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Figure 1.
STROBE Diagram Showing Flow of the Study and Status at Each Point
STROBE Diagram Showing Flow of the Study and Status at Each Point
Figure 2.
Detection of Atrial Fibrillation (AF)
Detection of Atrial Fibrillation (AF)

A, Time to first episode of AF lasting 6 or more minutes. At 30 days, the incidence rate was 6.2%; at 6 months, 20.4%; at 12 months, 27.1%; at 18 months, 29.3%; at 24 months, 33.6%; and at 30 months, 40.0%. B, Onset of AF burden. At 18 months, the incidence of AF burden was 44.9%, 31.1%, 24.2%, and 12.0% for 6 or more minutes, 30 or more minutes, 1 or more hours, and 6 or more hours of AF in a day, respectively; at 30 months, 53.3%, 40.8%, 35.6%, and 19.1%. C, AF detection by CHADS2 score group. At 18 months, the incidence rate was 31.7%, 32.7% and 24.7% for those with a CHADS2 score of 4 or greater, 3, and 2, respectively. ICM indicates insertable cardiac monitor.

Table 1.  
Devices and Baseline Demographic Characteristics
Devices and Baseline Demographic Characteristics
Table 2.  
Predictive Value of Baseline Characteristics for Atrial Fibrillation Onset
Predictive Value of Baseline Characteristics for Atrial Fibrillation Onset
1.
Chugh  SS, Havmoeller  R, Narayanan  K,  et al.  Worldwide epidemiology of atrial fibrillation: a Global Burden of Disease 2010 Study.  Circulation. 2014;129(8):837-847.PubMedGoogle ScholarCrossref
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Kirchhof  P, Benussi  S, Kotecha  D,  et al.  2016 ESC Guidelines for the management of atrial fibrillation developed in collaboration with EACTS.  Europace. 2016;18(11):1609-1678.PubMedGoogle ScholarCrossref
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January  CT, Wann  LS, Alpert  JS,  et al; ACC/AHA Task Force Members.  2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: executive summary: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines and the Heart Rhythm Society.  Circulation. 2014;130(23):2071-2104.PubMedGoogle ScholarCrossref
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Javaheri  S, Barbe  F, Campos-Rodriguez  F,  et al.  Sleep apnea: types, mechanisms, and clinical cardiovascular consequences.  J Am Coll Cardiol. 2017;69(7):841-858.PubMedGoogle ScholarCrossref
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Barbarossa  A, Guerra  F, Capucci  A.  Silent atrial fibrillation: a critical review.  J Atr Fibrillation. 2014;7(3):1138.PubMedGoogle Scholar
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Kirchhof  P, Breithardt  G, Aliot  E,  et al.  Personalized management of atrial fibrillation: proceedings from the fourth Atrial Fibrillation competence NETwork/European Heart Rhythm Association consensus conference.  Europace. 2013;15(11):1540-1556.PubMedGoogle ScholarCrossref
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Garimella  RS, Chung  EH, Mounsey  JP, Schwartz  JD, Pursell  I, Gehi  AK.  Accuracy of patient perception of their prevailing rhythm: a comparative analysis of monitor data and questionnaire responses in patients with atrial fibrillation.  Heart Rhythm. 2015;12(4):658-665.PubMedGoogle ScholarCrossref
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Belkin  M, Hayes  DL, Upadhyay  GA. Device-detected atrial tachycardia and risk of thromboembolism. https://www.acc.org/latest-in-cardiology/articles/2017/02/03/09/44/device-detected-atrial-tachycardia-and-risk-of-thromboembolism. Accessed March 8, 2017.
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Boriani  G, Glotzer  TV, Santini  M,  et al.  Device-detected atrial fibrillation and risk for stroke: an analysis of >10,000 patients from the SOS AF project (Stroke preventiOn Strategies based on Atrial Fibrillation information from implanted devices).  Eur Heart J. 2014;35(8):508-516.PubMedGoogle ScholarCrossref
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Botto  GL, Padeletti  L, Santini  M,  et al.  Presence and duration of atrial fibrillation detected by continuous monitoring: crucial implications for the risk of thromboembolic events.  J Cardiovasc Electrophysiol. 2009;20(3):241-248.PubMedGoogle ScholarCrossref
12.
Capucci  A, Santini  M, Padeletti  L,  et al; Italian AT500 Registry Investigators.  Monitored atrial fibrillation duration predicts arterial embolic events in patients suffering from bradycardia and atrial fibrillation implanted with antitachycardia pacemakers.  J Am Coll Cardiol. 2005;46(10):1913-1920.PubMedGoogle ScholarCrossref
13.
Glotzer  TV, Daoud  EG, Wyse  DG,  et al.  The relationship between daily atrial tachyarrhythmia burden from implantable device diagnostics and stroke risk: the TRENDS study.  Circ Arrhythm Electrophysiol. 2009;2(5):474-480.PubMedGoogle ScholarCrossref
14.
Glotzer  TV, Hellkamp  AS, Zimmerman  J,  et al; MOST Investigators.  Atrial high rate episodes detected by pacemaker diagnostics predict death and stroke: report of the Atrial Diagnostics Ancillary Study of the MOde Selection Trial (MOST).  Circulation. 2003;107(12):1614-1619.PubMedGoogle ScholarCrossref
15.
Healey  JS, Connolly  SJ, Gold  MR,  et al; ASSERT Investigators.  Subclinical atrial fibrillation and the risk of stroke.  N Engl J Med. 2012;366(2):120-129.PubMedGoogle ScholarCrossref
16.
Shanmugam  N, Boerdlein  A, Proff  J,  et al.  Detection of atrial high-rate events by continuous home monitoring: clinical significance in the heart failure-cardiac resynchronization therapy population.  Europace. 2012;14(2):230-237.PubMedGoogle ScholarCrossref
17.
Orlov  MV, Ghali  JK, Araghi-Niknam  M, Sherfesee  L, Sahr  D, Hettrick  DA; Atrial High Rate Trial Investigators.  Asymptomatic atrial fibrillation in pacemaker recipients: incidence, progression, and determinants based on the atrial high rate trial.  Pacing Clin Electrophysiol. 2007;30(3):404-411.PubMedGoogle ScholarCrossref
18.
Strickberger  SA, Ip  J, Saksena  S, Curry  K, Bahnson  TD, Ziegler  PD.  Relationship between atrial tachyarrhythmias and symptoms.  Heart Rhythm. 2005;2(2):125-131.PubMedGoogle ScholarCrossref
19.
Conti  S, Reiffel  JA, Gersh  BJ,  et al.  Baseline demographics, safety, and patient acceptance of an insertable cardiac monitor for atrial fibrillation screening: the REVEAL AF study.  J Atr Fibrillation. 2017;9(5):9-15.Google Scholar
20.
Reiffel  J, Verma  A, Halperin  JL,  et al.  Rationale and design of REVEAL AF: a prospective study of previously undiagnosed atrial fibrillation as documented by an insertable cardiac monitor in high-risk patients.  Am Heart J. 2014;167(1):22-27.PubMedGoogle ScholarCrossref
21.
Hindricks  G, Pokushalov  E, Urban  L,  et al; XPECT Trial Investigators.  Performance of a new leadless implantable cardiac monitor in detecting and quantifying atrial fibrillation: results of the XPECT trial.  Circ Arrhythm Electrophysiol. 2010;3(2):141-147.PubMedGoogle ScholarCrossref
22.
Reiffel  JA, Verma  A, Kowey  PR,  et al. Do atrial fibrillation detection rates differ based on presenting symptomatology in patients at risk of atrial fibrillation and stroke? results from the REVEAL AF study. Poster presented at: European Society of Cardiology Annual Scientific Sessions; August 26–30, 2017; Barcelona, Spain.
23.
Wachter  R, Gröschel  K, Gelbrich  G,  et al; Find-AF(randomised) Investigators and Coordinators.  Holter-electrocardiogram-monitoring in patients with acute ischaemic stroke (Find-AFRANDOMISED): an open-label randomised controlled trial.  Lancet Neurol. 2017;16(4):282-290.PubMedGoogle ScholarCrossref
24.
Healey  JS, Alings  M, Ha  AC,  et al; ASSERT-2 Investigators.  Subclinical atrial fibrillation in older patients  [published online August 4, 2017].  Circulation.PubMedGoogle Scholar
25.
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
26.
Engdahl  J, Andersson  L, Mirskaya  M, Rosenqvist  M.  Stepwise screening of atrial fibrillation in a 75-year-old population: implications for stroke prevention.  Circulation. 2013;127(8):930-937.PubMedGoogle ScholarCrossref
27.
Lowres  N, Neubeck  L, Redfern  J, Freedman  SB.  Screening to identify unknown atrial fibrillation: a systematic review.  Thromb Haemost. 2013;110(2):213-222.PubMedGoogle ScholarCrossref
28.
Lowres  N, Neubeck  L, Salkeld  G,  et al.  Feasibility and cost-effectiveness of stroke prevention through community screening for atrial fibrillation using iPhone ECG in pharmacies: the SEARCH-AF study.  Thromb Haemost. 2014;111(6):1167-1176.PubMedGoogle ScholarCrossref
29.
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
30.
Turakhia  MP, Ullal  AJ, Hoang  DD,  et al.  Feasibility of extended ambulatory electrocardiogram monitoring to identify silent atrial fibrillation in high-risk patients: the Screening Study for Undiagnosed Atrial Fibrillation (STUDY-AF).  Clin Cardiol. 2015;38(5):285-292.PubMedGoogle ScholarCrossref
31.
Charitos  EI, Ziegler  PD, Stierle  U,  et al.  Atrial fibrillation burden estimates derived from intermittent rhythm monitoring are unreliable estimates of the true atrial fibrillation burden.  Pacing Clin Electrophysiol. 2014;37(9):1210-1218.PubMedGoogle ScholarCrossref
32.
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
33.
Israel  CW, Grönefeld  G, Ehrlich  JR, Li  YG, Hohnloser  SH.  Long-term risk of recurrent atrial fibrillation as documented by an implantable monitoring device: implications for optimal patient care.  J Am Coll Cardiol. 2004;43(1):47-52.PubMedGoogle ScholarCrossref
34.
Reiffel  JA.  If it were only that simple.  Eur Heart J. 2016;37(20):1603-1605.PubMedGoogle ScholarCrossref
35.
Flaker  GC, Belew  K, Beckman  K,  et al; AFFIRM Investigators.  Asymptomatic atrial fibrillation: demographic features and prognostic information from the Atrial Fibrillation Follow-up Investigation of Rhythm Management (AFFIRM) study.  Am Heart J. 2005;149(4):657-663.PubMedGoogle ScholarCrossref
36.
Witt  CT, Kronborg  MB, Nohr  EA, Mortensen  PT, Gerdes  C, Nielsen  JC.  Early detection of atrial high rate episodes predicts atrial fibrillation and thromboembolic events in patients with cardiac resynchronization therapy.  Heart Rhythm. 2015;12(12):2368-2375.PubMedGoogle ScholarCrossref
37.
Sanna  T, Diener  HC, Passman  RS,  et al; CRYSTAL AF Investigators.  Cryptogenic stroke and underlying atrial fibrillation.  N Engl J Med. 2014;370(26):2478-2486.PubMedGoogle ScholarCrossref
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Mazurek  M, Huisman  MV, Lip  GY.  Registries in atrial fibrillation: from trials to real-life clinical practice.  Am J Med. 2017;130(2):135-145.PubMedGoogle ScholarCrossref
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Mittal  S, Rogers  J, Sarkar  S,  et al.  Real-world performance of an enhanced atrial fibrillation detection algorithm in an insertable cardiac monitor.  Heart Rhythm. 2016;13(8):1624-1630.PubMedGoogle ScholarCrossref
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Original Investigation
August 26, 2017

Incidence of Previously Undiagnosed Atrial Fibrillation Using Insertable Cardiac Monitors in a High-Risk PopulationThe REVEAL AF Study

Author Affiliations
  • 1Columbia University College of Physicians and Surgeons, New York, New York
  • 2Southlake Regional Health Centre, Newmarket, Ontario, Canada
  • 3Lankenau Institute for Medical Research, Wynnewood, Pennsylvania
  • 4Mount Sinai Medical Center, New York, New York
  • 5Mayo Clinic College of Medicine, Rochester, Minnesota
  • 6Clinic for Cardiology and Pneumology, University Medicine Göttingen, Göttingen, Germany
  • 7Medtronic, Minneapolis, Minnesota
JAMA Cardiol. Published online August 26, 2017. doi:10.1001/jamacardio.2017.3180
Key Points

Question  Will insertable cardiac monitors identify a high incidence of previously undiagnosed atrial fibrillation (AF) in patients at high risk for AF and stroke?

Findings  In this study of 446 patients, the rate of AF detection was 29.3% and 40.0% at 18 and 30 months, respectively, and often resulted in prescription of oral anticoagulation.

Meaning  The incidence of previously undiagnosed AF identified by insertable cardiac monitors may be substantial in patients at high risk for AF and stroke.

Abstract

Importance  In approximately 20% of atrial fibrillation (AF)–related ischemic strokes, stroke is the first clinical manifestation of AF. Strategies are needed to identify and therapeutically address previously undetected AF.

Objective  To quantify the incidence of AF in patients at high risk for but without previously known AF using an insertable cardiac monitor.

Design, Setting, and Participants  This prospective, single-arm, multicenter study was conducted from November 2012 to January 2017. Visits took place at 57 centers in the United States and Europe. Patients with a CHADS2 score of 3 or greater (or 2 with at least 1 additional risk factor) were enrolled. Approximately 90% had nonspecific symptoms potentially compatible with AF, such as fatigue, dyspnea, and/or palpitations.

Exposures  Patients underwent monitoring with an insertable cardiac monitor for 18 to 30 months.

Main Outcomes and Measures  The primary end point was adjudicated AF lasting 6 or more minutes and was assessed at 18 months. Other analyses included detection rates at points from 30 days to 30 months and among CHADS2 score subgroups. Median time from insertion to detection and the percentage of patients subsequently prescribed oral anticoagulation therapy was also determined.

Results  A total of 446 patients were enrolled; 233 (52.2%) were male, and the mean (SD) age was 71.5 (9.9) years. A total of 385 patients (86.3%) received an insertable cardiac monitor, met the primary analysis cohort definition, and were observed for a mean (SD) period of 22.5 (7.7) months. The detection rate of AF lasting 6 or more minutes at 18 months was 29.3%. Detection rates at 30 days and 6, 12, 24, and 30 months were 6.2%, 20.4%, 27.1%, 33.6%, and 40.0%, respectively. At 18 months, AF incidence was similar among patients with CHADS2 scores of 2 (24.7%; 95% CI, 17.3-31.4), 3 (32.7%; 95% CI, 23.8-40.7), and 4 or greater (31.7%; 95% CI, 22.0-40.3) (P = .23). Median (interquartile) time from device insertion to first AF episode detection was 123 (41-330) days. Of patients meeting the primary end point, 13 (10.2%) had 1 or more episodes lasting 24 hours or longer, and oral anticoagulation therapy was prescribed for 72 patients (56.3%).

Conclusions and Relevance  The incidence of previously undiagnosed AF may be substantial in patients with risk factors for AF and stroke. Atrial fibrillation would have gone undetected in most patients had monitoring been limited to 30 days. Further trials regarding the value of detecting subclinical AF and of prophylactic therapies are warranted.

Trial Registration  clinicaltrials.gov Identifier: NCT01727297

Introduction

Atrial fibrillation (AF) affects millions of people worldwide,1,2 is associated with increased morbidity and mortality, and increases with older age, hypertension, diabetes, heart failure, and more.24 Importantly, these same conditions are independently associated with increased stroke risk.5 Atrial fibrillation combined with these comorbidities is particularly concerning.

Atrial fibrillation episodes may be symptomatic, asymptomatic (ie, silent AF), or both.2,6,7 Symptoms commonly associated with AF (all nonspecific) include palpitations, chest discomfort, dizziness or syncope, dyspnea, heart failure, and/or fatigue,2,7 but correlation between AF and symptoms is poor.8 Heart failure or stroke can be the first clinical manifestation of AF.

Other than in patients with cryptogenic stroke or implanted pacemakers/defibrillators (the latter having associated cardiac electrical disorders), silent AF incidence has not been well defined, to our knowledge. Importantly, in patients with implanted pacemakers/defibrillators, silent (sometimes also termed subclinical) AF episodes as brief as 5 minutes to 24 hours have been associated with increased stroke risk916 and are more common than symptomatic episodes.1518 Recognition of previously undiagnosed AF and initiation of appropriate/indicated therapies, including oral anticoagulation (OAC) therapy, is essential for stroke prevention.

Minimally invasive prolonged electrocardiographic monitoring with insertable cardiac monitors (ICMs) could facilitate early AF diagnosis and earlier treatment. However, the diagnostic yield in high-risk patients is not well known. The REVEAL AF study was therefore performed to determine the incidence of previously undiagnosed AF using ICMs in a high-risk population.

Methods
Trial Design

The REVEAL AF study is a prospective, single-arm, open-label, multicenter clinical study designed to establish the incidence of AF using an ICM (Reveal XT or Reveal LINQ; Medtronic). Detailed methods have been published previously.19,20

The study was supported by Medtronic and was conducted in compliance with applicable local laws and regulations of each participating country. The study protocol can be found in Supplement 1. Ethics committee or institutional review board approval was obtained at each institution (eAppendix in Supplement 2). All patients provided written informed consent prior to participation in the study. A steering committee was responsible for the study design, conduct, and reporting. Data monitoring, collection, and analysis were performed by the sponsor and steering committee in partnership.

Study Participants

Recruitment occurred at 57 clinical centers in the United States and Europe from November 2012 to June 2015. Patients with no AF history but deemed to be at risk based on demographic characteristics with or without symptoms were enrolled. All patients had either a CHADS2 score of 3 or greater or a score of 2 with at least 1 of the following AF risk factors: coronary artery disease, renal impairment, sleep apnea, or chronic obstructive pulmonary disease. All patients underwent 24 hours or more of external monitoring within 90 days prior to enrollment or before ICM insertion. Any AF was exclusionary.

Enrolled patients who received an ICM were observed for 18 or more months, until either their 30-month visit or until the last patient completed the 18-month visit. Patients had in-office visits every 6 months (plus unscheduled pro re nata) and transmitted device data monthly via remote monitoring (CareLink; Medtronic). The REVEAL AF study used the components of the Reveal ICM device. Devices were used in accordance with approved indications and were not paid for by the sponsor.

Study Outcomes

The primary outcome was the incidence of adjudicated AF 6 or more minutes in duration at 18 months. Secondary outcomes included predictors of AF and physician actions in response to AF detection. Additional exploratory objectives encompassed safety, AF incidence at additional time points, and comparison of AF incidence among CHADS2 subgroups and patients with vs without baseline symptoms.

Statistical Analysis

Sample size was chosen to (1) generate a 2-sided 95% CI for the 18-month incidence rate of AF that would be approximately 10 percentage points in width for an estimated event rate of 16% to 20% and (2) adequately power the secondary objectives. Standard statistical methods were used for summarization and analysis. To ensure a robust data set for subgroup analysis, a minimum of 70 patients with CHADS2 scores of 2, 3, and 4 or greater were included in each of these subgroups. Confidence intervals and any statistical significance testing used an α level of .05, unless otherwise stated. Tests of hypotheses were 2-tailed. Only adjudicated episodes, based on stored electrogram data, were included for analysis of the primary end point. Patients without an end point during follow-up were censored at the date of last device interrogation. The date of device implant was time 0 for survival analyses. A Cox proportional hazards model was used to identify predictors of AF, while log-rank tests were used to compare AF incidence among CHADS2 score subgroups and subgroups defined by presence of baseline symptoms, such as palpitations. Atrial fibrillation lasting 6 or more minutes was chosen as the primary end point because at the time this study was being designed, current evidence suggested that subclinical AF lasting 5 to 6 minutes or longer was associated with a significantly increased risk of stroke or systemic embolism in patients with a pacemaker14,15 and because the Reveal ICM has high sensitivity, specificity, and positive predictive value for detecting AF episodes of this duration.21

Results
Patient Characteristics

Of 446 patients screened, 394 (88.3%) underwent device insertion. Table 1 and eTable 1 in Supplement 2 summarize the devices used and baseline demographic characteristics in those who underwent device insertion. Procedure-related and/or device-related serious adverse events were infrequent (total, 13 [3.3%]; Reveal LINQ ICM, 6 [2.2%]; Reveal XT ICM, 7 [5.7%]; P = .12) and have been reported previously.19 There were 385 patients included in the primary end point analysis; of these, 326 (84.7%) reached the target 18-month follow-up (Figure 1). The mean (SD) age was 71.5 (9.9) years, and 297 (77.1%) were 65 years or older. See eTables 2 and 3 in Supplement 2 for details regarding study exits.

Primary Outcome

Final episode adjudication of the 10 850 device recordings revealed 6 or more minutes of AF in 128 participants, with an AF detection rate of 29.3% (95% CI, 24.4-33.8) at 18 months (Figure 2A). Atrial fibrillation detection rates at 30 days and 6, 12, 24, and 30 months were 6.2% (95% CI, 3.8-8.6), 20.4% (95% CI, 16.2-24.3), 27.1% (95% CI, 22.5-31.5), 33.6% (95% CI, 28.3-38.6), and 40.0% (95% CI, 33.6-45.8), respectively. Two sensitivity analyses were performed including all patients who exited the study prematurely; one assumed all patients had AF while the other assumed none had AF following their date of exit (the 2 extreme conditions). In the first, the 18-month incidence rate would have been 41.1%; in the second, 28.2%. Given our observed rate of 29.3%, it is possible the true incidence would have been higher had no patients exited early. Of the 128 patients with AF lasting 6 or more minutes, 113 (88.3%) had 30 or more minutes of AF, 97 (75.8%) had 1 or more hours of AF, and 53 (41.4%) had 6 or more hours of AF in a day at some point. Thirteen patients (10.2%) had at least 1 episode lasting 24 hours or longer. The time to onset of daily AF burden for the entire cohort, excluding events adjudicated to not be AF, is shown in Figure 2B. By 30 months, 35.6% (95% CI, 29.4-41.3) had at least 1 hour of AF in a day. Overall, the median (interquartile range) time from device insertion to first AF detection was 123 (41-330) days. There was no difference in AF detection rates between patients with or without any symptoms at enrollment.22 However, the AF detection rate at 18 months was higher in patients specifically with palpitations at baseline vs those without (35.3%; 95% CI, 29.0-42.6 vs 23.0%; 95% CI, 17.5-29.8; P = .02).

Other Outcomes

At 18 months, there was no significant difference in AF incidence between patients with CHADS2 scores of 2 (24.7%; 95% CI, 17.3-31.4), 3 (32.7%; 95% CI, 23.8- 40.7), or 4 or more (31.7%; 95% CI, 22.0-40.3) (Figure 2C). When individual baseline characteristics were assessed, only age (the strongest) and body mass index were significant independent predictors of AF, with AF incidence higher in older and more obese patients (Table 2). Biomarkers (brain natriuretic peptide, C-reactive protein, troponin-I, and thyrotropin) were also examined as predictors in a subset of patients, but the analysis was underpowered. No circulating biomarkers were predictive of AF when controlling for other prespecified clinical characteristics.

Among patients who met the primary outcome of 6 or more minutes of AF, 72 (56.3%) were prescribed OAC therapy and 19 (14.8%) were prescribed rhythm control at some point during follow-up. Treatment was not required per protocol. During the total 732.8 patient-years of follow-up among patients in the primary end point analysis, 132 patients (34.1%) experienced 1 or more health care uses, including 94 hospitalizations (12 associated with AF); 12 patients (3.1%) developed persistent AF (with 4 undergoing cardioversion).

There were 6 strokes in 6 patients (3 met the primary end point before the stroke event; 1 met the primary end point after having a stroke), and 12 transient ischemic attacks in 11 patients (all nonadjudicated). Their significance cannot be assessed owing to frequent initiation of OAC therapy on detection of AF.

Discussion

The at-risk population chosen for this study represents a common group of patients encountered clinically. Stroke is a high concern in patients with AF and does not require AF to be symptomatic. Results of the REVEAL AF study demonstrated a substantial incidence of previously undiagnosed AF (nearly 30%) at 18 months of follow-up in patients demographically at high risk of both AF and stroke. By 30 months, the detection rate increased to 40%. With a median time to AF detection of 123 days, most patients would not have been identified with shorter duration monitoring typical of external devices. Age and body mass index were found to be significant predictors of AF detection. In separate univariate assessments, palpitations at baseline were associated with a higher incidence of AF, but CHADS2 score was not. However, notably, in most large monitoring databases, palpitations are not specific for AF and often occur in association with sinus rhythm. Of patients who met the primary end point, 72 (56%) were prescribed OAC therapy. While the benefit of OAC in this patient population is unknown, ongoing anticoagulation trials for subclinical AF will provide insight (ie, Apixaban for the Reduction of Thromboembolism in Patients With Device-Detected Subclinical Atrial Fibrillation [ARTESiA; clinicaltrials.gov identifier: NCT01938248], Non–Vitamin K Antagonist Oral Anticoagulants in Patients With Atrial High Rate Episodes [NOAH; NCT02618577], and Atrial Fibrillation Detected by Continuous ECG Monitoring [LOOP; NCT02036450]). Additionally, results from the FIND-AF randomized trial23 suggest OAC therapy is beneficial for detected subclinical AF in patients with acute ischemic stroke.

Two smaller trials24,25 have also reported on the incidence of AF in high-risk populations using ICMs. The Prevalence of Sub-Clinical Atrial Fibrillation Using an Implantable Cardiac Monitor (ASSERT-II) study (NCT01694394)24 was a multicenter trial that enrolled 273 at-risk patients without known AF; 252 (92.3%) received an ICM and completed follow-up. The incidence rate of AF 5 or more minutes was 34.4% per person-year. The Predicting Atrial Fibrillation or Flutter (PREDATE-AF) study (NCT01851902)25 was a single-center trial of patients without known AF but with a CHA2DS2-VASc score of 2 or greater. In 245 patients, the incidence of AF or atrial flutter was 22% during an average follow-up of approximately 15 months. The mean time to detection was similar to the REVEAL AF study at 141 days. There was no difference in the AF detection rates between patients with CHA2DS2-VASc scores of 4 or less vs 5 or greater. Male sex was the only significant predictor of AF. Oral anticoagulation therapy was initiated in 76%. In contrast to both the PREDATE-AF study25 and the ASSERT-II study,24 the REVEAL AF study required a minimum of 24 hours of external monitoring without AF detected prior to device insertion. This, in addition to broader inclusion criteria, may explain the lower AF detection rate in the REVEAL AF study vs the ASSERT-II study.24

Other studies have also reported on the use of external monitors or smart phones to detect subclinical AF.2630 However, the AF incidence reported in such studies is low, as external monitors have a limited surveillance duration with lower diagnostic yield than ICMs. Furthermore, external devices cannot accurately determine AF burden, a parameter which may be related to the magnitude of stroke risk.31

While the primary end point in the REVEAL AF study was an AF episode lasting 6 or more minutes, many patients had prolonged cumulative periods of AF; the incidence of AF lasting 30 minutes or more in a day was greater than 40% at 30 months, and the corresponding incidence of AF lasting 6 or more hours in a day was nearly 20% at 30 months. Additionally, 10.2% of patients with 6 or more consecutive minutes of AF had at least 1 episode lasting 24 hours or longer. Both the Asymptomatic Atrial Fibrillation and Stroke Evaluation in Pacemaker Patients and the Atrial Fibrillation Reduction Atrial Pacing Trial (ASSERT)32 and the study by Israel et al33 demonstrated that even prolonged episodes of AF can be asymptomatic.

A recent subanalysis from ASSERT32 suggested that a 24-hour duration of subclinical AF may be critical for increased stroke risk. However, the mean CHADS2 score in ASSERT was only 2.2,32 and other reports suggest that risk is tied to synergism between AF duration and the severity of associated comorbidities rather than a specific AF duration.11,34 Importantly, pathophysiological changes in atrial tissue because of age, disease, or genetics may promote stasis and/or alter atrial endothelial function with resultant thromboembolic risk. Similar dysfunction may also be consequent to AF itself and can be additive to dysfunction produced by underlying comorbidities. The abnormal atrial milieu that underlies thrombogenesis may persist when an episode of AF ends. Thus, the duration of AF that is critical is likely not a single specific value. Moreover, the 24-hour duration has not been confirmed in other trials. Accordingly, we cannot yet determine in a given patient what degree subclinical AF is causative of embolization or whether it is just a risk marker.

Does the thromboembolic risk associated with relatively brief durations of AF justify their detection with prolonged monitoring? In the Atrial Fibrillation Follow-up Investigation of Rhythm Management (AFFIRM) trial,35 nonsustained, asymptomatic episodes of AF carried the same risk for stroke as symptomatic AF. Data gathered by device interrogation from patients with implanted pacemakers and defibrillators suggest that as little as 6 minutes to 6 hours of AF may double incident stroke risk,1315,36 yet such observations may not be relevant in patients without electrical disorders requiring a cardiac rhythm management device. It is also unknown whether treating such brief AF episodes with OAC therapy would significantly reduce stroke risk. Importantly, 3 trials (ARTESIA, NOAH, and LOOP) are underway to assess the potential role of OAC therapy in patients with device-detected AF.

It is noteworthy that based on the information available from the ICM, 56% of patients in the REVEAL AF study who met the primary end point received a new prescription for OACs, as did 76% of patients in the PREDATE AF study.25 Interestingly, this is lower than rates observed with ICM monitoring in patients with cryptogenic stroke37 and in response to AF detection clinically.38 For patients with cryptogenic stroke, the threshold to treat is likely lower owing to previous stroke history. Currently, to our knowledge, there are no data to prove the efficacy of OAC therapy in the REVEAL AF population, but this is currently under investigation in the LOOP trial. Nonetheless, REVEAL AF results support further studies to assess whether ICM-based screening for AF may be beneficial and cost-effective for stroke prevention in specific high-risk populations and demonstrate that high-risk patients were willing to undergo ICM monitoring for AF screening

Limitations

Although the REVEAL AF study is, to our knowledge, the largest trial assessing the use of ICMs for AF detection in high-risk patients, it remains modest in size. Nonetheless, the PREDATE AF,25 ASSERT-II,24 and REVEAL AF studies are concordant in finding that previously undetected AF is common in high-risk patients. Second, we were unable to assess the embolic risk posed by device-detected AF because of the small number of strokes during follow-up and potential confounding by anticoagulation use. Third, the positive predictive value of ICMs for AF depends on episode duration, device settings, and AF incidence in the population monitored.39 In the REVEAL AF study, devices were programmed to favor sensitivity, as this was an exploratory study in a new patient population. Importantly, all episodes that met the primary end point definition were adjudicated. Fourth, given the size of our study, the low enrollment rate, and premature dropouts, it is difficult to determine the external validity of this study cohort to the general population. However, the relative consistency of findings with the PREDATE AF study,25 ASSERT-II,24 and the pacemaker/ICD population suggests that the REVEAL AF cohort likely is representative of the general population.

Conclusions

Atrial fibrillation 6 or more minutes is frequently detected with ICM monitoring in patients with previously unknown AF but with demographic factors (with or without symptoms) that place them at risk of both AF and stroke. As the AF incidence was still rising at 30 months, the ideal monitoring duration is unclear. Our findings have important implications for AF screening and stroke prevention in this population.

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Article Information

Corresponding Author: James A. Reiffel, MD, Columbia University College of Physicians and Surgeons, 630 W 168th St, New York, NY 10032 (jar2@columbia.edu).

Accepted for Publication: July 26, 2017.

Published Online: August 26, 2017. doi:10.1001/jamacardio.2017.3180

Open Access: This article is published under the JN-OA license and is free to read on the day of publication.

Author Contributions: Dr Reiffel had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Reiffel, Verma, Kowey, Halperin, Ziegler.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Reiffel, Verma, Kowey, Pouliot.

Critical revision of the manuscript for important intellectual content: Reiffel, Verma, Kowey, Halperin, Gersh, Wachter, Ziegler.

Statistical analysis: Verma, Pouliot.

Administrative, technical, or material support: Reiffel, Ziegler.

Supervision: Reiffel, Verma, Kowey, Halperin.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Drs Reiffel, Verma, Kowey, Halperin, Gersh, and Wachter are consultants for and receive modest honoraria from Medtronic. Ms Pouliot and Mr Ziegler are employed by and stock owners of Medtronic.

Funding/Support: This study was sponsored by Medtronic. Funding was provided for non–standard of care procedures. Devices were used within current indications and were not paid for by Medtronic.

Role of the Funder/Sponsor: The Steering Committee (authors of this manuscript) plus specific Medtronic personnel were involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Group Information: In addition to the listed authors, the REVEAL AF Investigators include the following: Devender Akula, MD (Lourdes Cardiology Services, Voorhees, New Jersey); Hetal Bhakta, MD (Desert Heart Rhythm Consultants, Palm Springs, California); William Bowden, MD (Healdsburg Cardiology, Windsor, California); Johannes Brachmann, MD, PhD (Klinikum Coburg, Coburg, Germany); Sukesh Burjonroppa, MD (Baylor Research Institute, Fort Worth, Texas); Melissa Carry, MD (Baylor Heart and Vascular Hospital, Dallas, Texas); Bernardo De la Guardia, MD (Woodlands North Houston Heart and Vein Center, The Woodlands, Texas); Lukas R. C. Dekker, MD, PhD (Catharina Ziekenhuis, Eindhoven, the Netherlands); Frederick Ehlert, MD (New York-Presbyterian Hospital/Columbia University Medical Center, New York); Jay Erlebacher, MD (Englewood Hospital and Medical Center, Englewood, New Jersey); Douglas Esberg, MD (Lankenau Institute for Medical Research, Wynnewood, Pennsylvania); Steven Fera, MD (South County Cardiology, Wakefield, Rhode Island); Scott Ferreira, MD (Saint Louis University Hospital, St Louis, Missouri); Alfredo Figueroa, MD (Jackson Heart Clinic, Jackson, Mississippi); Malcolm Foster, MD (Turkey Creek Medical Center, Knoxville, Tennessee); Samir Germanwala, DO (Longview Regional Medical Center, Longview, Texas); Eve Gillespie, MD (Glacier View Research Institute Cardiology, Kalispell, Montana); Taya Glotzer, MD (Hackensack University Medical Center, Hackensack, New Jersey); Richard Gordon, MD (The Stern Cardiovascular Foundation, Germantown, Tennessee); Michael Isaac, MD (Medical City Dallas Hospital, Dallas, Texas); Rajesh Kabra, MD (Sutherland Cardiology Clinic, Germantown, Tennessee); Sunil Kakkar, MD (Cardiac Clinic, Kissimmee, Florida); Stephen Keim, MD (Delmarva Heart Research Foundation Inc, Salisbury, Maryland); Shakeel Khan, MD (Phoenix Heart, PLLC, Glendale, Arizona); Jay Koons, MD, PhD (The Cardiac and Vascular Institute, Gainesville, Florida); Karl-Heinz Kuck, MD, PhD (Asklepios Klinik Sankt Georg, Hamburg, Germany); Joshua Leichman, MD (Salem Cardiovascular Associates, Salem, Oregon); Aziz Maksoud, MD (Cardiovascular Consultants of Kansas, Wichita); Martin Matsumura, MD (The Heart Care Group PC, Allentown, Pennsylvania); Jordi Mercé, MD, PhD (Hospital Universitari de Tarragona Joan XXIII, Tarragona, Spain); Marc Miller, MD (Icahn School of Medicine at Mount Sinai, New York, New York); Suneet Mittal, MD (The Valley Hospital, Ridgewood, New Jersey); Giulio Molon, MD (Ospedale Classificato ed Equiparato Sacro Cuore–Don Calabria, Verona, Italy); Philip Morales, MD (Baylor Research Institute, Plano, Texas); Marc Newell, MD (Minneapolis Heart Institute Foundation, Minneapolis, Minnesota); Eugene Parent, MD (Bradenton Cardiology, Bradenton, Florida); James Parks, MD (Southview Cardiovascular Associates, Birmingham, Alabama); Christian Perings, MD (Klinikum Lünen St. Marien Hospital–Akademisches Lehrkrankenhaus der Westfälischen Wilhelms-Un, Lünen, Germany); Michael Peterson, MD (United Heart and Vascular Clinic, Saint Paul, Minnesota); Rhea Pimentel, MD (The University Kansas Medical Center Research Institute, Kansas City); Helmut Friedrich Puererfellner, MD (Allgemein Öffentliches Krankenhaus der Elisabethinen Linz, Linz, Austria); Rita Riedlbauer, MD (Landeskrankenhaus–Universitätsklinikum Graz, Graz, Austria); Giovanni Rovaris, MD (Azienda Ospedaliera San Gerardo, Monza, Italy); Steven Rowe, MD (Cox Medical Center South, Springfield, Missouri); Ruby Satpathy, MD (CHI Health Clinic Cardiology Bergan, Omaha, Nebraska); Jan Schmidt, MD (Universitätsklinikum Düsseldorf, Düsseldorf, Germany); Jürgen Schreieck, MD (Eberhard Karls Universität Tübingen–Universitätsklinikum Tübingen, Tübingen, Germany); Gaetano Senatore, MD (Ospedale Civile di Ciriè, Torino, Italy); Rick Simons, MD (Nanticoke Cardiology, Seaford, Delaware); Matjaz Sinkovec, MD (University Medical Centre Ljubljana, Ljubljana, Slovenia); John Strobel, MD (Premier HealthCare, Bloomington, Indiana); Rohit Sundrani, MD (Cardiovascular Consultants Heart Center, Fresno, California); Satish Surabhi, MD (AnMed Health, Andreson, South Carolina); Michael Tamberella, MD (Caromont Regional Medical Center, Gastonia, North Carolina); Venkat Tholakanahalli, MD (Minneapolis VA Health Care System, Minneapolis, Minnesota); Selcuk Tombul, DO (private practice, Chattanooga, Tennessee); Subha Varahan, MD (Oklahoma Heart Hospital Research Foundation, Oklahoma City); Rolf Wachter, MD (Universitätsmedizin Göttingen Georg–August-Universität, Göttingen, Germany); Peter Wassmer, MD (Northside Hospital, Saint Petersburg, Florida); Matthew Weinberg, MD (ProHealth Care, Waukesha, Wisconsin); Maurits Christoffel Emile Franciscus Wijffels, MD, PhD (St. Antonius Ziekenhuis, Nieuwegein, the Netherlands); Chakri Yarlagadda, MD (Mercy Health–Saint Elizabeth Youngstown Hospital, Youngstown, Ohio); and Andrew Yen, MD (North Georgia Heart Foundation, Gainesville).

Meeting Presentation: A summary of these results was presented at the Heart Rhythm Society Annual Scientific Sessions; May 12, 2017; Chicago, Illinois. Additionally, a summary of these results was presented at the European Society of Cardiology Congress 2017; August 26, 2017; Barcelona, Spain.

Additional Contributions: We thank Medtronic Senior Principal Statistician Lou Sherfesee, PhD, for his contributions to the review and analysis of study data, and Medtronic Senior Clinical Research Specialist Rachelle Kaplon, PhD, for her work managing the REVEAL AF study and reviewing the manuscript. Drs Sherfesee and Kaplon are employees of Medtronic and received compensation for their contributions.

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