Screening for Atrial Fibrillation in the Older Population: A Randomized Clinical Trial

David J Gladstone; Rolf Wachter; Katharina Schmalstieg-Bahr; F Russell Quinn; Eva Hummers; Noah Ivers; Tamara Marsden; Andrea Thornton; Angie Djuric; Johanna Suerbaum; Doris von Grünhagen; William F McIntyre; Alexander P Benz; Jorge A Wong; Fatima Merali; Sam Henein; Chris Nichol; Stuart J Connolly; Jeff S Healey

doi:10.1001/jamacardio.2021.0038

. 2021 Feb 24;6(5):1–10. doi: 10.1001/jamacardio.2021.0038

Screening for Atrial Fibrillation in the Older Population

A Randomized Clinical Trial

David J Gladstone ^1,^2,^✉, Rolf Wachter ^3,^4,⁵, Katharina Schmalstieg-Bahr ^6,⁷, F Russell Quinn ⁸, Eva Hummers ^5,⁶, Noah Ivers ⁹, Tamara Marsden ¹⁰, Andrea Thornton ¹⁰, Angie Djuric ¹⁰, Johanna Suerbaum ^4,⁵, Doris von Grünhagen ¹¹, William F McIntyre ¹⁰, Alexander P Benz ¹⁰, Jorge A Wong ¹⁰, Fatima Merali ¹², Sam Henein ¹³, Chris Nichol ¹⁴, Stuart J Connolly ¹⁰, Jeff S Healey ¹⁰, for the SCREEN-AF Investigators and Coordinators

¹Hurvitz Brain Sciences Program, Sunnybrook Research Institute, and Division of Neurology, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada

²Division of Neurology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada

³Clinic and Policlinic for Cardiology, University Hospital, Leipzig, Germany

⁴Department of Cardiology, University Medical Center Göttingen, Göttingen, Germany

⁵DZHK (German Centre for Cardiovascular Research), partner site Göttingen, Göttingen, Germany

⁶Department of General Practice, University Medical Center Göttingen, Göttingen, Germany

⁷Department of General Practice and Primary Care, University Medical Center Hamburg-Eppendorf, Hamburg-Eppendorf, Germany

⁸Libin Cardiovascular Institute, University of Calgary, Calgary, Alberta, Canada

⁹Women’s College Hospital, Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada

¹⁰Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada

¹¹Clinic for Cardiology and Pneumology, University Medicine Göttingen, Göttingen, Germany

¹²LMC Manna Research, Burlington, Ontario, Canada

¹³Southlake Regional Health Centre, Newmarket, Ontario, Canada

¹⁴Camrose Primary Care Network, Camrose, Alberta, Canada

Group Information: The SCREEN-AF Investigators and Coordinators are listed at the end of this article.

Accepted for Publication: December 22, 2020.

Published Online: February 24, 2021. doi:10.1001/jamacardio.2021.0038

^✉

Corresponding Author: David J. Gladstone, MD, PhD, Sunnybrook Research Institute, University of Toronto Department of Medicine, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada (david.gladstone@sunnybrook.ca).

Author Contributions: Drs Gladstone and Marsden had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Gladstone and Wachter are co–principal authors.

Concept and design: Gladstone, Quinn, Hummers, Ivers, Healey.

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

Drafting of the manuscript: Gladstone, Wachter, Schmalstieg-Bahr, Ivers, Thornton, Djuric, Merali.

Critical revision of the manuscript for important intellectual content: Gladstone, Wachter, Schmalstieg-Bahr, Quinn, Hummers, Ivers, Marsden, Suerbaum, von Grunhagen, McIntyre, Benz, Wong, Henein, Nichol, Connolly, Healey.

Statistical analysis: Gladstone, Marsden.

Obtained funding: Gladstone, Wachter, Hummers, Healey.

Administrative, technical, or material support: Wachter, Schmalstieg-Bahr, Hummers, Thornton, Djuric, Suerbaum, von Grunhagen, Wong, Healey.

Supervision: Wachter, Hummers, Merali, Henein, Nichol, Connolly.

Conflict of Interest Disclosures: Dr Gladstone reported receiving an operating grant from the Canadian Stroke Prevention Intervention Network (C-SPIN) for the SCREEN-AF trial (C-SPIN is a peer-reviewed national network grant funded by the Canadian Institutes of Health Research [CIHR]) during the conduct of the study; a Heart and Stroke Foundation of Canada Mid-Career Investigator Award, grants from Ontario Genomics peer-reviewed operating grant, and grants from CIHR-funded C-SPIN Network operating grant for the Ontario Holter/Echo Database Study outside the submitted work; in addition, he is chair of the Secondary Stroke Prevention Guidelines Committee for the Canadian Stroke Best Practice Recommendations (uncompensated); member of the Canadian Cardiovascular Society Atrial Fibrillation Guidelines Committee (uncompensated); he served as a site principal investigator for the NAVIGATE ESUS and NASPAF-ICH trials (all site fees paid to his institution); and he is a Canadian national coleader of the National Institute of Neurological Disorders and Stroke–sponsored ARCADIA trial. He previously served as an independent medical safety monitor for ARCADIA (uncompensated). Dr Gladstone had no personal financial relationships with pharmaceutical companies or cardiac monitoring device manufacturers in the past more than 4 years. Dr Wachter reported receiving grants from Deutsches Zentrum für Herz-/Kreislaufforschung during the conduct of the study, Deutsche Forschungsgemeinschaft, European Union, Bundesministerium für Bildung und Forschung, and Boehringer Ingelheim; personal fees from Bayer, Boehringer Ingelheim, CVRx, Daiichi, BMS, Medtronic, Novartis, Pfizer, Pharmacosmos, and Servier outside the submitted work. Dr Schmalstieg-Bahr reported receiving grants from German Centre for Cardiovascular Research (DZHK), which financed her position within the research team during the conduct of the study. Dr Quinn reported receiving personal fees from BMS-Pfizer and grants from Bayer outside the submitted work. Dr Hummers reported receiving peer-reviewed grants from the German Centre for Cardiovascular Research and Canadian Stroke Prevention Intervention Network, and nonfinancial support from iRhythm technologies during the conduct of the study. Dr Suerbaum reported the German Centre of Cardiovascular Research Scholarship allowed her to participate in the project. Dr McIntyre reported speaking fees from Servier and Bayer outside the submitted work. Dr Healey reported receiving grants from Boehringer-Ingelheim C-SPIN network during the conduct of the study; grants from BMS/Pfizer, Bayer, Medtronic, and Abbott outside the submitted work; and personal fees from Servier. No other disclosures were reported.

Funding/Support: The trial was funded by C-SPIN, a peer-reviewed national network grant from the CIHR; a peer-reviewed operating grant (FKZ 81X1300111) from the German Centre for Cardiovascular Research (DZHK); Boehringer Ingelheim; and in-kind support from Microlife Corp, ManthaMed, and iRhythm. In Germany, the trial was carried out using the Clinical Research Platform of the DZHK.

Role of the Funder/Sponsor: The device manufacturers and funders had no role in study design, data collection, analysis, interpretation, or manuscript preparation. Zio patch reports and ECG tracings provided by iRhythm underwent central study adjudication and analysis by the trial statistician and steering committee, independent of industry.

Group Information: The SCREEN-AF Steering Committee members are David J. Gladstone, MD, PhD, Jeff S. Healey, MD, MSc, F. Russell Quinn, MD, PhD, Noah Ivers, Rolf Wachter, MD, Katharina Schmalstieg-Bahr, MD, Eva Hummers, MD, PhD, Andrea Thornton, BSc, and Angie Djuric; the clinical events adjudication committee comprised Demetrios J. Sahlas, MD, Ashkan Shoamanesh, MD, and Mukul Sharma, MD; and the AF adjudication committee included F. Russell Quinn, MD, PhD, Alexander P. Benz, MD, William F. McIntyre, MD, and Jorge A. Wong, MD, MPH.

Data Sharing Statement: See Supplement 3.

^✉

Corresponding author.

PMCID: PMC7905702 PMID: 33625468

Key Points

Question

Will screening older individuals for atrial fibrillation with a wearable electrocardiographic monitor be feasible, detect a high rate of atrial fibrillation, and lead to anticoagulation for most patients?

Findings

In a randomized clinical trial of 856 participants aged 75 years or older with hypertension from outpatient primary care practices, new atrial fibrillation was detected in 5.3% of the screening group vs 0.5% of the control group. Median atrial fibrillation duration on continuous electrocardiographic monitoring was 6.3 hours, and anticoagulation was prescribed to 75.0% of the participants with screen-detected atrial fibrillation.

Meaning

In this trial, a wearable electrocardiogram-based screening intervention increased atrial fibrillation detection 10-fold and prompted anticoagulation in most cases; this strategy warrants evaluation to prevent stroke.

Abstract

Importance

Atrial fibrillation (AF) is a major cause of preventable strokes. Screening asymptomatic individuals for AF may increase anticoagulant use for stroke prevention.

Objective

To evaluate 2 home-based AF screening interventions.

Design, Setting, and Participants

This multicenter randomized clinical trial recruited individuals from primary care practices aged 75 years or older with hypertension and without known AF. From April 5, 2015, to March 26, 2019, 856 participants were enrolled from 48 practices.

Interventions

The control group received standard care (routine clinical follow-up plus a pulse check and heart auscultation at baseline and 6 months). The screening group received a 2-week continuous electrocardiographic (cECG) patch monitor to wear at baseline and at 3 months, in addition to standard care. The screening group also received automated home blood pressure (BP) machines with oscillometric AF screening capability to use twice-daily during the cECG monitoring periods.

Main Outcomes and Measures

With intention-to-screen analysis, the primary outcome was AF detected by cECG monitoring or clinically within 6 months. Secondary outcomes included anticoagulant use, device adherence, and AF detection by BP monitors.

Results

Of the 856 participants, 487 were women (56.9%); mean (SD) age was 80.0 (4.0) years. Median cECG wear time was 27.4 of 28 days (interquartile range [IQR], 18.4-28.0 days). In the primary analysis, AF was detected in 23 of 434 participants (5.3%) in the screening group vs 2 of 422 (0.5%) in the control group (relative risk, 11.2; 95% CI, 2.7-47.1; P = .001; absolute difference, 4.8%; 95% CI, 2.6%-7.0%; P < .001; number needed to screen, 21). Of those with cECG-detected AF, median total time spent in AF was 6.3 hours (IQR, 4.2-14.0 hours; range 1.3 hours-28 days), and median duration of the longest AF episode was 5.7 hours (IQR, 2.9-12.9 hours). Anticoagulation was initiated in 15 of 20 patients (75.0%) with cECG-detected AF. By 6 months, anticoagulant therapy had been prescribed for 18 of 434 participants (4.1%) in the screening group vs 4 of 422 (0.9%) in the control group (relative risk, 4.4; 95% CI, 1.5-12.8; P = .007; absolute difference, 3.2%; 95% CI, 1.1%-5.3%; P = .003). Twice-daily AF screening using the home BP monitor had a sensitivity of 35.0% (95% CI, 15.4%-59.2%), specificity of 81.0% (95% CI, 76.7%-84.8%), positive predictive value of 8.9% (95% CI, 4.9%-15.5%), and negative predictive value of 95.9% (95% CI, 94.5%-97.0%). Adverse skin reactions requiring premature discontinuation of cECG monitoring occurred in 5 of 434 participants (1.2%).

Conclusions and Relevance

In this randomized clinical trial, among older community-dwelling individuals with hypertension, AF screening with a wearable cECG monitor was well tolerated, increased AF detection 10-fold, and prompted initiation of anticoagulant therapy in most cases. Compared with continuous ECG, intermittent oscillometric screening with a BP monitor was an inferior strategy for detecting paroxysmal AF. Large trials with hard clinical outcomes are now needed to evaluate the potential benefits and harms of AF screening.

Trial Registration

ClinicalTrials.gov Identifier: NCT02392754

This randomized clinical trial evaluates the use of continuous electrographic monitoring with a patch in older patients with hypertension to detect atrial fibrillation.

Introduction

Atrial fibrillation (AF) is one of the most common treatable risk factors for stroke, and its prevalence is increasing.^1,2 By age 55 years, the lifetime risk of developing AF in the US is 1 in 3.³ When AF is identified, initiation of oral anticoagulant therapy (OAC) can prevent two-thirds of strokes. However, AF often goes undetected and untreated because it is frequently short-lasting and asymptomatic, and stroke can be its first manifestation.^4,5,6 Approximately 10% to 20% of ischemic strokes are attributed to previously undiagnosed AF,⁷ and AF-associated strokes tend to be more disabling and more often fatal compared with other types of ischemic strokes.⁸ If screening can effectively detect sufficient numbers of individuals with AF and trigger initiation of OAC, many strokes could potentially be prevented.

Interest in AF screening has increased with advances in wearable technologies for arrhythmia detection^9,10 and the availability of safer and highly effective OAC medications for stroke prevention.¹¹ In the secondary prevention context, among patients with recent ischemic stroke, ambulatory electrocardiographic (ECG) monitoring with wearable or implanted devices detects AF in 15% to 30% of patients.^12,13,14,15 However, the concept of primary prevention screening for AF in asymptomatic individuals remains controversial.^16,17,18 Randomized clinical trials are lacking to determine which patients merit screening, how best to screen, and whether screening will prevent stroke. In primary care, routine screening for AF is either not performed or is limited to a random pulse check or single opportunistic ECG. According to European guidelines, “systematic ECG screening should be considered to detect AF in individuals aged 75 years or older or those at high risk of stroke.”¹⁹^(p3) However, the US Preventive Services Task Force recommended against routine ECG screening for AF, citing insufficient evidence.²⁰

We conducted a randomized clinical trial of AF screening in older community-dwelling individuals without known AF using a wearable continuous ECG (cECG) patch monitor vs standard care. The secondary objective assessed whether AF detection led to OAC treatment. Within the screening group, we also evaluated an automated home blood pressure (BP) device for oscillometric AF screening.

Methods

Trial Design, Setting, and Oversight

SCREEN-AF was an investigator-initiated, multicenter, open-label, randomized clinical trial investigating noninvasive home-based AF screening interventions. Participants were recruited from primary care clinics in Canada and Germany. Participants provided written informed consent and were not paid to participate. The study protocol and prespecified statistical analysis plan are available in Supplement 1. The study was funded by peer-reviewed national government grants, coordinated at the Population Health Research Institute, Hamilton, Canada, and approved by the national regulatory authorities and research ethics committees representing all sites. The list of site principal investigators and individuals who provided statistical assistance and study coordination is available in the eAppendix in Supplement 2. This study followed the Consolidated Standards of Reporting Trials (CONSORT) reporting guideline for randomized clinical trials.

Participants

We recruited community-dwelling individuals aged 75 years or older without known AF who were not receiving OAC but were potential OAC candidates if AF was diagnosed (CHADS₂ [congestive heart failure, hypertension, age ≥75 years, diabetes, stroke]) score ≥2, indicating moderate or high risk for stroke, and no OAC contraindications). All participants had a history of hypertension requiring antihypertensive medication and were in sinus rhythm at enrollment as assessed by 30-second pulse palpation and heart auscultation by enrolling physicians (eTable 1 in Supplement 2). Key exclusion criteria were previously documented AF or atrial flutter, pacemaker, defibrillator, or implanted loop recorder.

At Canadian sites, patients attending regularly scheduled outpatient visits were screened for eligibility and offered study participation. Study visits were conducted by local investigators and coordinators. German sites screened electronic records for potentially eligible patients and sent invitation letters. A mobile study team (physician, nurse, and medical student) performed study procedures; 6-month visits were conducted by the patients’ family physician.

Randomization

Eligible participants were randomly allocated (1:1) to the screening group or control group via web-based randomization using computer-generated random block sizes of 4 and 6, stratified by center. The control group received standard clinical care and follow-up for 6 months, including pulse check and heart auscultation by a physician at baseline and 6 months. The screening group received a 2-week ambulatory cECG patch monitor, one at baseline and another at 3 months, in addition to standard care. The screening group also received an automated home BP monitor with an AF screening algorithm to be used twice daily during each of the 2-week cECG monitoring periods.

Study Interventions

We studied an adhesive patch cECG (Zio XT; iRhythm Technologies), a miniature, single-lead Holter-type device worn on the chest that provides up to 2 weeks of continuous ECG recording.^{21,22,23,24,25} It was applied by study personnel immediately after randomization, with instructions to wear it for 2 weeks, including sleep and showering. At 3 months, participants returned to receive another 2-week cECG. Devices were mailed back for central interpretation. Results were sent to each participant’s primary care physician who was responsible for clinical treatment decisions.

The home BP monitor (WatchBP-Home A; Microlife Corp) has been endorsed as an AF screening tool.^26,27,28,29 Participants in the screening group were instructed to record their home BP twice daily (morning and evening) during each of the cECG monitoring periods. Each assessment consisted of 3 sequential BP measurements; a positive AF screen was indicated if 2 or more of the 3 consecutive measurements were positive for AF. Participants and clinicians were advised not to act upon the home BP monitor AF screening results.

Assessments

Study visits were conducted in the clinic at baseline, 3 months, and 6 months. Baseline assessments collected data via patient interview and medical records review on demographics, medical history, and medications, and measured pulse and BP. Follow-up assessments recorded medications and any interim outcome events; specifically, any new clinical diagnosis of AF, ischemic or hemorrhagic stroke, transient ischemic attack, systemic embolism, major bleeding, death, and physician/hospital visits. For all outcome events, original source documents were requested for central adjudication (ECG tracings, hospital records).

Outcomes

The primary outcome was detection of AF within 6 months postrandomization, either by study cECG monitors or as part of routine clinical care. We defined AF for the primary outcome as 1 or more episode of continuous AF or atrial flutter lasting more than 5 minutes on cECG or diagnosed clinically (12-lead ECG or other source documentation). All AF outcome events (from cECG and site-reported clinical AF diagnoses) underwent central adjudication by 2 arrhythmia physicians (F.R.Q., W.F.M., A.P.B., and J.A.W.) blinded to randomization group.

The secondary outcome was OAC use at 6 months. Additional outcomes included device adherence, tolerability, detection of other prespecified arrhythmias, health care use, and AF screening performance of the home BP monitor. Site-reported clinical events (stroke, transient ischemic attack, and systemic embolism) underwent central blinded adjudication by 2 neurologists.

Statistical Analysis

Sample size calculations are reported in the eMethods in Supplement 2. All analyses were performed using SAS, version 9.4 (SAS Institute Inc), using an intention-to-screen principle of all randomized patients, regardless of device use, adherence, or duration of participation. Categorical variables are presented as numbers and percentages, and groups were compared using χ² tests or Fisher exact tests for small samples. Continuous variables are presented as means (SDs) or medians and interquartile ranges (IQRs), and groups were compared using the t tests or Wilcoxon rank sum tests if normality was questionable. Missing values were treated as missing and no imputation was done for any analyses.

The primary analysis compared the proportion of participants in each group achieving the primary outcome of AF detection using the χ² test and is presented with relative risk and corresponding 95% CI from a modified Poisson regression model with robust error variances. The absolute risk difference is also reported along with 95% CI. A 2-sided significance level of P < .05 was used for all analyses. A planned per-protocol analysis evaluated the primary outcome among patients who wore 2 cECG monitors for 12 or more days each.

For patients with the primary outcome of AF detected by cECG, we summarized the time to first AF detection, number and longest duration of AF episodes, total time in AF, and AF burden (percentage of analyzable time spent in AF per cECG monitor). Adherence was measured by cECG wear times (automatically time-stamped by the device). Tolerability was measured by patient satisfaction surveys and incidence of adverse skin reactions.

For the BP monitor analysis, we estimated sensitivity, specificity, and positive and negative predictive values at the patient level using the simultaneously acquired cECG results as the standard for AF detection. Post hoc, we separately considered AF duration of more than 24 hours and AF duration of less than 24 hours. Details are available in the eMethods in Supplement 2. We compared the number of physician visits, hospitalizations, and emergency department visits at 6 months between groups using the Poisson regression model with log as the link function.

Results

Patient Characteristics

From April 5, 2015, to March 26, 2019, 856 participants (555 from Canada, 301 from Germany) underwent randomization: 434 were assigned to the screening group and 422 to the control group. Follow-up was complete in 95.6% of the participants at 3 months and 92.6% at 6 months (Figure 1). There were no interim analyses. Baseline patient characteristics were balanced between groups (Table 1). Mean (SD) age was 80.0 (4.0) years, 487 participants (56.9%) were women, 369 were men (43.1%), with a median score of 4 points (IQR, 4-5 points) on the CHA₂DS₂-VASc (congestive heart failure, hypertension, age ≥75 years, diabetes, stroke or transient ischemic attack, vascular disease, age 65-74 years, sex category) scale.

Figure 1. — ECG indicates electrocardiograhic.

Table 1. Patient Characteristics.

Characteristic	No. (%)
Characteristic	Screening group (n = 434)	Control group (n = 422)
Age, mean (SD), y	79.8 (3.8)	80.1 (4.1)
Sex
Female	255 (58.8)	232 (55.0)
Male	179 (41.2)	190 (45.0)
Location
Canada	283 (65.2)	272 (64.4)
Germany	151 (34.8)	150 (35.5)
Race/ethnicity
White	409 (94.2)	397 (94.1)
Black	7 (1.6)	6 (1.4)
Asian	14 (3.2)	13 (3.1)
Other^a	4 (0.9)	6 (1.4)
Baseline blood pressure, mean (SD), mm Hg
Systolic	140 (17.1)	141 (17.9)
Diastolic	75.1 (9.5)	74.6 (9.9)
Height, mean (SD), cm	165 (10.6)	165 (9.7)
Weight, mean (SD), kg	76.9 (16.4)	76.1 (16.2)
BMI, mean (SD)	28.1 (5.4)	27.8 (5.4)
CHA₂DS₂-VASc score, median (IQR)	4.0 (4.0-5.0)	4.0 (4.0-5.0)
Medical history
Diabetes	102 (23.7)	103 (24.4)
Congestive heart failure	16 (3.7)	19 (4.5)
Ischemic stroke, TIA, or systemic embolism	40 (9.3)	43 (10.2)
Coronary artery disease	72 (16.7)	80 (19.0)
Coronary angioplasty/coronary stent	47 (10.9)	46 (10.9)
Myocardial infarction	42 (9.7)	38 (9.0)
Hyperlipidemia	241 (56.0)	234 (55.5)
Severe aortic or mitral valve disease	4 (0.9)	4 (0.9)
Rheumatic valve disease	3 (0.7)	1 (0.2)
Prosthetic heart valve	3 (0.7)	1 (0.2)
Sleep apnea	31 (7.2)	23 (5.5)
Dialysis	0	0
Cardiac surgery
CABG	20 (4.6)	29 (6.9)
Valve surgery	4 (0.9)	3 (0.7)
Peripheral artery disease (aortic plaque)	26 (6.0)	24 (5.7)
Dementia	6 (1.4)	2 (0.5)
Smoker
Current	26 (6.0)	20 (4.7)
Past	153 (38.0)	154 (38.3)
History of any palpitations in past year (patient self-report)	73 (16.9)	75 (17.8)

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Abbreviations: BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); CABG, coronary artery bypass graft; CHA₂DS₂-VASc, congestive heart failure, hypertension, age ≥75 years, diabetes, stroke or transient ischemic attack, vascular disease, age 65-74 years, sex category; TIA, transient ischemic attack.

^{^a}

Other includes the following categories: Hispanic/Latino, Middle Eastern, Aboriginal, and Other.

Adherence to cECG Monitoring

The first cECG monitor was worn by 423 participants (97.5%), and a second monitor was worn by 344 individuals (79.3%). Overall, 93.8% of the participants completed at least 1 week of monitoring, 85.9% completed at least 2 weeks, and 74.2% completed at least 3 weeks. Median wear times were 14.0 days (IQR, 13.4-14.0 days) for the first monitoring period, 13.9 days (IQR, 9.8-14.0 days) for the second monitoring period, and 27.5 days (IQR, 20.4-28.0 days) in total. The ECG quality (signal-to-noise) was high, yielding a median analyzable time of 13.7 days (IQR, 12.9-14.0 days) for the first monitoring period, 13.5 days (IQR, 8.0-13.9 days) for the second monitoring period, and 26.8 days (IQR, 15.6-27.7 days) in total.

AF Detection

In the intention-to-screen analysis, the primary outcome of AF detection at 6 months occurred in 23 of 434 participants (5.3%) in the screening group vs 2 of 422 (0.5%) in the control group (relative risk, 11.2; 95% CI, 2.7-47.1; P = .001; absolute difference, 4.8%; 95% CI, 2.6%-7.0%; P < .001; number-needed-to-screen, 21). Sensitivity analysis using a different AF definition yielded similar results (eResults in Supplement 2). Results did not differ substantially by country. In the screening group, 20 of 23 of the AF cases (87.0%) were detected by the cECG monitors and 3 of 23 (13.0%) were diagnosed clinically (these 3 patients presented to the hospital with symptomatic ECG-documented AF).

In a per-protocol analysis restricted to patients with the highest level of adherence (wearing both cECG monitors for at least 12 days each, n = 294), the primary outcome was detected in 17 of 294 individuals (5.8%) in the screening group vs 2 of 422 (0.5%) in the control group (relative risk, 12.2; 95% CI, 2.8-52.4; P < .001; absolute difference, 5.3%; 95% CI, 2.6%-8.1%; P < .001, number-needed-to-screen, 19). The 3-month rate of AF detection (a secondary outcome, based on only a single 2-week cECG) was significantly higher in the screening group (4.6% vs 0.2%; relative risk, 19.5; 95% CI, 2.6-144.3; P = .004; absolute difference, 4.4%; 95% CI, 2.3% to 6.4%; P < .001; number-needed-to-screen, 23).

Anticoagulant Therapy

Oral anticoagulant therapy for any indication increased from 0 at baseline in both groups to 18 of 434 (4.1%) in the screening group vs 4 of 422 (0.9%) in the control group at 6 months (relative risk, 4.4; 95% CI, 1.5-12.8; P = .007; absolute difference, 3.2%; 95% CI, 1.1%-5.3%; P = .003). Atrial fibrillation was the only indication for OAC in the screening group. In the control group, reasons for OAC were AF (2 patients), venous thromboembolism (1 patient), and lower limb angioplasty/stenting (1 patient). The 6-month rate of OAC use for AF was 18 of 434 (4.1%) in the screening group vs 2 of 422 (0.5%) in the control group (relative risk, 8.8; 95% CI, 2.0-37.5; P = .004; absolute difference, 3.7%; 95% CI, 1.7%-5.7%; P < .001).

In the screening group, OAC was prescribed by 6 months for 15 of 20 (75.0%) patients who had cECG-detected AF and for all 3 patients who had AF diagnosed clinically. There were no major bleeding events within 6 months among patients with AF or those prescribed OAC.

Details of AF Detected by cECG Monitors

Of the 20 patients with cECG-detected AF duration of more than 5 minutes, 19 had AF and 1 had atrial flutter. Atrial fibrillation was paroxysmal in 18 of 20 patients (90.0%) and continuous throughout the recording in 2 of 20 (10.0%). Atrial fibrillation was asymptomatic in 17 of 20 patients (85.0%); only 1 of 20 patients (5.0%) presented to the hospital with symptomatic AF during the 6-month follow-up.

The median time in AF per patient was 6.3 hours (IQR, 4.2-14.0 hours; range, 1.3 hours-28 days). Atrial fibrillation episodes lasted more than 1 hour in 95% of the participants, more than 4 hours in 70%, more than 6 hours in 50%, more than 9 hours in 30%, more than 12 hours in 25%, and more than 24 hours in 15%. The median duration of the longest AF episode was 5.7 hours (IQR, 2.9-12.9 hours) (Figure 2 and Table 2).

Table 2. Details of the AF Cases Detected by Continuous Electrocardiographic Patch Monitoring in the Screening Group.

Characteristic	Median (IQR) [range]
Total time in AF per patient	6.3 h (4.2-14.0 h) [1.3 h-28 d]
AF per patient
Maximum burden per 2-wk patch, %	1.9 (1.3-17.1) [0.4-17.1]
No. of episodes	3 (2-13) [1-110]
Duration of longest episode	5.7 h (2.9-12.9 h) [50 min-14 d]
Time to first detected episode, d	10.2 (2.8-15.2) [0-24.3]

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Abbreviations: AF, atrial fibrillation; IQR, interquartile range.

The time course of AF detection is shown in Figure 3. Of the 20 AF cases, 8 (40%) were detected within the first week of cECG monitoring, 15 (75%) were detected within 2 weeks, 17 (85%) were detected within 3 weeks, and 3 (15%) were first detected only during the fourth week; 18 AF cases (90%) were first detected after the first 24 hours of monitoring. Among patients who wore 2 cECG monitors (baseline and 3 months), if the first cECG was negative for AF, the probability of the second cECG finding AF was 5 of 329 (1.5%). Detection of other arrhythmias was rare (eTable 2 in Supplement 2).

cECG Tolerability

Adverse skin reactions requiring premature discontinuation of cECG monitoring occurred in 5 of 434 participants (1.2%). On a 5-point scale, most participants agreed or strongly agreed that the cECG monitor was comfortable (daytime: 289 of 356 [81.2%]; sleeping: 285 of 357 [79.8%]); 33 of 355 participants (9.3%) reported that the monitor hindered daily activities and 134 of 354 (37.9%) reported pruritus.

Clinical Outcomes

During the 6-month study period, 1 participant died (control group; cardiovascular death) and 2 participants had an ischemic stroke (both in the screening group) (eMethods in Supplement 2). One patient had a transient ischemic attack (screening group); this patient’s cECG was negative for AF, but AF was subsequently diagnosed in the hospital at the time of presentation with transient ischemic attack. There were no cases of intracranial hemorrhage or systemic embolism. There were no significant differences between the screening and control groups in total physician visits (1233 vs 1251; P = .83), emergency department visits (5 vs 2; P > .99), hospitalizations (5 vs 3; P = .48), or pacemaker implantations (3 vs 2; P > .99).

AF Screening by Home BP Monitors

In the screening group, 412 of 434 participants (94.9%) used the BP monitor for a median of 27.4 days (IQR, 14-28 days), with a median of 55 measurements (IQR, 28-56 measurements) recorded per patient. Among 399 patients with concurrent BP monitor and cECG recordings, the BP monitor had a sensitivity of 35.0% (95% CI, 15.4%-59.2%), specificity of 81.0% (95% CI, 76.7%-84.8%), positive predictive value of 8.9% (95% CI, 4.9%-15.5%), and negative predictive value of 95.9% (95% CI, 94.5%-97.0%) (eTable 3 in Supplement 2). Sensitivity increased to 66.7% for detecting AF episodes lasting more than 24 hours. Specificity increased to 93.4% when BP monitoring was positive for AF at both the morning and evening measurement times in a given day (additional details in the eMethods in Supplement 2).

The BP monitors had at least 1 positive screen for AF in 79 of 434 patients (18.2%), of which 72 (91.1%) were false-positives. When BP monitoring was positive for AF on both the morning and evening measurements in a single day (28 of 434 patients [6.5%]), 3 of 28 (10.7%) were true-positives and 25 (89.3%) were false-positives. In total, BP monitoring yielded 497 false-positive screens, of which 39.2% were associated with frequent atrial or ventricular premature complexes (>60/h) on cECG monitoring. The median AF duration among patients with a true-positive AF screen by BP monitoring was 15.8 hours; the median AF duration among episodes missed by BP monitoring was 4.9 hours.

Discussion

SCREEN-AF investigated 2 technologies for home-based AF screening in older primary care patients with hypertension. A wearable cECG strategy for up to 4 weeks (1) detected a substantial prevalence (5%) of subclinical AF, (2) was superior to 6 months of standard clinical care for AF detection (number-needed-to-screen, 21), and (3) resulted in more patients prescribed OAC for stroke prevention. Most AF cases were paroxysmal, with episodes lasting many hours. Patient adherence to cECG was high, three-quarters of AF cases were detected within the first 2 weeks of ECG monitoring, and 90% of cases would have been missed using a 24-hour Holter monitor.

Our trial strengthens the evidence supporting the effectiveness of screening for early detection of AF. Most previous AF screening studies have been single-group observational studies. Only 1 other completed randomized clinical trial (mSTOPS) investigated screening interventions beyond pulse palpation or random 30-second ECGs in asymptomatic individuals³⁰; our results are consistent with that trial, which found a 3.9% AF detection rate within 4 months among patients randomized to two 2-week cECG patch monitors vs 0.9% in controls (mean age, 74 years; median CHA₂DS₂-VASc score, 3).²⁹ Our AF detection rate with 2- or 4-week noninvasive cECG monitoring was similar to the yield of implanted cardiac loop recorders after 2 weeks (3.1%) and 1 month (6.2%)^31,32 and it was lower, as expected, than in patients with a recent stroke undergoing a similar duration of ECG monitoring.^12,13 Our results in an older population complement the Apple Heart Study³³ and Huawei Heart Study,³⁴ which both focused on younger patients, lending support for further testing of wearables for screening of older individuals who are at risk for AF.

Our findings highlight several advantages of ambulatory cECG monitoring over other types of AF screening interventions. First, cECG monitoring yields higher AF detection rates than either single time point screening (eg, pulse palpation, BP monitoring, or handheld ECG device) or brief intermittent screening.^{35,36,37,38,39} Single random screening primarily detects nonparoxysmal AF, whereas cECG monitoring detects both paroxysmal and nonparoxysmal AF. Thus, it is not surprising that 2 recent trials found that single time point AF screening was not superior to usual care in primary care clinics in the Netherlands.^40,41 Second, unlike handheld ECGs, watches, and BP monitors in which false-positive AF detection is an issue, wearable cECG devices serve as both the screening tool and the diagnostic test, essentially eliminating the need for confirmatory testing. Third, compared with implanted cardiac monitors, wearable ECG devices are noninvasive, less costly, more accessible, can be self-applied by patients at home, and have fewer false-positive results.⁴² Although 2- or 4-week cECG monitoring will miss infrequent paroxysmal AF compared with long-term implanted devices,⁴³ AF detected within only 2 weeks by a wearable monitor is of higher burden and likely more clinically significant than the same amount of AF that is detectable only after longer monitoring durations (months to years) with implanted devices.

Twice-daily AF screening by a home BP monitor had a high false-positive rate and missed most AF episodes lasting less than 24 hours. The low sensitivity and specificity of BP monitoring in this study, as compared with previous reports,^27,44,45 may reflect patient adherence to the BP monitor, a different standard compared with other studies,^38,39,40 the patient population, and our detection of relatively brief episodes of paroxysmal AF rather than persistent AF.

Strengths of our study include the randomized multicenter trial design and broad eligibility criteria to maximize generalizability. We selected a population at risk for both AF and stroke based on older age and hypertension. Our findings should not be generalized to younger individuals who will have a lower prevalence of AF. In our patients, with a median CHA₂DS₂-VASc score of 4, the finding of many hours of AF is potentially clinically important. The minimum clinically significant amount of subclinical device-detected AF is currently debated.⁴⁶ An AF burden of greater than 11% during 2-week cECG monitoring has been associated with a 3-fold increase in stroke risk without OAC.⁴⁷ In patients with a pacemaker or cardioverter-defibrillator, AF durations associated with significantly increased stroke risk range from greater than 6 minutes⁴⁸ to greater than 1 hour,⁴⁹ greater than 5.5 hours,^50,51,52 and greater than 24 hours.^53,54 A subset of patients with brief AF progress to longer AF episodes over time.^55,56,57,58

This work has implications for primary stroke prevention, as the prevalence of AF and AF-associated strokes is increasing with an aging population. The primary goal of screening is to identify patients with a sufficiently high burden of AF (eg, >24 continuous hours) for whom OAC is likely to provide net benefit.⁵⁹ For subclinical AF of less than 24 hours, clinical equipoise for OAC exists.⁶⁰ Trials underway should help define the role of OAC for brief subclinical AF.^61,62 Until such results are available, use of OAC is empirical and treatment decisions must be individualized taking into account the CHA₂DS₂-VASc score and likelihood of recurrent AF (eg, left atrial enlargement). If the efficacy of OAC for patients with low-burden, device-detected AF is similar to that of clinically detected AF, then future AF screening programs could have major public health benefits for improving stroke prevention at a population level.⁶³

Limitations

The main limitation of our trial is that it was underpowered to detect differences in clinical outcomes. Follow-up duration was short and we cannot exclude a lead-time bias effect. Extended follow-up is ongoing to explore these questions. Larger trials and pooled analyses will be necessary to determine the effect of AF screening on stroke prevention, and several such trials are underway.^{64,65,66,67,68} Screening for AF, like screening for other conditions, has potential harms.⁶⁹ The main concerns are overdiagnosis and overtreatment of low-risk patients for whom OAC may be unwarranted (eg, AF lasting seconds only), increasing bleeding risk without benefit. Screening may also cause patient anxiety, increase health care use, or affect health insurance eligibility.⁷⁰ We found no signal of increased bleeding, although our follow-up duration was short, and we have not assessed cost-effectiveness. Preliminary estimates suggest wearable cECG strategies are potentially cost-effective,^71,72 but further work is needed. Given the rapid proliferation of wearable technologies, we are entering an uncharted new era of consumer-driven screening and direct-to-consumer marketing, and consumers must be informed of the potential benefits and risks.^73,74,75 We caution against premature or inappropriate uptake of screening until its effect on hard clinical outcomes and cost-effectiveness have been established.

Conclusions

This randomized clinical trial provides evidence that a wearable continuous ECG strategy is well tolerated and effective for early detection of AF in older primary care patients, often leading to OAC treatment with the potential to avert future strokes. Intermittent oscillometric screening with a BP monitor is an inferior strategy for detecting paroxysmal AF. Future studies need to determine the effect of AF screening on clinical outcomes.

Supplement 1.

Trial Protocol and Statistical Analysis Plan

Click here for additional data file.^{(1.1MB, pdf)}

Supplement 2.

eAppendix. Acknowledgments

eMethods. Methods – Additional Details

eResults. Results – Additional Details

eTable 1. Eligibility Criteria

eTable 2. Incidence of Other Prespecified Device-Detected Arrhythmias in the Screening Group (n=434)

eTable 3. Performance of Home BP Monitor for AF Detection

Click here for additional data file.^{(238.7KB, pdf)}

Supplement 3.

Data Sharing Statement

Click here for additional data file.^{(21KB, pdf)}

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement 1.

Trial Protocol and Statistical Analysis Plan

Click here for additional data file.^{(1.1MB, pdf)}

Supplement 2.

eAppendix. Acknowledgments

eMethods. Methods – Additional Details

eResults. Results – Additional Details

eTable 1. Eligibility Criteria

eTable 2. Incidence of Other Prespecified Device-Detected Arrhythmias in the Screening Group (n=434)

eTable 3. Performance of Home BP Monitor for AF Detection

Click here for additional data file.^{(238.7KB, pdf)}

Supplement 3.

Data Sharing Statement

Click here for additional data file.^{(21KB, pdf)}

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PERMALINK

Screening for Atrial Fibrillation in the Older Population

David J Gladstone, MD, PhD

Rolf Wachter, MD

Katharina Schmalstieg-Bahr, MD

F Russell Quinn, MD, PhD

Eva Hummers, MD, PhD

Noah Ivers, MD

Tamara Marsden, MSc

Andrea Thornton, BSc

Angie Djuric

Johanna Suerbaum, MD

Doris von Grünhagen

William F McIntyre, MD

Alexander P Benz, MD

Jorge A Wong, MD, MPH

Fatima Merali, MSc, MD

Sam Henein, MD

Chris Nichol, MD

Stuart J Connolly, MD

Jeff S Healey, MD, MSc

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Interventions

Main Outcomes and Measures

Results

Conclusions and Relevance

Trial Registration

Introduction

Methods

Trial Design, Setting, and Oversight

Participants

Randomization

Study Interventions

Assessments

Outcomes

Statistical Analysis

Results

Patient Characteristics

Figure 1. Flow Diagram.

Table 1. Patient Characteristics.

Adherence to cECG Monitoring

AF Detection

Anticoagulant Therapy

Details of AF Detected by cECG Monitors

Figure 2. Duration of Longest Episode of Atrial Fibrillation (AF) Detected by Continuous Electrocardiographic Monitoring.

Table 2. Details of the AF Cases Detected by Continuous Electrocardiographic Patch Monitoring in the Screening Group.

Figure 3. Time Course of Atrial Fibrillation (AF) Detection by Continuous Electrocardiographic (cECG) Monitoring in the Screening Group.

cECG Tolerability

Clinical Outcomes

AF Screening by Home BP Monitors

Discussion

Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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