The DOI matches its Crossref record; 49 of the 51 references it cites were found in a registry or an index.
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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“The mSToPS trial (table 1and figure 1C) exemplifies such screening strategy.(26) Alternatively, intermittent”
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“The question remains, how much effort should be expended to identify AFib and what is the risk of initiating lifelong anticoagulation in patients who may not truly require it? Atrial fibrillation is often asymptomatic and paroxysmal, and studies of episodic versus continuous monitoring have demonstrated that the more…”
BackgroundThe single-lead 14-day ECG patch EZYPRO®: a new kid in the block
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“[14,19] They can monitor patients’ heart rate [20,21] and oxygen saturation, [22] and they can be used to manage medications.”
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What’s the best way to leverage 31 million days of ECG data?
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“When applying continuous ECG monitoring to unselected patientpopulations,thedetectionrateforAFover7-daysofmonitoringis9-10%inbothsexes,andlessthanhalfoftheparoxysmalAFcasesthatoccur inclinicalpopulationshavebeendetectedafter24 – 48 hofmonitoring 10,11 .”
Thompson, A., Fleischmann, K. E., Smilowitz, N. R., Fuentes, L. D. L., Mukherjee, D., Aggarwal, N. R., Ahmad, F. S., Allen, R. B., Altin, S. E., Auerbach, A., et al. (2026) · Circulation · doi:10.1161/cir.0000000000001472 · Cited by 2
Electrocardiographic Risk Factors for a Common Cardiac Condition
Littmann, L. (2022) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2022.3304 · Cited by 2
Improving participant representation in the era of digital clinical studies
Ramos, E., Baca-Motes, K., Pandit, J. A., & Ajayi, T. A. (2022) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2022.07.004 · Cited by 2
Self-citationTan, C., MINEYAMA, K., & Shiotani, H. (2024) · Industrial Health · doi:10.2486/indhealth.2023-0157 · Cited by 2
“This device is capable of continuous monitoring for as long as two weeks and is currently used for the diagnosis of transient atrial fibrillation 25–27 ) .”
BackgroundScreening for atrial fibrillation: the role of CHA2DS2-VASc and atrial fibrillation burden
Xing, L. Y., Vad, O. B., Engler, D., Svendsen, J. H., & Diederichsen, S. Z. (2024) · European Heart Journal Supplements · doi:10.1093/eurheartjsupp/suae078 · Cited by 2
“…continuous AF screening with an ECG patch for four weeks and then an observational study to compare the screened participants with a matched cohort 30 —also demonstrated a lower risk of stroke in the screening group relative to the matched controls at 3-year follow-up [1.7%/year vs. 2.2%/year; HR…”
ResultInfluentialDigital health for cardiovascular disease and diabetes
Shan, R., Kim, C. H., Spaulding, E. M., Marvel, F. A., & Martin, S. S. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-15728-8.00004-5 · Cited by 2
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Russell, M., Cain, E., Bazzano, L., Anda‐Duran, I. D., Woo, J. G., & Urbina, E. M. (2025) · JMIR Human Factors · doi:10.2196/71103 · Cited by 2
“Similar to our study, one group found that more than one-third of participants did not wear the device during the study period [23].”
Wijesurendra, R. S., Pessoa-Amorim, G., Buck, G. A. N., Harper, C., Bulbulia, R. A., Jones, N. R., A’Court, C., Kurien, R., Taylor, K., Casadei, B., et al. (2025) · American Heart Journal · doi:10.1016/j.ahj.2025.07.004 · Cited by 2
2025 Thai guideline for the diagnosis and management of atrial fibrillation
Ngarmukos, T., Methavigul, K., Rungpradubvong, V., Apiyasawat, S., Wongcharoen, W., Pumprueg, S., Boonyapisit, W., Suwanagool, A., Chantrarat, T., Makarawate, P., et al. (2025) · Asian Biomedicine · doi:10.2478/abm-2025-0028 · Cited by 2
12-Lead ECG Reconstruction via Koopman Operators
Golany, T., Radinsky, K., Freedman, D. Z., & Minha, S. (2021) · International Conference on Machine Learning · Cited by 2
Monitoring for atrial fibrillation after stroke
Wasserlauf, J., & Volgman, A. S. (2021) · The Lancet Neurology · doi:10.1016/s1474-4422(21)00106-x · Cited by 2
Recurrence of atrial fibrillation postablation: which is the most effective approach for detection?
Casella, M., Compagnucci, P., Conti, M. A., Falanga, U., Volpato, G., Fogante, M., Cipolletta, L., Misiani, A., Molini, S., Giovagnoni, A., et al. (2022) · Minerva Cardiology and Angiology · doi:10.23736/s2724-5683.22.05859-8 · Cited by 2
Demonstration of flexible encapsulation in assembly industry
Liu, C., Chen, M., Pi, T.-C., Kao, J.-C., & Yeh, Y.-I. (2022) · IEEE Electronic Components and Technology Conference (ECTC) · doi:10.1109/ectc51906.2022.00161 · Cited by 2
Machine learning for ranking f-wave extraction methods in single-lead ECGs
Ben-Moshe, N., Biton, S. B., Tsutsui, K., Suleiman, M. A., Sörnmo, L., & Behar, J. A. (2024) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.106817 · Cited by 2
“However, singlelead ECGs are becoming increasingly more common thanks to the development of patches and smartwatches for remote health monitoring and screening [15], [16].”
BackgroundHayama, E., Yamashita, T., Otsuka, T., Yagi, N., Arita, T., Yajima, J., & Suzuki, S. S. (2020) · Japanese Journal of Electrocardiology · doi:10.5105/jse.40.207 · Cited by 2
Poposka, L., Vavlukis, M., Pejkov, H., & Gušev, M. (2021) · Open Access Macedonian Journal of Medical Sciences · doi:10.3889/oamjms.2021.4960 · Cited by 2
Tan, C., Zhang, L., Wu, H., & Qian, T. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1906.07361 · Cited by 2
“Wearable Holters and mobile devices that are commonly used for an early diagnosis of arrhythmia usually come with a single-lead ECG [3].”
BackgroundA Survey of Challenges and Opportunities in Sensing and Analytics for Cardiovascular DisordersPreprint
Hurley, N. C., Spatz, E. S., Krumholz, H. M., Jafari, R., & Mortazavi, B. J. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1908.06170 · Cited by 2
“Chief risk factors that predispose patients to AFib are age, other heart disease, diabetes, and chronic lung disease.”
BackgroundInfluentialTraining neural networks with synthetic electrocardiogramsPreprint
Kaisti, M., Laitala, J., & Airola, A. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2111.06175 · Cited by 2
Oesterle, A., & Upadhyay, G. A. (2019) · The American Journal of Medicine · doi:10.1016/j.amjmed.2018.11.032 · Cited by 2
Robust In-Vehicle Heartbeat Detection Using Multimodal Signal FusionPreprint
Warnecke, J. M., Lasenby, J., & Deserno, T. M. (2023) · Research Square · doi:10.21203/rs.3.rs-2828298/v1 · Cited by 2
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Sigfstead, S., Newman, D., Nault, I., Gladstone, D. J., TANG, A. S. L., Macle, L., Healey, J. S., Andrade, J. G., Kaba, R. A., & Cheung, C. C. (2024) · Canadian Journal of Cardiology · doi:10.1016/j.cjca.2024.08.122 · Cited by 1
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Brik, T., Niekel, M. S., Bak, M., Himmelreich, J. C. L., Harskamp, R. E., & van Charante, E. P. M. (2025) · BMJ Open · doi:10.1136/bmjopen-2025-102160 · Cited by 1
Almur, O., Emran, B., Milhem, F. S., Ayaseh, Q. Z., Dahmas, A. M., Abukhalil, M. M., Saife, S., Bdair, M., Younas, A., Neiroukh, H., et al. (2025) · Clinical Medicine Insights Cardiology · doi:10.1177/11795468251361209 · Cited by 1
“75 In parallel, shared decision-making—incorporating patient preferences, lifestyle considerations, and treatment bur-dens—remains a cornerstone for optimizing therapy adherence and overall outcomes.”
Saito, T., Nishiyama, Y., Otsuka, T., Sakamoto, Y., Okubo, S., Iguchi, Y., Yamaguchi, K., Okada, Y., Hamaguchi, H., Yonehara, T., et al. (2025) · Frontiers in Neurology · doi:10.3389/fneur.2025.1560495 · Cited by 2
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Atrial Fibrillation Screening: Burden or Benefit for Patients and the Healthcare System
Senoo, K. (2025) · Journal of Cardiovascular Electrophysiology · doi:10.1111/jce.70153 · Cited by 1
Segar, M. W., Keshvani, N., Jaeger, B. C., Rosenblatt, A., Razavi, M., Saeed, M., Rodríguez, C. J., Khan, S. S., Kao, D. P., & Pandey, A. (2025) · Heart Rhythm · doi:10.1016/j.hrthm.2025.12.008 · Cited by 1
Screen-printing of eco-friendly PEDOT: PSS/graphene composite ink for flexible electronics
Chen, Y., Wang, T., Wu, Y., Bai, W., & Dong, J. (2025) · Flexible and Printed Electronics · doi:10.1088/2058-8585/ae292c · Cited by 1
“…of a wide range of critical applications, such as electronic skin for epidermal sensing [1–3], flexible solar cells for energy harvesting [4–6], neural probes for multi-modal sensing [7–9], electrocardiogram patches for heart monitoring [10–12], and biosensors for chemical detection [13–15].”
Understanding Artificial Intelligence (AI) for the Electrophysiologist
Ramanathan, C., & Trayanova, N. A. (2026) · Indian Pacing and Electrophysiology Journal · doi:10.1016/j.ipej.2026.01.010 · Cited by 1
Emerging trends and underexplored frontiers in stroke nursing care: A bibliometric review
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“High-risk ambulatory screening studies (mSToPS) show that patch-first or patch-plus-intermittent strategies increase AF diagnoses and anticoagulation starts, though they may also raise resource utilization, which is relevant when designing pragmatic postsurgery pathways [15].”
Association of a High Cardiovascular Disease Risk OSA Phenotype With Incident Atrial Fibrillation
Xu, J., Kwon, Y., Esmaeili, N., Sands, S. A., Hajipour, M., Vena, D., Heckbert, S. R., Soliman, E. Z., Wellman, A., Michos, E. D., et al. (2026) · CHEST Journal · doi:10.1016/j.chest.2026.01.027 · Cited by 1
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Overdiagnosis in atrial fibrillation screening with wearables
Haase, C. B., Jensen, A. E., Modin, F. A., Siersma, V., & Brodersen, J. (2026) · Scandinavian Journal of Primary Health Care · doi:10.1080/02813432.2026.2656694 · Cited by 1
“Only three studies included follow-up periods beyond the screening phase, with durations of 2 · 5 years [31], 3 years [32], and 7 years [33]. additionally, four of the six studies lacked participant blinding [3,31,34,35]. the included studies primarily focused on older populations with an elevated…”
Rashid, A. B., Aslam, E., Ashraf, I., Mubeen, T., Mubeen, A., Zakriya, H., & Amjad, M. (2026) · Future Cardiology · doi:10.1080/14796678.2026.2689050 · Cited by 1
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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