which led to higher rates of cardiology visits and follow-up investigations.”
From Unlocking Tomorrow’s Health Care: Expanding the Clinical Scope of Wearables by Applying Artificial Intelligence (2024) · cites this paper as [27]
In the citing paper
“This study showed that ECG monitoring analyzed by a deep learning model led to a higher rate of new AF diagnosis than standard methods, and was associated with increased initiation of anticoagulation therapy and cardiology referral.”
From Unlocking Tomorrow’s Health Care: Expanding the Clinical Scope of Wearables by Applying Artificial Intelligence (2024) · cites this paper as [27]
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Waalen, J., Edwards, A. M., Sanyal, A., Zambon, R. A., Ariniello, L. M., Ebner, G. S., Baca-Motes, K., Carter, C., Felicione, E., Sarich, T. C., et al. (2020) · Heart Rhythm O2 · doi:10.1016/j.hroo.2020.09.005 · Cited by 8
“The mHealth Screening to Prevent Strokes (mSToPS) trial was a randomized pragmatic trial (RPT) involving more than 1700 older adults with no known AF and at increased risk for stroke based on age and/or clinical risk factors who underwent continuous 1-lead ECG monitoring with a Zio patch for 2 2-week periods over 4 mo…”
BackgroundMethodInfluentialSelf-citationVodička, S., Susič, A. P., & Zelko, E. (2021) · Micromachines · doi:10.3390/mi12010055 · Cited by 8
“Studies have shown that patients presenting with atypical chest pain are more likely to be suffering from an anxiety disorder, and when the standard 12-lead ECG reading is normal, they do not have a greater risk for cardiovascular incidents [28,29].”
BackgroundWong, K., Nguyen, T. N., & Chow, C. K. (2024) · npj Cardiovascular Health · doi:10.1038/s44325-024-00014-w · Cited by 10
Informatics in Emergency Medicine: A Literature Review
Conforti, R. (2024) · Emergency Care and Medicine · doi:10.3390/ecm2010002 · Cited by 10
Basem, J. I., Mani, R., Sun, S., Gilotra, K., Dianati‐Maleki, N., & Dashti, R. (2025) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2025.1525966 · Cited by 8
Advancements in Sensor Technology for Monitoring and Management of Chronic Coronary Syndrome
Cricco, R., Segreti, A., Ferro, A., Beato, S., Castaldo, G., Ciancio, M., Sacco, F. M., Pennazza, G., Ussia, G. P., & Grigioni, F. (2025) · Sensors · doi:10.3390/s25154585 · Cited by 9
“Importantly, these technologies expand cardiovascular surveillance beyond traditional healthcare settings, making it accessible to broader populations, including individuals in underserved areas or those with limited access to in-person care [27].”
InfluentialWang, J., Li, Y., Shi, S., & Bo, Y. (2025) · BMC Cardiovascular Disorders · doi:10.1186/s12872-025-05284-5 · Cited by 7
Vermunicht, P., Grecu, M., Deharo, J., Buckley, C. M., Palà, E., Mairesse, G. H., Farkowski, M. M., Bergonti, M., Pürerfellner, H., Hanson, C. L., et al. (2023) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2023.1112561 · Cited by 7
Sandberg, E. L., Halvorsen, S., Berge, T., Grimsmo, J., Atar, D., Grenne, B. L., & Jortveit, J. (2024) · European Heart Journal - Digital Health · doi:10.1093/ehjdh/ztae026 · Cited by 7
“15 Initiation of anticoagulation therapy was not reported in the Apple Heart Study, the Fitbit study or in the ReducinG stroke by screening for UndiAgnosed atRial fibrillation in elderly inDividuals (GUARD-AF) study.”
MethodScreening and diagnosis of atrial fibrillation using wearable devices
Park, Y. J., & Bae, M. H. (2024) · The Korean Journal of Internal Medicine · doi:10.3904/kjim.2023.521 · Cited by 9
“The mHealth Screening to Prevent Strokes trial investigated the efficacy of a wearable ECG patch for detecting AF and its associated clinical outcomes [11].”
A Crowdsourced AI Framework for Atrial Fibrillation Detection in Apple Watch and Kardia Mobile ECGs
Rad, A. B., Kirsch, M., Li, Q., Xue, J. Q., Sameni, R., Albert, D., & Clifford, G. D. (2024) · Sensors · doi:10.3390/s24175708 · Cited by 10
Intelligent algorithms powered smart devices for atrial fibrillation discrimination
Xie, L., Wang, L., Mo, D., Zhang, Z., & Liang, M. (2024) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.107480 · Cited by 7
Bufalino, V. J., Bleser, W. K., Singletary, E. A., Granger, B. B., O'Brien, E. C., Elkind, M. S. V., Lopez, M. H., Saunders, R. S., McClellan, M., & Brown, N. (2020) · Circulation Cardiovascular Quality and Outcomes · doi:10.1161/circoutcomes.120.006780 · Cited by 8
Nadarajah, R., Wu, J., Frangi, A. F., Hogg, D., Cowan, C., & Gale, C. P. (2021) · European Heart Journal - Quality of Care and Clinical Outcomes · doi:10.1093/ehjqcco/qcab094 · Cited by 7
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Brik, T., Lucassen, W. A. M., Harskamp, R. E., Karregat, E. P. M., Himmelreich, J. C. L., Busschers, W. B., & van Charante, E. P. M. (2022) · American Heart Journal · doi:10.1016/j.ahj.2022.09.002 · Cited by 7
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Kim, Y., Joo, G., Jeon, B. K., Kim, D., Shin, T. Y., Im, H., & Park, J. (2023) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2023.1168054 · Cited by 7
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“This approach, which employs the strategy of collaborating with health plans to identify eligible members to recruit participants via mail and email, is now well entrenched, as was demonstrated by the mHealth Screening to Prevent Strokes randomized clinical trial.(26,27) Following our outreach and recruitment efforts,…”
BackgroundMethodPatel, U. K., Malik, P., Patel, N., Patel, P., Mehta, N. N., Urhoghide, E., Aedma, S. K., Chakinala, R. C., Shah, S., & Arumaithurai, K. (2021) · Cureus · doi:10.7759/cureus.12437 · Cited by 7
“al, 2018 (USA) [30] 2659 clinical trial and prospective matched observational cohort study.”
BackgroundInfluentialIntroduction of Wearable Device in Cardiovascular Field for Monitoring Arrhythmia
Kim, N. H., & Ko, J. S. (2021) · Chonnam Medical Journal · doi:10.4068/cmj.2021.57.1.1 · Cited by 7
Continuous ECG Monitoring with Low-Power Electronics and Energy Harvesting
Richards, J., Lim, M., Li, G., Araya, E., & Jia, Y. (2020) · IEEE International Midwest Symposium on Circuits and Systems (MWSCAS) · doi:10.1109/mwscas48704.2020.9184610 · Cited by 7
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Tran, H. H.-V., Urgessa, N. A., Geethakumari, P., Kampa, P., Parchuri, R., Bhandari, R., Alnasser, A. R., Akram, A., Kar, S., Osman, F., et al. (2023) · Cureus · doi:10.7759/cureus.50952 · Cited by 6
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“5,7,18,36 However, the diagnostic accuracy of the devices is crucial, and some arrhythmia episodes might be undetected by these systems.”
BackgroundJoint HW/SW Signal Co-Conditioning Strategy for Unobtrusive Single-Arm Cardiac Surveillance
Huang, L., Chen, J., Zhang, X., Li, Z., Xu, L., Millham, R. C., Bian, G., & Wu, W. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3522425 · Cited by 6
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Parizad, R., Hatwal, J., Brar, A. S., Desai, R., Batta, A., & Mohan, B. (2026) · Vascular Health and Risk Management · doi:10.2147/vhrm.s590502 · Cited by 9
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“6,7 However, the limited follow-up period of these studies has not allowed a fuller evaluation of the effectiveness of a 1-year screening intervention for preventing cardiovascular events over the longer term, beyond the screening period.”
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“Many of them assessed accuracy for the detection of cardiac arrhythmias at rest or during low-intensity activities, focusing mainly on atrial fibrillation [18,30,31].”
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Detection of Previously Unrecognized (Subclinical) Atrial Fibrillation
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“High-level hospitals could adopt new atrial fibrillation screening and monitoring techniques (eg, portable ECG monitoring patches and smartwatches with ECG monitoring functions) to improve the detection rate of atrial fibrillation.(17) These measures will significantly benefit our ability to prevent and manage atrial…”
BackgroundMass Screening for Atrial Fibrillation: The Hype, The Methods, and The Application
Reiffel, J. A. (2019) · The American Journal of Medicine · doi:10.1016/j.amjmed.2018.12.027 · Cited by 6
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Metadata
- Authors
- Steinhubl, S. R., Waalen, J., Edwards, A. M., Ariniello, L. M., Mehta, R. R., Ebner, G. S., Carter, C., Baca-Motes, K., Felicione, E., Sarich, T., & Topol, E. J.
- Affiliations
- Scripps Translational Science Institute, La Jolla, California
- Healthagen Outcomes, Chicago, Illinois
- Janssen Scientific Affairs (United States) (US)
- Corresponding author
- Steinhubl, Steven R.
- ORCID
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2018-07-10
- Volume
- 320
- Issue
- 2
- Pages
- 146
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- PMC
- PMC6583518
- OpenAlex
- W2869528658
- Cited by
- 539
- References
- 51
- Citations by year
- 2026: 65 · 2025: 70 · 2024: 58 · 2023: 56 · 2022: 72 · 2021: 79 · 2020: 68 · 2019: 58 · 2018: 13
- FWCI
- 41.17
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- JAMA (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (UL1TR001114)
- National Center for Advancing Translational Sciences
- Janssen Pharmaceuticals
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Atrial Fibrillation Management and Outcomes
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Keywords
- atrial fibrillation, opportunistic screening, undiagnosed atrial fibrillation, anticoagulant prescription, health care utilization, CHA2DS2-VASc score, stroke prevention, older adults, health insurance beneficiaries, emergency department visits, hospitalization, primary care visits, cost-effectiveness
- MeSH terms
- Wearable Electronic Devices, Aged, Anticoagulants, Atrial Fibrillation, Female, Health Resources, Humans, Male, Mass Screening, Middle Aged, Risk Factors, Cohort Studies, Electrocardiography, Ambulatory, Comorbidity, Incidence, Intention to Treat Analysis
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