Effect of a Home-Based Wearable Continuous ECG Monitoring Patch on Detection of Undiagnosed Atrial Fibrillation: The mSToPS Randomized Clinical Trial | Atrial Fibrillation | JAMA | JAMA Network
[Skip to Navigation]
Access to paid content on this site is currently suspended due to excessive activity being detected from your IP address 35.170.64.36. Please contact the publisher to request reinstatement.

This video summarizes findings from a combined randomized trial and matched cohort study testing the effects of immediate vs delayed use of a self-applied adhesive continuous ECG monitoring patch on new diagnoses of atrial fibrillation in patients at high risk of the dysrhythmia.

1.
Weng  LC, Preis  SR, Hulme  OL,  et al.  Genetic predisposition, clinical risk factor burden, and lifetime risk of atrial fibrillation.  Circulation. 2018;137(10):1027-1038.PubMedGoogle ScholarCrossref
2.
Hannon  N, Sheehan  O, Kelly  L,  et al.  Stroke associated with atrial fibrillation: incidence and early outcomes in the north Dublin population stroke study.  Cerebrovasc Dis. 2010;29(1):43-49.PubMedGoogle ScholarCrossref
3.
Wolf  PA, Abbott  RD, Kannel  WB.  Atrial fibrillation: a major contributor to stroke in the elderly: the Framingham Study.  Arch Intern Med. 1987;147(9):1561-1564.PubMedGoogle ScholarCrossref
4.
Friberg  L, Rosenqvist  M, Lindgren  A, Terént  A, Norrving  B, Asplund  K.  High prevalence of atrial fibrillation among patients with ischemic stroke.  Stroke. 2014;45(9):2599-2605.PubMedGoogle ScholarCrossref
5.
Lin  HJ, Wolf  PA, Benjamin  EJ, Belanger  AJ, D’Agostino  RB.  Newly diagnosed atrial fibrillation and acute stroke: the Framingham Study.  Stroke. 1995;26(9):1527-1530.PubMedGoogle ScholarCrossref
6.
Hart  RG, Pearce  LA, Aguilar  MI.  Meta-analysis: antithrombotic therapy to prevent stroke in patients who have nonvalvular atrial fibrillation.  Ann Intern Med. 2007;146(12):857-867.PubMedGoogle ScholarCrossref
7.
Goldstein  LB, Bushnell  CD, Adams  RJ,  et al; American Heart Association Stroke Council; Council on Cardiovascular Nursing; Council on Epidemiology and Prevention; Council for High Blood Pressure Research; Council on Peripheral Vascular Disease, and Interdisciplinary Council on Quality of Care and Outcomes Research.  Guidelines for the primary prevention of stroke.  Stroke. 2011;42(2):517-584.PubMedGoogle ScholarCrossref
8.
Kirchhof  P, Benussi  S, Kotecha  D,  et al; ESC Scientific Document Group.  2016 ESC Guidelines for the management of atrial fibrillation developed in collaboration with EACTS.  Eur Heart J. 2016;37(38):2893-2962.PubMedGoogle ScholarCrossref
9.
Steinhubl  SR, McGovern  P, Dylan  J, Topol  EJ.  The digitised clinical trial.  Lancet. 2017;390(10108):2135.PubMedGoogle ScholarCrossref
10.
Choudhry  NK.  Randomized, controlled trials in health insurance systems.  N Engl J Med. 2017;377(10):957-964.PubMedGoogle ScholarCrossref
11.
Steinhubl  SR, Mehta  RR, Ebner  GS,  et al.  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.  Am Heart J. 2016;175:77-85.PubMedGoogle ScholarCrossref
12.
Hughes  M, Lip  GY; Guideline Development Group, National Clinical Guideline for Management of Atrial Fibrillation in Primary and Secondary Care, National Institute for Health and Clinical Excellence.  Stroke and thromboembolism in atrial fibrillation.  Thromb Haemost. 2008;99(2):295-304.PubMedGoogle Scholar
13.
Nasir  JM, Pomeroy  W, Marler  A,  et al.  Predicting Determinants of Atrial Fibrillation or Flutter for Therapy Elucidation in Patients at Risk for Thromboembolic Events (PREDATE AF) Study.  Heart Rhythm. 2017;14(7):955-961.PubMedGoogle ScholarCrossref
14.
Healey  JS, Alings  M, Ha  A,  et al; ASSERT-II Investigators.  Subclinical atrial fibrillation in older patients.  Circulation. 2017;136(14):1276-1283.PubMedGoogle ScholarCrossref
15.
Hanchak  NA, Murray  JF, Hirsch  A, McDermott  PD, Schlackman  N.  USQA Health Profile Database as a tool for health plan quality improvement.  Manag Care Q. 1996;4(2):58-69.PubMedGoogle Scholar
16.
Jensen  PN, Johnson  K, Floyd  J, Heckbert  SR, Carnahan  R, Dublin  S.  A systematic review of validated methods for identifying atrial fibrillation using administrative data.  Pharmacoepidemiol Drug Saf. 2012;21(suppl 1):141-147.PubMedGoogle ScholarCrossref
17.
Proietti  M, Mairesse  GH, Goethals  P,  et al; Belgian Heart Rhythm Week Investigators.  A population screening programme for atrial fibrillation.  Europace. 2016;18(12):1779-1786.PubMedGoogle Scholar
18.
Lowres  N, Krass  I, Neubeck  L,  et al.  Atrial fibrillation screening in pharmacies using an iPhone ECG.  Int J Clin Pharm. 2015;37(6):1111-1120.PubMedGoogle ScholarCrossref
19.
Svennberg  E, Engdahl  J, Al-Khalili  F, Friberg  L, Frykman  V, Rosenqvist  M.  Mass screening for untreated atrial fibrillation: the STROKESTOP Study.  Circulation. 2015;131(25):2176-2184.PubMedGoogle ScholarCrossref
20.
Halcox  JPJ, Wareham  K, Cardew  A,  et al.  Assessment of remote heart rhythm sampling using the AliveCor heart monitor to screen for atrial fibrillation: the REHEARSE-AF Study.  Circulation. 2017;136(19):1784-1794.PubMedGoogle ScholarCrossref
21.
Reiffel  JA, Verma  A, Kowey  PR,  et al; REVEAL AF Investigators.  Incidence of previously undiagnosed atrial fibrillation using insertable cardiac monitors in a high-risk population: the REVEAL AF Study.  JAMA Cardiol. 2017;2(10):1120-1127.PubMedGoogle ScholarCrossref
22.
Benjamin  EJ, Levy  D, Vaziri  SM, D’Agostino  RB, Belanger  AJ, Wolf  PA.  Independent risk factors for atrial fibrillation in a population-based cohort: the Framingham Heart Study.  JAMA. 1994;271(11):840-844.PubMedGoogle ScholarCrossref
23.
Muse  ED, Wineinger  NE, Spencer  EG,  et al.  Validation of a genetic risk score for atrial fibrillation.  PLoS Med. 2018;15(3):e1002525.PubMedGoogle ScholarCrossref
24.
Mahajan  R, Perera  T, Elliott  AD,  et al.  Subclinical device-detected atrial fibrillation and stroke risk.  Eur Heart J. 2018;39(16):1407-1415.PubMedGoogle ScholarCrossref
25.
Link  MS, Giugliano  RP, Ruff  CT,  et al; ENGAGE AF-TIMI 48 Investigators.  Stroke and mortality risk in patients with various patterns of atrial fibrillation: results from the ENGAGE AF-TIMI 48 Trial (Effective Anticoagulation With Factor Xa Next Generation in Atrial Fibrillation-Thrombolysis in Myocardial Infarction 48).  Circ Arrhythm Electrophysiol. 2017;10(1):e004267.PubMedGoogle ScholarCrossref
26.
Vanassche  T, Lauw  MN, Eikelboom  JW,  et al.  Risk of ischaemic stroke according to pattern of atrial fibrillation: analysis of 6563 aspirin-treated patients in ACTIVE-A and AVERROES.  Eur Heart J. 2015;36(5):281-287a.PubMedGoogle ScholarCrossref
27.
Van Gelder  IC, Healey  JS, Crijns  HJGM,  et al.  Duration of device-detected subclinical atrial fibrillation and occurrence of stroke in ASSERT.  Eur Heart J. 2017;38(17):1339-1344.PubMedGoogle ScholarCrossref
28.
Rahimi  K.  Subclinical atrial fibrillation in need of more assertive evidence.  Eur Heart J. 2017;38(17):1345-1347.PubMedGoogle ScholarCrossref
29.
Wolf  PA, Abbott  RD, Kannel  WB.  Atrial fibrillation as an independent risk factor for stroke: the Framingham Study.  Stroke. 1991;22(8):983-988.PubMedGoogle ScholarCrossref
30.
Chen  LY, Chung  MK, Allen  LA,  et al; American Heart Association Council on Clinical Cardiology; Council on Cardiovascular and Stroke Nursing; Council on Quality of Care and Outcomes Research; and Stroke Council.  Atrial fibrillation burden: moving beyond atrial fibrillation as a binary entity.  Circulation. 2018;137(20):e623-e644.PubMedGoogle ScholarCrossref
31.
Redman  K, Thorne  S, Lauck  SB, Taverner  T.  ‘What else can I do?’ insights from atrial fibrillation patient communication online.  Eur J Cardiovasc Nurs. 2017;16(3):194-200.PubMedGoogle ScholarCrossref
32.
Dorian  P, Jung  W, Newman  D,  et al.  The impairment of health-related quality of life in patients with intermittent atrial fibrillation.  J Am Coll Cardiol. 2000;36(4):1303-1309.PubMedGoogle ScholarCrossref
Original Investigation
July 10, 2018

Effect of a Home-Based Wearable Continuous ECG Monitoring Patch on Detection of Undiagnosed Atrial Fibrillation: The mSToPS Randomized Clinical Trial

Author Affiliations
  • 1Scripps Translational Science Institute, La Jolla, California
  • 2Wave Research Center, La Jolla, California
  • 3Healthagen Outcomes, Chicago, Illinois
  • 4Janssen Scientific Affairs, Titusville, New Jersey
JAMA. 2018;320(2):146-155. doi:10.1001/jama.2018.8102
Key Points

Question  Can a home-based self-applied wearable electrocardiogram (ECG) patch improve the diagnosis of atrial fibrillation (AF) relative to routine care?

Findings  In this randomized clinical trial of 2659 individuals at increased risk for AF, immediate monitoring using a self-applied ECG patch, compared with delaying ECG monitoring for 4 months, led to a significantly higher rate of AF diagnosis at 4 months (3.9% vs 0.9%).

Meaning  Among individuals at increased risk for AF, use of a home-based self-applied ECG patch facilitated AF diagnosis; further research is needed regarding clinical implications.

Abstract

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

×