Protocol for a Systematic Review and Individual Participant Data Meta-Analysis of Randomized Trials of Screening for Atrial Fibrillation to Prevent Stroke

Abstract Introduction  Atrial fibrillation (AF) is a common cause of stroke. Timely diagnosis of AF and treatment with oral anticoagulation (OAC) can prevent up to two-thirds of AF-related strokes. Ambulatory electrocardiographic (ECG) monitoring can identify undiagnosed AF in at-risk individuals, but the impact of population-based ECG screening on stroke is uncertain, as ongoing and published randomized controlled trials (RCTs) have generally been underpowered for stroke. Methods and analysis  The AF-SCREEN Collaboration, with support from AFFECT-EU, have begun a systematic review and individual participant data meta-analysis of RCTs evaluating ECG screening for AF. The primary outcome is stroke. Secondary outcomes include AF detection, OAC prescription, hospitalization, mortality, and bleeding. After developing a common data dictionary, anonymized data will be collated from individual trials into a central database. We will assess risk of bias using the Cochrane Collaboration tool, and overall quality of evidence with the Grading of Recommendations Assessment, Development and Evaluation approach. We will pool data using random effects models. Prespecified subgroup and multilevel meta-regression analyses will explore heterogeneity. We will perform prespecified trial sequential meta-analyses of published trials to determine when the optimal information size has been reached, and account for unpublished trials using the SAMURAI approach. Impact and Dissemination  Individual participant data meta-analysis will generate adequate power to assess the risks and benefits of AF screening. Meta-regression will permit exploration of the specific patient, screening methodology, and health system factors that influence outcomes. Trial registration number  PROSPERO CRD42022310308.

[1]  D. McManus,et al.  ReducinG stroke by screening for UndiAgnosed atRial fibrillation in elderly inDividuals (GUARD-AF): Rationale and Design of the GUARD-AF Randomized Trial of Screening for Atrial Fibrillation with a 14-day Patch-Based Continuous ECG Monitor. , 2022, American heart journal.

[2]  D. McManus,et al.  Screening for Atrial Fibrillation in Older Adults at Primary Care Visits: VITAL-AF Randomized Controlled Trial , 2022, Circulation.

[3]  Chyke A Doubeni,et al.  Screening for Atrial Fibrillation: US Preventive Services Task Force Recommendation Statement. , 2022, JAMA.

[4]  D. Conen,et al.  Long-Term Follow-up of Enhanced Holter-Electrocardiography Monitoring in Acute Ischemic Stroke , 2021, Journal of Stroke.

[5]  M. Rosenqvist,et al.  Clinical outcomes in systematic screening for atrial fibrillation (STROKESTOP): a multicentre, parallel group, unmasked, randomised controlled trial , 2021, The Lancet.

[6]  A. Brandes,et al.  Implantable loop recorder detection of atrial fibrillation to prevent stroke (The LOOP Study): a randomised controlled trial , 2021, The Lancet.

[7]  Eric E. Smith,et al.  Effect of Implantable vs Prolonged External Electrocardiographic Monitoring on Atrial Fibrillation Detection in Patients With Ischemic Stroke: The PER DIEM Randomized Clinical Trial. , 2021, JAMA.

[8]  P. Kirchhof,et al.  Systematic monitoring for detection of atrial fibrillation in patients with acute ischaemic stroke (MonDAFIS): a randomised, open-label, multicentre study , 2021, The Lancet Neurology.

[9]  J. Healey,et al.  Screening for Atrial Fibrillation in the Older Population: A Randomized Clinical Trial. , 2021, JAMA cardiology.

[10]  J. Knottnerus,et al.  Opportunistic screening versus usual care for detection of atrial fibrillation in primary care: cluster randomised controlled trial , 2020, BMJ.

[11]  K. Vernooy,et al.  Implementation of an on-demand app-based heart rate and rhythm monitoring infrastructure for the management of atrial fibrillation through teleconsultation: TeleCheck-AF , 2020, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.

[12]  Jeroen J. Bax,et al.  2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association of Cardio-Thoracic Surgery (EACTS). , 2020, European heart journal.

[13]  F. Pomero,et al.  Definition of major bleeding: Prognostic classification , 2020, Journal of thrombosis and haemostasis : JTH.

[14]  Steven A. Lubitz,et al.  Population-Based Screening for Atrial Fibrillation. , 2020, Circulation research.

[15]  A. Brandes,et al.  A Comprehensive Evaluation of Rhythm Monitoring Strategies in Screening for Atrial Fibrillation: Insights from Patients at Risk Long-Term Monitored with Implantable Loop Recorder. , 2020, Circulation.

[16]  J. Gordon,et al.  Cost-effectiveness of targeted screening for the identification of patients with atrial fibrillation: evaluation of a machine learning risk prediction algorithm , 2019, Journal of medical economics.

[17]  Marco V Perez,et al.  Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation. , 2019, The New England journal of medicine.

[18]  J. Healey,et al.  Prevalence of undiagnosed atrial fibrillation in elderly individuals and potential cost-effectiveness of non-invasive ambulatory electrocardiographic screening: The ASSERT-III study. , 2019, Journal of electrocardiology.

[19]  A. Brandes,et al.  Incidence and predictors of atrial fibrillation episodes as detected by implantable loop recorder in patients at risk: From the LOOP study. , 2019, American heart journal.

[20]  M. Rosenqvist,et al.  Stepwise mass screening for atrial fibrillation using N-terminal B-type natriuretic peptide: the STROKESTOP II study , 2019, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.

[21]  Natalie S Blencowe,et al.  RoB 2: a revised tool for assessing risk of bias in randomised trials , 2019, BMJ.

[22]  S. Steinhubl,et al.  Effect of a Home-Based Wearable Continuous ECG Monitoring Patch on Detection of Undiagnosed Atrial Fibrillation: The mSToPS Randomized Clinical Trial , 2018, JAMA.

[23]  M. Chung,et al.  Atrial Fibrillation Burden: Moving Beyond Atrial Fibrillation as a Binary Entity A Scientific Statement From the American Heart Association , 2018, Circulation.

[24]  C. Gerloff,et al.  Expert opinion paper on atrial fibrillation detection after ischemic stroke , 2018, Clinical Research in Cardiology.

[25]  Dana P. Goldman,et al.  Estimated prevalence of undiagnosed atrial fibrillation in the United States , 2018, PloS one.

[26]  Michael B. Gravenor,et al.  Assessment of Remote Heart Rhythm Sampling Using the AliveCor Heart Monitor to Screen for Atrial Fibrillation: The REHEARSE-AF Study , 2017, Circulation.

[27]  J. Healey,et al.  Subclinical Atrial Fibrillation in Older Patients , 2017, Circulation.

[28]  Bernard J. Gersh,et al.  Incidence of Previously Undiagnosed Atrial Fibrillation Using Insertable Cardiac Monitors in a High-Risk Population: The REVEAL AF Study , 2017, JAMA cardiology.

[29]  P. Kirchhof,et al.  Screening for Atrial Fibrillation: A Report of the AF-SCREEN International Collaboration , 2017, Circulation.

[30]  J. Jakobsen,et al.  Trial Sequential Analysis in systematic reviews with meta-analysis , 2017, BMC Medical Research Methodology.

[31]  P. Wolf,et al.  Stroke as the Initial Manifestation of Atrial Fibrillation: The Framingham Heart Study , 2017, Stroke.

[32]  J. Healey,et al.  High prevalence of modifiable stroke risk factors identified in a pharmacy-based screening programme , 2016, Open Heart.

[33]  S. Yusuf,et al.  Global and regional effects of potentially modifiable risk factors associated with acute stroke in 32 countries (INTERSTROKE): a case-control study , 2016, The Lancet.

[34]  Peter A Noseworthy,et al.  Typical, atypical, and asymptomatic presentations of new-onset atrial fibrillation in the community: Characteristics and prognostic implications. , 2016, Heart rhythm.

[35]  J. Hallas,et al.  The Danish Cardiovascular Screening Trial (DANCAVAS): study protocol for a randomized controlled trial , 2015, Trials.

[36]  Jason Shafrin,et al.  Economic Burden of Undiagnosed Nonvalvular Atrial Fibrillation in the United States. , 2015, The American journal of cardiology.

[37]  Richard D Riley,et al.  Preferred Reporting Items for a Systematic Review and Meta-analysis of Individual Participant Data: The PRISMA-IPD Statement , 2015 .

[38]  David J Gladstone,et al.  Atrial fibrillation in patients with cryptogenic stroke. , 2014, The New England journal of medicine.

[39]  D. Rinkes,et al.  Validation and clinical use of a novel diagnostic device for screening of atrial fibrillation , 2014, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.

[40]  S. Bangdiwala,et al.  SAMURAI: Sensitivity analysis of a meta-analysis with unpublished but registered analytical investigations (software) , 2014, Systematic Reviews.

[41]  Ewout W. Steyerberg,et al.  Individual participant data meta-analyses should not ignore clustering , 2013, Journal of clinical epidemiology.

[42]  A. Capucci,et al.  Subclinical atrial fibrillation and the risk of stroke. , 2012, The New England journal of medicine.

[43]  J. Seward,et al.  173 Silent atrial fibrillation in olmsted county: A community-based study , 2011 .

[44]  G. Guyatt,et al.  GRADE guidelines: a new series of articles in the Journal of Clinical Epidemiology. , 2011, Journal of clinical epidemiology.

[45]  M. Aguilar,et al.  Meta-analysis: Antithrombotic Therapy to Prevent Stroke in Patients Who Have Nonvalvular Atrial Fibrillation , 2007, Annals of Internal Medicine.

[46]  Simon G Thompson,et al.  Can meta-analysis help target interventions at individuals most likely to benefit? , 2005, The Lancet.

[47]  M. Symons,et al.  Hazard rate ratio and prospective epidemiological studies. , 2002, Journal of clinical epidemiology.

[48]  S. Yusuf,et al.  Cumulating evidence from randomized trials: utilizing sequential monitoring boundaries for cumulative meta-analysis. , 1997, Controlled clinical trials.

[49]  M. Parmar,et al.  Meta-analysis of the literature or of individual patient data: is there a difference? , 1993, The Lancet.

[50]  N. Laird,et al.  Meta-analysis in clinical trials. , 1986, Controlled clinical trials.

[51]  A. Brandes,et al.  Comprehensive Evaluation of Rhythm Monitoring Strategies in Screening for Atrial Fibrillation , 2020 .