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Van Gelder IC, Rienstra M, Bunting KV, Casado-Arroyo R, Caso V, Crijns HJGM, De Potter TJR, Dwight J, Guasti L, Hanke T, Jaarsma T, Lettino M, Løchen ML, Lumbers RT, Maesen B, Mølgaard I, Rosano GMC, Sanders P, Schnabel RB, Suwalski P, Svennberg E, Tamargo J, Tica O, Traykov V, Tzeis S, Kotecha D. 2024 ESC Guidelines for the management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS). Eur Heart J 2024; 45:3314-3414. [PMID: 39210723 DOI: 10.1093/eurheartj/ehae176] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/04/2024] Open
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Parks AL, Frankel DS, Kim DH, Ko D, Kramer DB, Lydston M, Fang MC, Shah SJ. Management of atrial fibrillation in older adults. BMJ 2024; 386:e076246. [PMID: 39288952 DOI: 10.1136/bmj-2023-076246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/19/2024]
Abstract
Most people with atrial fibrillation are older adults, in whom atrial fibrillation co-occurs with other chronic conditions, polypharmacy, and geriatric syndromes such as frailty. Yet most randomized controlled trials and expert guidelines use an age agnostic approach. Given the heterogeneity of aging, these data may not be universally applicable across the spectrum of older adults. This review synthesizes the available evidence and applies rigorous principles of aging science. After contextualizing the burden of comorbidities and geriatric syndromes in people with atrial fibrillation, it applies an aging focused approach to the pillars of atrial fibrillation management, describing screening for atrial fibrillation, lifestyle interventions, symptoms and complications, rate and rhythm control, coexisting heart failure, anticoagulation therapy, and left atrial appendage occlusion devices. Throughout, a framework is suggested that prioritizes patients' goals and applies existing evidence to all older adults, whether atrial fibrillation is their sole condition, one among many, or a bystander at the end of life.
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Affiliation(s)
- Anna L Parks
- University of Utah, Division of Hematology and Hematologic Malignancies, Salt Lake City, UT, USA
| | - David S Frankel
- Cardiovascular Division, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Dae H Kim
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Harvard Medical School, Boston, MA, USA
| | - Darae Ko
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Harvard Medical School, Boston, MA, USA
- Richard A and Susan F Smith Center for Outcomes Research, Beth Israel Deaconess Medical Center; Boston Medical Center, Section of Cardiovascular Medicine, Boston, MA, USA
| | - Daniel B Kramer
- Richard A and Susan F Smith Center for Outcomes Research, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Melis Lydston
- Massachusetts General Hospital, Treadwell Virtual Library, Boston, MA, USA
| | - Margaret C Fang
- University of California, San Francisco, Division of Hospital Medicine, San Francisco, CA, USA
| | - Sachin J Shah
- Massachusetts General Hospital, Division of General Internal Medicine, Center for Aging and Serious Illness, and Harvard Medical School, Boston, MA, USA
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Shah SJ, Iyer JM, Agha L, Chang Y, Ashburner JM, Atlas SJ, McManus DD, Ellinor PT, Lubitz SA, Singer DE. Identifying a Heterogeneous Effect of Atrial Fibrillation Screening in Older Adults: A Secondary Analysis of the VITAL-AF Trial. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.17.24307559. [PMID: 38883753 PMCID: PMC11178018 DOI: 10.1101/2024.05.17.24307559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2024]
Abstract
Background One-time atrial fibrillation (AF) screening trials have produced mixed results; however, it is unclear if there is a subset for whom screening is effective. Identifying such a subgroup would support targeted screening. Methods We conducted a secondary analysis of VITAL-AF, a randomized trial of one-time, single-lead ECG screening during primary care visits. We tested two approaches to identify a subgroup where screening is effective. First, we developed an effect-based model using a T-learner. Specifically, we separately predicted the likelihood of AF diagnosis under screening and usual care conditions; the difference in probabilities was the predicted screening effect. Second, we used a validated AF risk model to test for a heterogeneous screening effect. We used interaction testing to determine if observed AF diagnosis rates in the screening and usual care groups differed when stratified by decile of the predicted screening effect and predicted AF risk. Results Baseline characteristics were similar between the screening (n=15187) and usual care (n=15078) groups (mean age 74 years, 59% female). In the effect-based analysis, in the highest decile of predicted screening effectiveness (n=3026), AF diagnosis rates were higher in the screening group (6.50 vs. 3.06 per 100 person-years, rate difference 3.45, 95%CI 1.62 to 5.28). In this group, the mean age was 84 years and 68% were female. The risk-based analysis did not identify a subgroup where screening was more effective. Predicted screening effectiveness and predicted baseline AF risk were poorly correlated (Spearman coefficient 0.13). Conclusions In a secondary analysis of the VITAL-AF trial, we identified a small subgroup where one-time screening was associated with increased AF diagnoses using an effect-based approach. In this study, predicted AF risk was a poor proxy for predicted screening effectiveness. These data caution against the assumption that high AF risk is necessarily correlated with high screening effectiveness.
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Kany S, Rämö JT, Friedman SF, Weng LC, Roselli C, Kim MS, Fahed AC, Lubitz SA, Maddah M, Ellinor PT, Khurshid S. Integrating Clinical, Genetic, and Electrocardiogram-Based Artificial Intelligence to Estimate Risk of Incident Atrial Fibrillation. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.13.24311944. [PMID: 39185529 PMCID: PMC11343245 DOI: 10.1101/2024.08.13.24311944] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/27/2024]
Abstract
Background AF risk estimation is feasible using clinical factors, inherited predisposition, and artificial intelligence (AI)-enabled electrocardiogram (ECG) analysis. Objective To test whether integrating these distinct risk signals improves AF risk estimation. Methods In the UK Biobank prospective cohort study, we estimated AF risk using three models derived from external populations: the well-validated Cohorts for Aging in Heart and Aging Research in Genomic Epidemiology AF (CHARGE-AF) clinical score, a 1,113,667-variant AF polygenic risk score (PRS), and a published AI-enabled ECG-based AF risk model (ECG-AI). We estimated discrimination of 5-year incident AF using time-dependent area under the receiver operating characteristic (AUROC) and average precision (AP). Results Among 49,293 individuals (mean age 65±8 years, 52% women), 825 (2.4%) developed AF within 5 years. Using single models, discrimination of 5-year incident AF was higher using ECG-AI (AUROC 0.705 [95%CI 0.686-0.724]; AP 0.085 [0.071-0.11]) and CHARGE-AF (AUROC 0.785 [0.769-0.801]; AP 0.053 [0.048-0.061]) versus the PRS (AUROC 0.618, [0.598-0.639]; AP 0.038 [0.028-0.045]). The inclusion of all components ("Predict-AF3") was the best performing model (AUROC 0.817 [0.802-0.832]; AP 0.11 [0.091-0.15], p<0.01 vs CHARGE-AF+ECG-AI), followed by the two component model of CHARGE-AF+ECG-AI (AUROC 0.802 [0.786-0.818]; AP 0.098 [0.081-0.13]). Using Predict-AF3, individuals at high AF risk (i.e., 5-year predicted AF risk >2.5%) had a 5-year cumulative incidence of AF of 5.83% (5.33-6.32). At the same threshold, the 5-year cumulative incidence of AF was progressively higher according to the number of models predicting high risk (zero: 0.67% [0.51-0.84], one: 1.48% [1.28-1.69], two: 4.48% [3.99-4.98]; three: 11.06% [9.48-12.61]), and Predict-AF3 achieved favorable net reclassification improvement compared to both CHARGE-AF+ECG-AI (0.039 [0.015-0.066]) and CHARGE-AF+PRS (0.033 [0.0082-0.059]). Conclusions Integration of clinical, genetic, and AI-derived risk signals improves discrimination of 5-year AF risk over individual components. Models such as Predict-AF3 have substantial potential to improve prioritization of individuals for AF screening and preventive interventions.
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Affiliation(s)
- Shinwan Kany
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Department of Cardiology, University Heart and Vascular Center Hamburg-Eppendorf, Hamburg, Germany
| | - Joel T. Rämö
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Samuel F. Friedman
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Lu-Chen Weng
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Carolina Roselli
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Min Seo Kim
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Akl C. Fahed
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Steven A. Lubitz
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Mahnaz Maddah
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Patrick T. Ellinor
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Shaan Khurshid
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, Massachusetts, USA
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Petzl AM, Jabbour G, Cadrin-Tourigny J, Pürerfellner H, Macle L, Khairy P, Avram R, Tadros R. Innovative approaches to atrial fibrillation prediction: should polygenic scores and machine learning be implemented in clinical practice? Europace 2024; 26:euae201. [PMID: 39073570 PMCID: PMC11332604 DOI: 10.1093/europace/euae201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Accepted: 07/22/2024] [Indexed: 07/30/2024] Open
Abstract
Atrial fibrillation (AF) prediction and screening are of important clinical interest because of the potential to prevent serious adverse events. Devices capable of detecting short episodes of arrhythmia are now widely available. Although it has recently been suggested that some high-risk patients with AF detected on implantable devices may benefit from anticoagulation, long-term management remains challenging in lower-risk patients and in those with AF detected on monitors or wearable devices as the development of clinically meaningful arrhythmia burden in this group remains unknown. Identification and prediction of clinically relevant AF is therefore of unprecedented importance to the cardiologic community. Family history and underlying genetic markers are important risk factors for AF. Recent studies suggest a good predictive ability of polygenic risk scores, with a possible additive value to clinical AF prediction scores. Artificial intelligence, enabled by the exponentially increasing computing power and digital data sets, has gained traction in the past decade and is of increasing interest in AF prediction using a single or multiple lead sinus rhythm electrocardiogram. Integrating these novel approaches could help predict AF substrate severity, thereby potentially improving the effectiveness of AF screening and personalizing the management of patients presenting with conditions such as embolic stroke of undetermined source or subclinical AF. This review presents current evidence surrounding deep learning and polygenic risk scores in the prediction of incident AF and provides a futuristic outlook on possible ways of implementing these modalities into clinical practice, while considering current limitations and required areas of improvement.
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Affiliation(s)
- Adrian M Petzl
- Electrophysiology Service, Department of Medicine, Montreal Heart Institute, Université de Montréal, 5000 rue Bélanger, Montreal, QC H1T 1C8, Canada
- Cardiovascular Genetics Center, Montreal Heart Institute, Université de Montréal, 5000 rue Bélanger, Montreal, QC H1T 1C8, Canada
| | - Gilbert Jabbour
- Electrophysiology Service, Department of Medicine, Montreal Heart Institute, Université de Montréal, 5000 rue Bélanger, Montreal, QC H1T 1C8, Canada
- Heartwise (heartwise.ai), Montreal Heart Institute, Montreal, Canada
| | - Julia Cadrin-Tourigny
- Electrophysiology Service, Department of Medicine, Montreal Heart Institute, Université de Montréal, 5000 rue Bélanger, Montreal, QC H1T 1C8, Canada
- Cardiovascular Genetics Center, Montreal Heart Institute, Université de Montréal, 5000 rue Bélanger, Montreal, QC H1T 1C8, Canada
| | - Helmut Pürerfellner
- Department of Internal Medicine 2/Cardiology, Ordensklinikum Linz Elisabethinen, Linz, Austria
| | - Laurent Macle
- Electrophysiology Service, Department of Medicine, Montreal Heart Institute, Université de Montréal, 5000 rue Bélanger, Montreal, QC H1T 1C8, Canada
| | - Paul Khairy
- Electrophysiology Service, Department of Medicine, Montreal Heart Institute, Université de Montréal, 5000 rue Bélanger, Montreal, QC H1T 1C8, Canada
| | - Robert Avram
- Heartwise (heartwise.ai), Montreal Heart Institute, Montreal, Canada
- Department of Medicine, Montreal Heart Institute, Université de Montréal, Montreal, Canada
| | - Rafik Tadros
- Electrophysiology Service, Department of Medicine, Montreal Heart Institute, Université de Montréal, 5000 rue Bélanger, Montreal, QC H1T 1C8, Canada
- Cardiovascular Genetics Center, Montreal Heart Institute, Université de Montréal, 5000 rue Bélanger, Montreal, QC H1T 1C8, Canada
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Brik T, Harskamp RE, Himmelreich JCL. Screening and detection of atrial fibrillation in primary care: current practice and future perspectives. Eur Heart J Suppl 2024; 26:iv12-iv18. [PMID: 39099572 PMCID: PMC11292407 DOI: 10.1093/eurheartjsupp/suae074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/06/2024]
Abstract
Atrial fibrillation (AF) is a common arrhythmia associated with an increased risk of stroke, which can be effectively reduced by prophylaxis initiation and integrated care to reduce cardiovascular risk and AF-related complications. Screening for AF has the potential to improve long-term clinical outcomes through timely AF detection in asymptomatic patients. With the central role of primary care in most European healthcare systems in terms of disease detection, treatment, as well as record keeping, primary care is ideally situated as a setting for AF screening efforts. In this review, we provide an overview of evidence relating to AF screening in primary care. We discuss current practices of AF detection and screening, evidence from AF screening trials conducted in primary care settings, stakeholder views on barriers and facilitators for AF screening in primary care, and important aspects that will likely shape routine primary care AF detection as well as AF screening efforts. Finally, we present a potential outline for a primary care-centred AF screening trial coupled to integrated AF care that could further improve the benefit of AF screening.
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Affiliation(s)
- Tessa Brik
- Department of General Practice, Amsterdam UMC location University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Public Health, Personalized Medicine, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Ralf E Harskamp
- Department of General Practice, Amsterdam UMC location University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Public Health, Personalized Medicine, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Jelle C L Himmelreich
- Department of General Practice, Amsterdam UMC location University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Public Health, Personalized Medicine, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
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Ma C, Wu S, Liu S, Han Y. Chinese guidelines for the diagnosis and management of atrial fibrillation. Pacing Clin Electrophysiol 2024; 47:714-770. [PMID: 38687179 DOI: 10.1111/pace.14920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 11/30/2023] [Indexed: 05/02/2024]
Abstract
Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, significantly impacting patients' quality of life and increasing the risk of death, stroke, heart failure, and dementia. Over the past two decades, there have been significant breakthroughs in AF risk prediction and screening, stroke prevention, rhythm control, catheter ablation, and integrated management. During this period, the scale, quality, and experience of AF management in China have greatly improved, providing a solid foundation for the development of the guidelines for the diagnosis and management of AF. To further promote standardized AF management, and apply new technologies and concepts to clinical practice timely and fully, the Chinese Society of Cardiology of Chinese Medical Association and the Heart Rhythm Committee of Chinese Society of Biomedical Engineering jointly developed the Chinese Guidelines for the Diagnosis and Management of Atrial Fibrillation. The guidelines comprehensively elaborated on various aspects of AF management and proposed the CHA2DS2‑VASc‑60 stroke risk score based on the characteristics of the Asian AF population. The guidelines also reevaluated the clinical application of AF screening, emphasized the significance of early rhythm control, and highlighted the central role of catheter ablation in rhythm control.
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Affiliation(s)
- Changsheng Ma
- Chinese Society of Cardiology, Chinese Medical Association, Heart Rhythm Committee of Chinese Society of Biomedical Engineering, Beijing, China
| | - Shulin Wu
- Chinese Society of Cardiology, Chinese Medical Association, Heart Rhythm Committee of Chinese Society of Biomedical Engineering, Beijing, China
| | - Shaowen Liu
- Chinese Society of Cardiology, Chinese Medical Association, Heart Rhythm Committee of Chinese Society of Biomedical Engineering, Beijing, China
| | - Yaling Han
- Chinese Society of Cardiology, Chinese Medical Association, Heart Rhythm Committee of Chinese Society of Biomedical Engineering, Beijing, China
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Mant J, Modi RN, Dymond A, Armstrong N, Burt J, Calvert P, Cowie M, Ding WY, Edwards D, Freedman B, Griffin SJ, Hoare S, Hobbs FDR, Johnson R, Kaptoge S, Lip GYH, Lobban T, Lown M, Lund J, McManus RJ, Mills MT, Morris S, Powell A, Proietti R, Sutton S, Sweeting M, Thom H, Williams K. Randomised controlled trial of population screening for atrial fibrillation in people aged 70 years and over to reduce stroke: protocol for the SAFER trial. BMJ Open 2024; 14:e082047. [PMID: 38670614 PMCID: PMC11057258 DOI: 10.1136/bmjopen-2023-082047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 03/01/2024] [Indexed: 04/28/2024] Open
Abstract
INTRODUCTION There is a lack of evidence that the benefits of screening for atrial fibrillation (AF) outweigh the harms. Following the completion of the Screening for Atrial Fibrillation with ECG to Reduce stroke (SAFER) pilot trial, the aim of the main SAFER trial is to establish whether population screening for AF reduces incidence of stroke risk. METHODS AND ANALYSIS Approximately 82 000 people aged 70 years and over and not on oral anticoagulation are being recruited from general practices in England. Patients on the palliative care register or residents in a nursing home are excluded. Eligible people are identified using electronic patient records from general practices and sent an invitation and consent form to participate by post. Consenting participants are randomised at a ratio of 2:1 (control:intervention) with clustering by household. Those randomised to the intervention arm are sent an information leaflet inviting them to participate in screening, which involves use of a handheld single-lead ECG four times a day for 3 weeks. ECG traces identified by an algorithm as possible AF are reviewed by cardiologists. Participants with AF are seen by a general practitioner for consideration of anticoagulation. The primary outcome is stroke. Major secondary outcomes are: death, major bleeding and cardiovascular events. Follow-up will be via electronic health records for an average of 4 years. The primary analysis will be by intention-to-treat using time-to-event modelling. Results from this trial will be combined with follow-up data from the cluster-randomised pilot trial by fixed-effects meta-analysis. ETHICS AND DISSEMINATION The London-Central National Health Service Research Ethics Committee (19/LO/1597) provided ethical approval. Dissemination will include public-friendly summaries, reports and engagement with the UK National Screening Committee. TRIAL REGISTRATION NUMBER ISRCTN72104369.
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Affiliation(s)
- Jonathan Mant
- Primary Care Unit, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
| | - Rakesh N Modi
- Primary Care Unit, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
| | - Andrew Dymond
- Primary Care Unit, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
| | - Natalie Armstrong
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | | | - Peter Calvert
- Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, UK
| | - Martin Cowie
- School of Cardiovascular and Metabolic Medicine & Sciences, King's College London, London, UK
| | - Wern Yew Ding
- Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, UK
| | - Duncan Edwards
- Primary Care Unit, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
| | - Ben Freedman
- Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Simon J Griffin
- Institute of Public Health, University of Cambridge Primary Care Unit, Cambridge, UK
- MRC Epidemiology Unit, Cambridge, UK
| | - Sarah Hoare
- Department of Public Health and Primary Care, University of Cambridge Primary Care Unit, Cambridge, UK
| | - F D Richard Hobbs
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | | | | | - Gregory Y H Lip
- Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, UK
- Danish Centre for Health Services Research, Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| | - Trudie Lobban
- Arrhythmia Alliance and AF Association, Stratford upon Avon, UK
| | - Mark Lown
- School of Primary Care, Population Sciences and Medical Education, University of Southampton, Southampton, UK
| | - Jenny Lund
- Primary Care Unit, Department of Public Health & Primary Care, Strangeways Research Laboratory, Cambridge, UK
| | - Richard J McManus
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Mark T Mills
- Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, UK
| | - Stephen Morris
- Department of Public Health and Primary Care, University of Cambridge Primary Care Unit, Cambridge, UK
| | - Alison Powell
- THIS Institute, University of Cambridge, Cambridge, UK
| | - Riccardo Proietti
- Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, UK
| | - Stephen Sutton
- Department of Public Health and Primary Care, University of Cambridge Primary Care Unit, Cambridge, UK
| | | | | | - Kate Williams
- Primary Care Unit, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
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Rosas Diaz AN, Troy AL, Kaplinskiy V, Pritchard A, Vani R, Ko D, Orkaby AR. Assessment and Management of Atrial Fibrillation in Older Adults with Frailty. Geriatrics (Basel) 2024; 9:50. [PMID: 38667517 PMCID: PMC11050611 DOI: 10.3390/geriatrics9020050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Revised: 03/28/2024] [Accepted: 04/06/2024] [Indexed: 04/28/2024] Open
Abstract
Atrial fibrillation (AF) is a major driver of morbidity and mortality among older adults with frailty. Moreover, frailty is highly prevalent in older adults with AF. Understanding and addressing the needs of frail older adults with AF is imperative to guide clinicians caring for older adults. In this review, we summarize current evidence to support the assessment and management of older adults with AF and frailty, incorporating numerous recent landmark trials and studies in the context of the 2023 US AF guideline.
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Affiliation(s)
| | - Aaron L. Troy
- Beth Israel Deaconess Medical Center, Boston, MA 02215, USA (A.L.T.)
| | | | - Abiah Pritchard
- Beth Israel Deaconess Medical Center, Boston, MA 02215, USA (A.L.T.)
| | - Rati Vani
- Beth Israel Deaconess Medical Center, Boston, MA 02215, USA (A.L.T.)
| | - Darae Ko
- Section of Cardiovascular Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA 02118, USA
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Harvard Medical School, 1200 Center Street, Boston, MA 02131, USA
| | - Ariela R. Orkaby
- New England GRECC (Geriatric Research, Education and Clinical Center), VA Boston Healthcare System, Boston, MA 02130, USA
- Division of Aging, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
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10
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MA CS, WU SL, LIU SW, HAN YL. Chinese Guidelines for the Diagnosis and Management of Atrial Fibrillation. J Geriatr Cardiol 2024; 21:251-314. [PMID: 38665287 PMCID: PMC11040055 DOI: 10.26599/1671-5411.2024.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/28/2024] Open
Abstract
Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, significantly impacting patients' quality of life and increasing the risk of death, stroke, heart failure, and dementia. Over the past two decades, there have been significant breakthroughs in AF risk prediction and screening, stroke prevention, rhythm control, catheter ablation, and integrated management. During this period, the scale, quality, and experience of AF management in China have greatly improved, providing a solid foundation for the development of guidelines for the diagnosis and management of AF. To further promote standardized AF management, and apply new technologies and concepts to clinical practice in a timely and comprehensive manner, the Chinese Society of Cardiology of the Chinese Medical Association and the Heart Rhythm Committee of the Chinese Society of Biomedical Engineering have jointly developed the Chinese Guidelines for the Diagnosis and Management of Atrial Fibrillation. The guidelines have comprehensively elaborated on various aspects of AF management and proposed the CHA2DS2-VASc-60 stroke risk score based on the characteristics of AF in the Asian population. The guidelines have also reevaluated the clinical application of AF screening, emphasized the significance of early rhythm control, and highlighted the central role of catheter ablation in rhythm control.
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11
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Turnbull I, Camm CF, Halsey J, Du H, Bennett DA, Chen Y, Yu C, Sun D, Liu X, Li L, Chen Z, Clarke R. Correlates and consequences of atrial fibrillation in a prospective study of 25 000 participants in the China Kadoorie Biobank. EUROPEAN HEART JOURNAL OPEN 2024; 4:oeae021. [PMID: 38572088 PMCID: PMC10989653 DOI: 10.1093/ehjopen/oeae021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 02/08/2024] [Accepted: 02/15/2024] [Indexed: 04/05/2024]
Abstract
Aims The prevalence of atrial fibrillation (AF) is positively correlated with prior cardiovascular diseases (CVD) and CVD risk factors but is lower in Chinese than Europeans despite their higher burden of CVD. We examined the prevalence and prognosis of AF and other electrocardiogram (ECG) abnormalities in the China Kadoorie Biobank. Methods and results A random sample of 25 239 adults (mean age 59.5 years, 62% women) had a 12-lead ECG recorded and interpreted using a Mortara VERITAS™ algorithm in 2013-14. Participants were followed up for 5 years for incident stroke, ischaemic heart disease, heart failure (HF), and all CVD, overall and by CHA2DS2-VASc scores, age, sex, and area. Overall, 1.2% had AF, 13.6% had left ventricular hypertrophy (LVH), and 28.1% had ischaemia (two-thirds of AF cases also had ischaemia or LVH). The prevalence of AF increased with age, prior CVD, and levels of CHA₂DS₂-VASc scores (0.5%, 1.3%, 2.1%, 2.9%, and 4.4% for scores <2, 2, 3, 4, and ≥5, respectively). Atrial fibrillation was associated with two-fold higher hazard ratios (HR) for CVD (2.15; 95% CI, 1.71-2.69) and stroke (1.88; 1.44-2.47) and a four-fold higher HR for HF (3.79; 2.21-6.49). The 5-year cumulative incidence of CVD was comparable for AF, prior CVD, and CHA₂DS₂-VASc scores ≥ 2 (36.7% vs. 36.2% vs. 37.7%, respectively) but was two-fold greater than for ischaemia (19.4%), LVH (18.0%), or normal ECG (14.1%), respectively. Conclusion The findings highlight the importance of screening for AF together with estimation of CHA₂DS₂-VASc scores for prevention of CVD in Chinese adults.
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Affiliation(s)
- Iain Turnbull
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
| | - Christian Fielder Camm
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
| | - Jim Halsey
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
| | - Huaidong Du
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
| | - Derrick A Bennett
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
| | - Yiping Chen
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, Peking University, Beijing, China
- Department of Epidemiology and Biostatistics, Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Dianyianji Sun
- Department of Epidemiology and Biostatistics, Peking University, Beijing, China
- Department of Epidemiology and Biostatistics, Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Xiaohong Liu
- Medical Records Archive, Pengzhou Traditional Medicine Hospital, Penzhou, China
| | - Liming Li
- Department of Epidemiology and Biostatistics, Peking University, Beijing, China
- Department of Epidemiology and Biostatistics, Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases, Peking University, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
| | - Robert Clarke
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
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Mant J, Modi RN, Charlton P, Dymond A, Massou E, Brimicombe J, Freedman B, Griffin SJ, Hobbs FDR, Lip GYH, McManus RJ, Williams K. The feasibility of population screening for paroxysmal atrial fibrillation using hand-held electrocardiogram devices. Europace 2024; 26:euae056. [PMID: 38411621 PMCID: PMC10946414 DOI: 10.1093/europace/euae056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 02/22/2024] [Indexed: 02/28/2024] Open
Abstract
AIMS There are few data on the feasibility of population screening for paroxysmal atrial fibrillation (AF) using hand-held electrocardiogram (ECG) devices outside a specialist setting or in people over the age of 75. We investigated the feasibility of screening when conducted without face-to-face contact ('remote') or via in-person appointments in primary care and explored impact of age on screening outcomes. METHODS AND RESULTS People aged ≥65 years from 13 general practices in England participated in screening during 2019-20. This involved attending a practice nurse appointment (10 practices) or receiving an ECG device by post (three practices). Participants were asked to use a hand-held ECG for 1-4 weeks. Screening outcomes included uptake, quality of ECGs, AF detection rates, and uptake of anticoagulation if AF was detected. Screening was carried out by 2141 (87.5%) of people invited to practice nurse-led screening and by 288 (90.0%) invited to remote screening. At least 56 interpretable ECGs were provided by 98.0% of participants who participated for 3 weeks, with no significant differences by setting or age, except people aged 85 or over (91.1%). Overall, 2.6% (64/2429) screened participants had AF, with detection rising with age (9.2% in people aged 85 or over). A total of 53/64 (82.8%) people with AF commenced anticoagulation. Uptake of anticoagulation did not vary by age. CONCLUSION Population screening for paroxysmal AF is feasible in general practice and without face-to-face contact for all ages over 64 years, including people aged 85 and over.
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Affiliation(s)
- Jonathan Mant
- Primary Care Unit, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, 2 Worts’ Causeway, Cambridge CB1 8RN, UK
| | - Rakesh N Modi
- Primary Care Unit, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, 2 Worts’ Causeway, Cambridge CB1 8RN, UK
| | - Peter Charlton
- Primary Care Unit, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, 2 Worts’ Causeway, Cambridge CB1 8RN, UK
| | - Andrew Dymond
- Primary Care Unit, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, 2 Worts’ Causeway, Cambridge CB1 8RN, UK
| | - Efthalia Massou
- Primary Care Unit, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, 2 Worts’ Causeway, Cambridge CB1 8RN, UK
| | - James Brimicombe
- Primary Care Unit, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, 2 Worts’ Causeway, Cambridge CB1 8RN, UK
| | - Ben Freedman
- Heart Research Institute, University of Sydney, Room 3114, Level 3 East, D17 - Charles Perkins Centre, Sydney, NSW 2006, Australia
| | - Simon J Griffin
- Primary Care Unit, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, 2 Worts’ Causeway, Cambridge CB1 8RN, UK
- MRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0SL, UK
| | - F D Richard Hobbs
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK
| | - Gregory Y H Lip
- Liverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital, Liverpool, UK
- Danish Center for Health Services Research, Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| | - Richard J McManus
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK
| | - Kate Williams
- Primary Care Unit, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, 2 Worts’ Causeway, Cambridge CB1 8RN, UK
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13
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Ashburner JM, Chang Y, Borowsky LH, Khurshid S, McManus DD, Ellinor PT, Lubitz SA, Singer DE, Atlas SJ. Effect of clinic-based single-lead electrocardiogram rhythm assessment on oral anticoagulation prescriptions in patients with previously diagnosed atrial fibrillation. Heart Rhythm O2 2023; 4:469-477. [PMID: 37645259 PMCID: PMC10461197 DOI: 10.1016/j.hroo.2023.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/31/2023] Open
Abstract
Background Despite benefits of oral anticoagulation (OAC), many individuals with diagnosed atrial fibrillation (AF) do not receive OAC. Objective The purpose of this study was to assess whether cardiac rhythm assessment for AF impacted use of OAC in patients with previously diagnosed AF. Methods VITAL-AF was a cluster randomized controlled trial conducted in 16 primary care practices assessing the efficacy of AF rhythm assessment with single-lead electrocardiogram in routine care. Patients 65 years and older were offered rhythm assessment at visits. In this secondary analysis, we evaluated rhythm assessment uptake and compared initiation and discontinuation of OAC in patients with previously diagnosed AF from intervention and control arms over 1 year. Results The study included 4593 patients with previously diagnosed AF (2250 intervention; 2343 control). In the intervention arm, 2022 (89.9%) completed rhythm assessment (median 2 visits with rhythm assessment) and 40.1% had ≥1 "Possible AF" result. Initiation of OAC was similar in the intervention (17.7%) and control (19.1%) arms but was influenced by the rhythm assessment result: higher with a "Possible AF" (26.1%; adjusted odds ratio [aOR] 1.62; 95% confidence interval [CI] 1.04-2.51), and lower with a "Normal" result (9.9%; aOR 0.45; 95% CI 0.29-0.71) compared to control. OAC discontinuation was similar in the intervention (6.3%) and control (7.2%) arms, with lower discontinuation with a "Possible AF" result (3.8%; aOR 0.51; 95% CI 0.32-0.81). Conclusions Including patients with previously diagnosed AF in a point-of-care rhythm assessment strategy did not increase overall OAC use compared to the control arm. However, the rhythm assessment result influenced both initiation and discontinuation of OAC.
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Affiliation(s)
- Jeffrey M. Ashburner
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Yuchiao Chang
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Leila H. Borowsky
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Shaan Khurshid
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts
- Demoulas Center for Cardiac Arrhythmias, Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts
| | - David D. McManus
- Department of Medicine, University of Massachusetts Medical School, Worcester, Massachusetts
| | - Patrick T. Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts
- Demoulas Center for Cardiac Arrhythmias, Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts
| | - Steven A. Lubitz
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts
- Demoulas Center for Cardiac Arrhythmias, Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts
| | - Daniel E. Singer
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Steven J. Atlas
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
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Nadarajah R, Wu J, Hogg D, Raveendra K, Nakao YM, Nakao K, Arbel R, Haim M, Zahger D, Parry J, Bates C, Cowan C, Gale CP. Prediction of short-term atrial fibrillation risk using primary care electronic health records. Heart 2023; 109:1072-1079. [PMID: 36759177 PMCID: PMC10359547 DOI: 10.1136/heartjnl-2022-322076] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 01/26/2023] [Indexed: 02/11/2023] Open
Abstract
OBJECTIVE Atrial fibrillation (AF) screening by age achieves a low yield and misses younger individuals. We aimed to develop an algorithm in nationwide routinely collected primary care data to predict the risk of incident AF within 6 months (Future Innovations in Novel Detection of Atrial Fibrillation (FIND-AF)). METHODS We used primary care electronic health record data from individuals aged ≥30 years without known AF in the UK Clinical Practice Research Datalink-GOLD dataset between 2 January 1998 and 30 November 2018, randomly divided into training (80%) and testing (20%) datasets. We trained a random forest classifier using age, sex, ethnicity and comorbidities. Prediction performance was evaluated in the testing dataset with internal bootstrap validation with 200 samples, and compared against the CHA2DS2-VASc (Congestive heart failure, Hypertension, Age >75 (2 points), Stroke/transient ischaemic attack/thromboembolism (2 points), Vascular disease, Age 65-74, Sex category) and C2HEST (Coronary artery disease/Chronic obstructive pulmonary disease (1 point each), Hypertension, Elderly (age ≥75, 2 points), Systolic heart failure, Thyroid disease (hyperthyroidism)) scores. Cox proportional hazard models with competing risk of death were fit for incident longer-term AF between higher and lower FIND-AF-predicted risk. RESULTS Of 2 081 139 individuals in the cohort, 7386 developed AF within 6 months. FIND-AF could be applied to all records. In the testing dataset (n=416 228), discrimination performance was strongest for FIND-AF (area under the receiver operating characteristic curve 0.824, 95% CI 0.814 to 0.834) compared with CHA2DS2-VASc (0.784, 0.773 to 0.794) and C2HEST (0.757, 0.744 to 0.770), and robust by sex and ethnic group. The higher predicted risk cohort, compared with lower predicted risk, had a 20-fold higher 6-month incidence rate for AF and higher long-term hazard for AF (HR 8.75, 95% CI 8.44 to 9.06). CONCLUSIONS FIND-AF, a machine learning algorithm applicable at scale in routinely collected primary care data, identifies people at higher risk of short-term AF.
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Affiliation(s)
- Ramesh Nadarajah
- Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Jianhua Wu
- Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
- Department of Dentistry, University of Leeds, Leeds, UK
| | - David Hogg
- School of Computing, University of Leeds, Leeds, UK
| | | | - Yoko M Nakao
- Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Kazuhiro Nakao
- Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Ronen Arbel
- Maximizing Health Outcomes Research Lab, Sapir College, Hof Ashkelon, Israel
- Community Medical Services Division, Clalit Health Services, Tel Aviv, Israel
| | - Moti Haim
- Department of Cardiology, Soroka University Medical Center, Beer Sheva, Israel
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
| | - Doron Zahger
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Cardiology, Soroka Medical Center, Beer Sheva, Israel
| | | | | | | | - Chris P Gale
- Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
- Cardiology, Leeds General Infirmary, Leeds, UK
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15
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Protocol for a Systematic Review and Individual Participant Data Meta-Analysis of Randomized Trials of Screening for Atrial Fibrillation to Prevent Stroke. Thromb Haemost 2023; 123:366-376. [PMID: 36863334 PMCID: PMC9981276 DOI: 10.1055/s-0042-1760257] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 10/28/2022] [Indexed: 03/04/2023]
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.
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16
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Tu WJ, Zhao Z, Yin P, Cao L, Zeng J, Chen H, Fan D, Fang Q, Gao P, Gu Y, Tan G, Han J, He L, Hu B, Hua Y, Kang D, Li H, Liu J, Liu Y, Lou M, Luo B, Pan S, Peng B, Ren L, Wang L, Wu J, Xu Y, Xu Y, Yang Y, Zhang M, Zhang S, Zhu L, Zhu Y, Li Z, Chu L, An X, Wang L, Yin M, Li M, Yin L, Yan W, Li C, Tang J, Zhou M, Wang L. Estimated Burden of Stroke in China in 2020. JAMA Netw Open 2023; 6:e231455. [PMID: 36862407 PMCID: PMC9982699 DOI: 10.1001/jamanetworkopen.2023.1455] [Citation(s) in RCA: 210] [Impact Index Per Article: 105.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/03/2023] Open
Abstract
IMPORTANCE Stroke is the leading cause of death in China. However, recent data about the up-to-date stroke burden in China are limited. OBJECTIVE To investigate the urban-rural disparity of stroke burden in the Chinese adult population, including prevalence, incidence, and mortality rate, and disparities between urban and rural populations. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study was based on a nationally representative survey that included 676 394 participants aged 40 years and older. It was conducted from July 2020 to December 2020 in 31 provinces in mainland China. MAIN OUTCOMES AND MEASURES Primary outcome was self-reported stroke verified by trained neurologists during a face-to-face interviews using a standardized protocol. Stroke incidence were assessed by defining first-ever strokes that occurred during 1 year preceding the survey. Strokes causing death that occurred during the 1 year preceding the survey were considered as death cases. RESULTS The study included 676 394 Chinese adults (395 122 [58.4%] females; mean [SD] age, 59.7 [11.0] years). In 2020, the weighted prevalence, incidence, and mortality rates of stroke in China were 2.6% (95% CI, 2.6%-2.6%), 505.2 (95% CI, 488.5-522.0) per 100 000 person-years, and 343.4 (95% CI, 329.6-357.2) per 100 000 person-years, respectively. It was estimated that among the Chinese population aged 40 years and older in 2020, there were 3.4 (95% CI, 3.3-3.6) million incident cases of stroke, 17.8 (95% CI, 17.5-18.0) million prevalent cases of stroke, and 2.3 (95% CI, 2.2-2.4) million deaths from stroke. Ischemic stroke constituted 15.5 (95% CI, 15.2-15.6) million (86.8%) of all incident strokes in 2020, while intracerebral hemorrhage constituted 2.1 (95% CI, 2.1-2.1) million (11.9%) and subarachnoid hemorrhage constituted 0.2 (95% CI, 0.2-0.2) million (1.3%). The prevalence of stroke was higher in urban than in rural areas (2.7% [95% CI, 2.6%-2.7%] vs 2.5% [95% CI, 2.5%-2.6%]; P = .02), but the incidence rate (485.5 [95% CI, 462.8-508.3] vs 520.8 [95% CI, 496.3-545.2] per 100 000 person-years; P < .001) and mortality rate (309.9 [95% CI, 291.7-328.1] vs 369.7 [95% CI, 349.1-390.3] per 100 000 person-years; P < .001) were lower in urban areas than in rural areas. In 2020, the leading risk factor for stroke was hypertension (OR, 3.20 [95% CI, 3.09-3.32]). CONCLUSIONS AND RELEVANCE In a large, nationally representative sample of adults aged 40 years or older, the estimated prevalence, incidence, and mortality rate of stroke in China in 2020 were 2.6%, 505.2 per 100 000 person-years, and 343.4 per 100 000 person-years, respectively, indicating the need for an improved stroke prevention strategy in the general Chinese population.
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Affiliation(s)
- Wen-Jun Tu
- The General Office of Stroke Prevention Project Committee, National Health Commission of the People's Republic of China, Beijing, China
- Department of Radiobiology, Institute of Radiation Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhenping Zhao
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Peng Yin
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Lei Cao
- The General Office of Stroke Prevention Project Committee, National Health Commission of the People's Republic of China, Beijing, China
| | - Jingsheng Zeng
- Department of Neurology, the First Affiliated Hospital of Sun Yat–sen University, Guangzhou, China
| | - Huisheng Chen
- Department of Neurology, The General Hospital of Northern Theater Command of the Chinese People’s Liberation Army, Shenyang, China
| | - Dongsheng Fan
- Department of Neurology, Peking University Third Hospital, Beijing, China
| | - Qi Fang
- Department of Neurology, the First Affiliated Hospital of Soochow University, Suzhou, China
| | - Pei Gao
- Peking University School of Public Health, Beijing, China
| | - Yuxiang Gu
- Department of Neurosurgery, Huashan Hospital Fudan University, Shanghai, China
| | - Guojun Tan
- Department of Neurology, the Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Jianfeng Han
- Department of Neurology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi’an, China
| | - Li He
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, China
| | - Bo Hu
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yang Hua
- Department of Ultrasound Vascular, Xuanwu Hospital Capital Medical University, Beijing, China
| | - Dezhi Kang
- Department of Neurosurgery, the First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Hongyan Li
- Department of Neurology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China
| | - Jianmin Liu
- Department of Neurosurgery, Shanghai Changhai Hospital, Shanghai, China
| | - Yuanli Liu
- School of Health and Health Management Policy, Peking Union Medical College, Beijing, China
| | - Min Lou
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, Hangzhou, China
| | - Benyan Luo
- Department of Neurology, the First Affiliated Hospital of Zhejiang University, Hangzhou, China
| | - Suyue Pan
- Department of Neurology, Nanfang Hospital of Southern Medical University, Guangzhou, China
| | - Bin Peng
- Department of Neurology, Peking Union Medical College Hospital, Beijing, China
| | - Lijie Ren
- Department of Neurology, Shenzhen Second Hospital, Shenzhen, China
| | - Lihua Wang
- Department of Neurology, the Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Jian Wu
- Department of Neurology, Beijing Tsinghua Changgung Memoria Hospital, Beijing, China
| | - Yuming Xu
- Department of Neurology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yun Xu
- Department of Neurology, Drum Tower Hospital Affiliated to Nanjing University School of Medicine, China
| | - Yi Yang
- Department of Neurology, the First Bethune Hospital of Jilin University, Changchun, China
| | - Meng Zhang
- Department of Neurology, Daping Hospital, Army Medical University, Chongqing, China
| | - Shu Zhang
- Department of Cardiology, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Liangfu Zhu
- Department of Cerebrovascular Disease, Henan Provincial People's Hospital, Zhengzhou, China
| | - Yicheng Zhu
- Department of Neurology, Peking Union Medical College Hospital, Beijing, China
| | - Zixiao Li
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Lan Chu
- Department of Neurology, the Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Xiuli An
- Department of Neurology, Harbin Second Hospital, Harbin, China
| | - Lingxiao Wang
- The General Office of Stroke Prevention Project Committee, National Health Commission of the People's Republic of China, Beijing, China
| | - Meng Yin
- The General Office of Stroke Prevention Project Committee, National Health Commission of the People's Republic of China, Beijing, China
| | - Mei Li
- Chronic Noncommunicable Disease Prevention and Control Institute, Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, China
| | - Li Yin
- Department of Chronic Disease, Hunan Provincial Center for Disease Control and Prevention, Changsha, China
| | - Wei Yan
- Chronic Noncommunicable Disease Prevention and Control Institute, Jiangxi Provincial Center for Disease Control and Prevention, Nanchang, China
| | - Chuan Li
- Chronic Noncommunicable Disease Prevention and Control Institute, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Junli Tang
- Chronic Noncommunicable Disease Prevention and Control Institute, Shandong Provincial Center for Disease Control and Prevention, Jinan, China
| | - Maigeng Zhou
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Longde Wang
- The General Office of Stroke Prevention Project Committee, National Health Commission of the People's Republic of China, Beijing, China
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Diederichsen SZ, Xing LY, Frodi DM, Kongebro EK, Haugan KJ, Graff C, Højberg S, Krieger D, Brandes A, Køber L, Svendsen JH. Prevalence and Prognostic Significance of Bradyarrhythmias in Patients Screened for Atrial Fibrillation vs Usual Care: Post Hoc Analysis of the LOOP Randomized Clinical Trial. JAMA Cardiol 2023; 8:326-334. [PMID: 36790817 PMCID: PMC9932940 DOI: 10.1001/jamacardio.2022.5526] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
Importance There is increasing interest in heart rhythm monitoring and technologies to detect subclinical atrial fibrillation (AF), which may lead to incidental diagnosis of bradyarrhythmias. Objective To assess bradyarrhythmia prevalence and prognostic significance in persons screened for AF using implantable loop recorder (ILR) compared with unscreened persons. Design, Setting, and Participants This was a post hoc analysis of the Implantable Loop Recorder Detection of Atrial Fibrillation to Prevent Stroke (LOOP) randomized clinical trial, which took place in 4 sites in Denmark. Participants were 70 years or older without known AF but diagnosed with at least 1 of the following: hypertension, diabetes, heart failure, or prior stroke. Participants were recruited by letter invitation between January 31, 2014, and May 17, 2016. The median (IQR) follow-up period was 65 (59-70) months. Analysis took place between February and June 2022. Interventions ILR screening for AF with treatment of any bradyarrhythmia left to the discretion of the treating physician (ILR group) vs usual care (control group). Main Outcomes and Measures Adjudicated bradyarrhythmia episodes, pacemaker implantation, syncope, and sudden cardiovascular death. Results A total of 6004 participants were randomized (mean [SD] age, 75 [4.1] years; 2837 [47.3%] female; 5444 [90.7%] with hypertension; 1224 [20.4%] with prior syncope), 4503 to control and 1501 to ILR. Bradyarrhythmia was diagnosed in 172 participants (3.8%) in the control group vs 312 participants (20.8%) in the ILR group (hazard ratio [HR], 6.21 [95% CI, 5.15-7.48]; P < .001), and these were asymptomatic in 41 participants (23.8%) vs 249 participants (79.8%), respectively. The most common bradyarrhythmia was sinus node dysfunction followed by high-grade atrioventricular block. Risk factors for bradyarrhythmia included higher age, male sex, and prior syncope. A pacemaker was implanted in 132 participants (2.9%) vs 67 (4.5%) (HR, 1.53 [95% CI, 1.14-2.06]; P < .001), syncope occurred in 120 (2.7%) vs 33 (2.2%) (HR, 0.83 [95% CI, 0.56-1.22]; P = .34), and sudden cardiovascular death occurred in 49 (1.1%) vs 18 (1.2%) (HR, 1.11 [95% CI, 0.64-1.90]; P = .71) in the control and ILR groups, respectively. Bradyarrhythmias were associated with subsequent syncope, cardiovascular death, and all-cause death, with no interaction between bradyarrhythmia and randomization group. Conclusions and Relevance More than 1 in 5 persons older than 70 years with cardiovascular risk factors can be diagnosed with bradyarrhythmias when long-term continous monitoring for AF is applied. In this study, ILR screening led to a 6-fold increase in bradyarrhythmia diagnoses and a significant increase in pacemaker implantations compared with usual care but no change in the risk of syncope or sudden death.
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Affiliation(s)
- Søren Zöga Diederichsen
- Department of Cardiology, Copenhagen University Hospital–Rigshospitalet, Copenhagen, Denmark
| | - Lucas Yixi Xing
- Department of Cardiology, Copenhagen University Hospital–Rigshospitalet, Copenhagen, Denmark
| | - Diana My Frodi
- Department of Cardiology, Copenhagen University Hospital–Rigshospitalet, Copenhagen, Denmark
| | - Emilie Katrine Kongebro
- Department of Cardiology, Copenhagen University Hospital–Rigshospitalet, Copenhagen, Denmark
| | - Ketil Jørgen Haugan
- Department of Cardiology, Zealand University Hospital Roskilde, Roskilde, Denmark
| | - Claus Graff
- Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Søren Højberg
- Department of Cardiology, Copenhagen University Hospital–Bispebjerg, Copenhagen, Denmark
| | - Derk Krieger
- Stroke Unit, Mediclinic City Hospital, Dubai, United Arab Emirates
| | - Axel Brandes
- Department of Cardiology, Odense University Hospital, Odense, Denmark,Department of Clinical Research, Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark,Department of Internal Medicine–Cardiology, University Hospital of Southern Denmark–Esbjerg, Esbjerg, Denmark
| | - Lars Køber
- Department of Cardiology, Copenhagen University Hospital–Rigshospitalet, Copenhagen, Denmark,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jesper Hastrup Svendsen
- Department of Cardiology, Copenhagen University Hospital–Rigshospitalet, Copenhagen, Denmark,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Verbiest-van Gurp N, Uittenbogaart SB, van de Moosdijk SCM, van Sprang UF, Knottnerus JA, Stoffers HEJH, Lucassen WAM. How is atrial fibrillation detected in everyday healthcare? Results of a Dutch cohort study. Neth Heart J 2023; 31:76-82. [PMID: 36048351 PMCID: PMC9892390 DOI: 10.1007/s12471-022-01719-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/18/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Atrial fibrillation (AF) is a common arrhythmia with serious potential consequences when left untreated. For timely treatment, early detection is imperative. We explored how new AF is detected in patients aged ≥ 65 years in Dutch healthcare. METHODS The study cohort consisted of 9526 patients from 49 Dutch general practices in the usual-care arm of the Detecting and Diagnosing Atrial Fibrillation study. We automatically extracted data from the electronic medical records and reviewed individual records of patients who developed AF. Patient selection started in 2015, and data collection ended in 2019. RESULTS We included 258 patients with newly diagnosed AF. In 55.0% of the patients, the irregular heartbeat was first observed in general practice and in 16.3% in the cardiology department. Cardiologists diagnosed most cases (47.3%), followed by general practitioners (GPs; 33.7%). AF detection was triggered by symptoms in 64.7% of the patients and by previous stroke in 3.5%. Overall, patients aged 65-74 years more often presented with symptoms than those aged ≥ 75 years (73.5% vs 60.6%; p = 0.042). In 31.5% of the patients, AF was diagnosed incidentally ('silent AF'). Silent-AF patients were on average 2 years older than symptomatic-AF patients. GPs less often diagnosed silent AF than symptomatic AF (21.0% vs 39.0%; p = 0.008), whereas physicians other than GPs or cardiologists more often diagnosed symptomatic AF than silent AF (34.6% vs 11.9%; p < 0.001). Most diagnoses were based on a 12-lead electrocardiogram (93.8%). CONCLUSION Diagnosing AF is a multidisciplinary process. The irregular heartbeat was most often detected by the GP, but cardiologists diagnosed most cases. One-third of all newly diagnosed AF was silent.
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Affiliation(s)
- N Verbiest-van Gurp
- Department of Family Medicine, Care and Public Health Research Institute, Faculty of Health, Medicine, and Life Sciences, Maastricht University, Maastricht, The Netherlands.
| | - S B Uittenbogaart
- Department of General Practice, Amsterdam Public Health, Amsterdam University Medical Centres, University of Amsterdam, Amsterdam, The Netherlands
| | - S C M van de Moosdijk
- Department of Family Medicine, Care and Public Health Research Institute, Faculty of Health, Medicine, and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - U F van Sprang
- Department of General Practice, Amsterdam Public Health, Amsterdam University Medical Centres, University of Amsterdam, Amsterdam, The Netherlands
| | - J A Knottnerus
- Department of Family Medicine, Care and Public Health Research Institute, Faculty of Health, Medicine, and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - H E J H Stoffers
- Department of Family Medicine, Care and Public Health Research Institute, Faculty of Health, Medicine, and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - W A M Lucassen
- Department of General Practice, Amsterdam Public Health, Amsterdam University Medical Centres, University of Amsterdam, Amsterdam, The Netherlands
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19
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Komkov AA, Mazaev VP, Ryazanova SV, Kobak AA. System for digital character recognition, extraction and structuring of medical data with the formation of a cloud-based electronic health records. КАРДИОВАСКУЛЯРНАЯ ТЕРАПИЯ И ПРОФИЛАКТИКА 2023. [DOI: 10.15829/1728-8800-2022-3482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
The use of available systems for obtaining structured data from primary medical information is based on the use of various technologies, including digital transformation of primary data for the formation of electronic health records. The purpose of the work was to outline the structure and benefits of using the RuPatient electronic health record (EHR), created to automate the work with medical data, digital character recognition and building an algorithm for communicating with patients. The created RuPatient EHR automates the processing of medical documents using image digitization and optical character recognition and the formation of a database. The developed program code that combines modules into a single web service is registered as intellectual property. The web service is a client-server application with the ability to access the interface through a browser from a smartphone, tablet, laptop, and personal computer. The service contains an interface part (Frontend), a functional part, with the possibility of expanding with separate modules (Backend), and databases for storing information about patients. The developed service provides standardization and digitalization of documents of patient-doctor visits and is a tool for convenient remote communication between a patient and a doctor via the built-in chat. The RuPatient EHR serves as a convenient tool for standardizing medical information in digital form and is designed to help the doctor and the patient in organizing treatment and preventive interaction.
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Affiliation(s)
- A. A. Komkov
- National Medical Research Center for Therapy and Preventive Medicine; L.A. Vorokhobov City Clinical Hospital № 67
| | - V. P. Mazaev
- National Medical Research Center for Therapy and Preventive Medicine
| | - S. V. Ryazanova
- National Medical Research Center for Therapy and Preventive Medicine
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20
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Brik T, Lucassen WAM, Harskamp RE, Karregat EPM, Himmelreich JCL, Busschers WB, Moll van Charante EP. Personalized approach using wearable technology for early detection of atrial fibrillation in high-risk primary care patients (PATCH-AF): Study protocol for a cluster randomized controlled trial. Am Heart J 2022; 254:172-182. [PMID: 36099977 DOI: 10.1016/j.ahj.2022.09.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 08/29/2022] [Accepted: 09/05/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Atrial fibrillation (AF) is a common cardiac arrhythmia with a lifetime risk of one in 4. Unfortunately, AF often remains undetected, particularly when it is paroxysmal, for which single time-point evaluation is less effective. Recently, unobtrusive cardiac arrhythmia monitoring devices have become available, providing the opportunity to conduct prolonged electrocardiographic (ECG) monitoring in a patient-friendly manner. We hypothesize that applying these devices in at risk patients may improve AF detection, particularly when used during repeated episodes. We therefore aim to evaluate the diagnostic yield of yearly screening for atrial fibrillation when using a wearable device for continuous ECG monitoring for 7 days in primary care patients ≥ 65 years deemed at high-risk of AF (CHA2DS2VASc score ≥3 for men or ≥4 for women) compared with usual care over a study period of 3 years. METHODS Primary care based, cluster-randomized controlled trial with 10 general practices randomized to the intervention group and 10 general practices randomized to control group. In each group, we aim to enroll 930 patients, ≥65 years and a CHA2DS2VASc score ≥3 for men or ≥ 4 for women. The intervention consists of continuous ECG monitoring for 7 days at start of the study (t = 0), after one (t = 1) and 2 years (t = 2). The control practices will follow usual diagnostic care procedures. RESULTS Results are expected in 2025. CONCLUSIONS This study differs from previous randomized controlled trials, as it involves longitudinal screening of a risk-stratified population. In case of a beneficial diagnostic yield, the PATCH-AF study will add to the evidence for AF screening. TRIAL REGISTRATION The PATCH-AF study is registered at The Netherlands Trial Register (NTR number NL9656).
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Affiliation(s)
- Tessa Brik
- Department of General Practice, Amsterdam UMC, University of Amsterdam, Academic Medical Center, Amsterdam, The Netherlands.
| | - Wim A M Lucassen
- Department of General Practice, Amsterdam UMC, University of Amsterdam, Academic Medical Center, Amsterdam, The Netherlands
| | - Ralf E Harskamp
- Department of General Practice, Amsterdam UMC, University of Amsterdam, Academic Medical Center, Amsterdam, The Netherlands
| | - Evert P M Karregat
- Department of General Practice, Amsterdam UMC, University of Amsterdam, Academic Medical Center, Amsterdam, The Netherlands
| | - Jelle C L Himmelreich
- Department of General Practice, Amsterdam UMC, University of Amsterdam, Academic Medical Center, Amsterdam, The Netherlands
| | - Wim B Busschers
- Department of General Practice, Amsterdam UMC, University of Amsterdam, Academic Medical Center, Amsterdam, The Netherlands
| | - Eric P Moll van Charante
- Department of General Practice, Amsterdam UMC, University of Amsterdam, Academic Medical Center, Amsterdam, The Netherlands
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21
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Whitfield R, Ascenção R, da Silva GL, Almeida AG, Pinto FJ, Caldeira D. Screening strategies for atrial fibrillation in the elderly population: a systematic review and network meta-analysis. Clin Res Cardiol 2022:10.1007/s00392-022-02117-9. [DOI: 10.1007/s00392-022-02117-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 10/11/2022] [Indexed: 11/09/2022]
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22
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Noseworthy PA, Attia ZI, Behnken EM, Giblon RE, Bews KA, Liu S, Gosse TA, Linn ZD, Deng Y, Yin J, Gersh BJ, Graff-Radford J, Rabinstein AA, Siontis KC, Friedman PA, Yao X. Artificial intelligence-guided screening for atrial fibrillation using electrocardiogram during sinus rhythm: a prospective non-randomised interventional trial. Lancet 2022; 400:1206-1212. [PMID: 36179758 DOI: 10.1016/s0140-6736(22)01637-3] [Citation(s) in RCA: 89] [Impact Index Per Article: 29.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 08/15/2022] [Accepted: 08/18/2022] [Indexed: 12/25/2022]
Abstract
BACKGROUND Previous atrial fibrillation screening trials have highlighted the need for more targeted approaches. We did a pragmatic study to evaluate the effectiveness of an artificial intelligence (AI) algorithm-guided targeted screening approach for identifying previously unrecognised atrial fibrillation. METHODS For this non-randomised interventional trial, we prospectively recruited patients with stroke risk factors but with no known atrial fibrillation who had an electrocardiogram (ECG) done in routine practice. Participants wore a continuous ambulatory heart rhythm monitor for up to 30 days, with the data transmitted in near real time through a cellular connection. The AI algorithm was applied to the ECGs to divide patients into high-risk or low-risk groups. The primary outcome was newly diagnosed atrial fibrillation. In a secondary analysis, trial participants were propensity-score matched (1:1) to individuals from the eligible but unenrolled population who served as real-world controls. This study is registered with ClinicalTrials.gov, NCT04208971. FINDINGS 1003 patients with a mean age of 74 years (SD 8·8) from 40 US states completed the study. Over a mean 22·3 days of continuous monitoring, atrial fibrillation was detected in six (1·6%) of 370 patients with low risk and 48 (7·6%) of 633 with high risk (odds ratio 4·98, 95% CI 2·11-11·75, p=0·0002). Compared with usual care, AI-guided screening was associated with increased detection of atrial fibrillation (high-risk group: 3·6% [95% CI 2·3-5·4] with usual care vs 10·6% [8·3-13·2] with AI-guided screening, p<0·0001; low-risk group: 0·9% vs 2·4%, p=0·12) over a median follow-up of 9·9 months (IQR 7·1-11·0). INTERPRETATION An AI-guided targeted screening approach that leverages existing clinical data increased the yield for atrial fibrillation detection and could improve the effectiveness of atrial fibrillation screening. FUNDING Mayo Clinic Robert D and Patricia E Kern Center for the Science of Health Care Delivery.
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Affiliation(s)
- Peter A Noseworthy
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA; Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.
| | - Zachi I Attia
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Emma M Behnken
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA
| | - Rachel E Giblon
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Katherine A Bews
- Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA
| | - Sijia Liu
- Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, USA
| | - Tara A Gosse
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Zachery D Linn
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Yihong Deng
- Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA
| | - Jun Yin
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Bernard J Gersh
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | | | | | | | - Paul A Friedman
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Xiaoxi Yao
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA; Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA
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23
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Boriani G, Svennberg E, Guerra F, Linz D, Casado-Arroyo R, Malaczynska-Rajpold K, Duncker D, Boveda S, Merino JL, Leclercq C. Reimbursement practices for use of digital devices in atrial fibrillation and other arrhythmias: a European Heart Rhythm Association survey. Europace 2022; 24:1834-1843. [PMID: 36040858 DOI: 10.1093/europace/euac142] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 07/22/2022] [Indexed: 12/31/2022] Open
Abstract
AIMS Since digital devices are increasingly used in cardiology for assessing cardiac rhythm and detecting arrhythmias, especially atrial fibrillation (AF), our aim was to evaluate the expectations and opinions of healthcare professionals in Europe on reimbursement policies for the use of digital devices (including wearables) in AF and other arrhythmias. METHODS AND RESULTS An anonymous survey was proposed through announcements on the European Heart Rhythm Association website, social media channels, and mail newsletter. Two hundred and seventeen healthcare professionals participated in the survey: 32.7%, reported regular use of digital devices, 45.2% reported that they sometimes use these tools, 18.6% that they do not use but would like to. Only a minority (3.5%) reported a lack of trust in digital devices. The survey highlighted a general propensity to provide medical consultation for suspected AF or other arrhythmias detected by a consumer-initiated use of digital devices, even if time constraints and reimbursement availability emerged as important elements. More than 85% of respondents agreed that reimbursement should be applied for clinical use of digital devices, also in different settings such as post-stroke, post-cardioversion, post-ablation, and in patients with palpitations or syncope. Finally, 73.6% of respondents confirmed a lack of reimbursement fees in their country for physicians' consultations (tracings interpretation) related to digital devices. CONCLUSIONS Digital devices, including wearables, are increasingly and widely used for assessing cardiac rhythm and detecting AF, but a definition of reimbursement policies for physicians' consultations is needed.
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Affiliation(s)
- Giuseppe Boriani
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, Via del Pozzo, 71, 41124 Modena, Italy.,EHRA mHEALTH and Health Economics Section, European Heart Rhythm Association, Biot 06903, France
| | - Emma Svennberg
- Karolinska Institutet, Department of Medicine, Karolinska University Hospital Huddinge, 141 57 Huddinge, Stockholm, Sweden
| | - Federico Guerra
- Cardiology and Arrhythmology Clinic, University Hospital 'Lancisi-Umberto I- Salesi', 60126 Ancona, Italy.,Department of Biomedical Sciences and Public Health, Marche Polytechnic University, 60126 Ancona, Italy
| | - Dominik Linz
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, 6229 ER Maastricht, The Netherlands
| | - Ruben Casado-Arroyo
- Department of Cardiology, Erasme Hospital, Université Libre de Bruxelles, 1070 Bruxelles, Belgium
| | | | - David Duncker
- Hannover Heart Rhythm Center, Department of Cardiology and Angiology, Hannover Medical School, 30625 Hannover, Germany
| | - Serge Boveda
- Cardiology-Heart Rhythm Management Department, Clinique Pasteur, 31076 Toulouse, France.,Vrije Universiteit Brussel (VUB), 1050 Brussels, Belgium
| | - Josè Luis Merino
- Arrhythmia & Robotic EP Unit, University Hospital La Paz, Autonoma University, IdiPaz, 28029 Madrid, Spain
| | - Christophe Leclercq
- Department of Cardiology, University Hospital of Rennes, 35033 Rennes cedex 9, France
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Tang EWL, Yip BHK, Yu CP, Wong SYS, Lee EKP. Sensitivity and specificity of automated blood pressure devices to detect atrial fibrillation: A systematic review and meta-analysis of diagnostic accuracy. Front Cardiovasc Med 2022; 9:956542. [PMID: 36035905 PMCID: PMC9411860 DOI: 10.3389/fcvm.2022.956542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 07/25/2022] [Indexed: 12/03/2022] Open
Abstract
Background Atrial fibrillation (AF) is a prevalent and preventable cause of stroke and mortality. Aim This systematic review and meta-analysis aimed to investigate the sensitivity and specificity of office and out-of-office automated blood pressure (BP) devices to detect AF. Methods Diagnostic studies, extracted from databases such as Ovid Medline and Embase, on AF detection by BP device(s), electrocardiography, and reported sensitivity and specificity, were included. Screening of abstracts and full texts, data extraction, and quality assessment were conducted independently by two investigators using Covidence software. The sensitivity and specificity of the BP devices were pooled using a random-effects model. Results Sixteen studies including 10,158 participants were included. Only a few studies were conducted in primary care (n = 3) or with a low risk of bias (n = 5). Office BP devices, which utilised different algorithms to detect AF, had a sensitivity and specificity of 96.2 and 94%, respectively. Specificity was reduced when only one positive result was considered among consecutive BP measurements. Only a few studies (n = 3) investigated out-of-office BP. Only one study (n = 100) suggested the use of ≥79 and ≥26% of positive readings on 24-h ambulatory BP measurements to detect AF and paroxysmal AF, respectively. Conclusions Office BP devices can be used clinically to screen for AF in high-risk populations. Clinical trials are needed to determine the effect of AF screening using office BP devices in reducing stroke risk and mortality. Further studies are also required to guide out-of-office use of BP devices for detecting paroxysmal AF or AF. Systematic review registration https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022319541, PROSPERO CRD42022319541.
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Affiliation(s)
- Edmond W. L. Tang
- Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Benjamin H. K. Yip
- Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Chun-Pong Yu
- Li Ping Medical Library, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Samuel Y. S. Wong
- Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Eric K. P. Lee
- Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
- *Correspondence: Eric K. P. Lee
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Chen W, Khurshid S, Singer DE, Atlas SJ, Ashburner JM, Ellinor PT, McManus DD, Lubitz SA, Chhatwal J. Cost-effectiveness of Screening for Atrial Fibrillation Using Wearable Devices. JAMA HEALTH FORUM 2022; 3:e222419. [PMID: 36003419 PMCID: PMC9356321 DOI: 10.1001/jamahealthforum.2022.2419] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 06/10/2022] [Indexed: 11/18/2022] Open
Abstract
Question Is population-based atrial fibrillation (AF) screening using wearable devices cost-effective? Findings In this economic evaluation of 30 million simulated individuals with an age, sex, and comorbidity profile matching the US population aged 65 years or older, AF screening using wearable devices was cost-effective, with the overall preferred strategy identified as wearable photoplethysmography, followed conditionally by wearable electrocardiography with patch monitor confirmation (incremental cost-effectiveness ratio, $57 894 per quality-adjusted life-year). The cost-effectiveness of screening was consistent across multiple scenarios, including strata of sex, screening at earlier ages, and with variation in the association of anticoagulation with risk of stroke associated with screening-detected AF. Meaning This study suggests that contemporary AF screening using wearable devices may be cost-effective. Importance Undiagnosed atrial fibrillation (AF) is an important cause of stroke. Screening for AF using wrist-worn wearable devices may prevent strokes, but their cost-effectiveness is unknown. Objective To evaluate the cost-effectiveness of contemporary AF screening strategies, particularly wrist-worn wearable devices. Design, Setting, and Participants This economic evaluation used a microsimulation decision-analytic model and was conducted from September 8, 2020, to May 23, 2022, comprising 30 million simulated individuals with an age, sex, and comorbidity profile matching the US population aged 65 years or older. Interventions Eight AF screening strategies, with 6 using wrist-worn wearable devices (watch or band photoplethysmography, with or without watch or band electrocardiography) and 2 using traditional modalities (ie, pulse palpation and 12-lead electrocardiogram) vs no screening. Main Outcomes and Measures The primary outcome was the incremental cost-effectiveness ratio, defined as US dollars per quality-adjusted life-year (QALY). Secondary measures included rates of stroke and major bleeding. Results In the base case analysis of this model, the mean (SD) age was 72.5 (7.5) years, and 50% of the individuals were women. All 6 screening strategies using wrist-worn wearable devices were estimated to be more effective than no screening (range of QALYs gained vs no screening, 226-957 per 100 000 individuals) and were associated with greater relative benefit than screening using traditional modalities (range of QALYs gained vs no screening, −116 to 93 per 100 000 individuals). Compared with no screening, screening using wrist-worn wearable devices was associated with a reduction in stroke incidence by 20 to 23 per 100 000 person-years but an increase in major bleeding by 20 to 44 per 100 000 person-years. The overall preferred strategy was wearable photoplethysmography, followed conditionally by wearable electrocardiography with patch monitor confirmation, which had an incremental cost-effectiveness ratio of $57 894 per QALY, meeting the acceptability threshold of $100 000 per QALY. The cost-effectiveness of screening was consistent across multiple scenarios, including strata of sex, screening at earlier ages (eg, ≥50 years), and with variation in the association of anticoagulation with risk of stroke in the setting of screening-detected AF. Conclusions and Relevance This economic evaluation of AF screening using a microsimulation decision-analytic model suggests that screening using wearable devices is cost-effective compared with either no screening or AF screening using traditional methods.
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Affiliation(s)
- Wanyi Chen
- Institute for Technology Assessment, Massachusetts General Hospital, Boston
- Department of Radiology, Harvard Medical School, Boston, Massachusetts
| | - Shaan Khurshid
- Cardiovascular Research Center, Massachusetts General Hospital, Boston
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston
| | - Daniel E. Singer
- Division of General Internal Medicine, Massachusetts General Hospital, Boston
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Steven J. Atlas
- Division of General Internal Medicine, Massachusetts General Hospital, Boston
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Jeffrey M. Ashburner
- Division of General Internal Medicine, Massachusetts General Hospital, Boston
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Patrick T. Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston
| | - David D. McManus
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester
| | - Steven A. Lubitz
- Cardiovascular Research Center, Massachusetts General Hospital, Boston
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston
| | - Jagpreet Chhatwal
- Institute for Technology Assessment, Massachusetts General Hospital, Boston
- Department of Radiology, Harvard Medical School, Boston, Massachusetts
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Ashburner JM, Chang Y, Wang X, Khurshid S, Anderson CD, Dahal K, Weisenfeld D, Cai T, Liao KP, Wagholikar KB, Murphy SN, Atlas SJ, Lubitz SA, Singer DE. Natural Language Processing to Improve Prediction of Incident Atrial Fibrillation Using Electronic Health Records. J Am Heart Assoc 2022; 11:e026014. [PMID: 35904194 PMCID: PMC9375475 DOI: 10.1161/jaha.122.026014] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Accepted: 06/29/2022] [Indexed: 11/16/2022]
Abstract
Background Models predicting atrial fibrillation (AF) risk, such as Cohorts for Heart and Aging Research in Genomic Epidemiology AF (CHARGE-AF), have not performed as well in electronic health records. Natural language processing (NLP) may improve models by using narrative electronic health record text. Methods and Results From a primary care network, we included patients aged ≥65 years with visits between 2003 and 2013 in development (n=32 960) and internal validation cohorts (n=13 992). An external validation cohort from a separate network from 2015 to 2020 included 39 051 patients. Model features were defined using electronic health record codified data and narrative data with NLP. We developed 2 models to predict 5-year AF incidence using (1) codified+NLP data and (2) codified data only and evaluated model performance. The analysis included 2839 incident AF cases in the development cohort and 1057 and 2226 cases in internal and external validation cohorts, respectively. The C-statistic was greater (P<0.001) in codified+NLP model (0.744 [95% CI, 0.735-0.753]) compared with codified-only (0.730 [95% CI, 0.720-0.739]) in the development cohort. In internal validation, the C-statistic of codified+NLP was modestly higher (0.735 [95% CI, 0.720-0.749]) compared with codified-only (0.729 [95% CI, 0.715-0.744]; P=0.06) and CHARGE-AF (0.717 [95% CI, 0.703-0.731]; P=0.002). Codified+NLP and codified-only were well calibrated, whereas CHARGE-AF underestimated AF risk. In external validation, the C-statistic of codified+NLP (0.750 [95% CI, 0.740-0.760]) remained higher (P<0.001) than codified-only (0.738 [95% CI, 0.727-0.748]) and CHARGE-AF (0.735 [95% CI, 0.725-0.746]). Conclusions Estimation of 5-year risk of AF can be modestly improved using NLP to incorporate narrative electronic health record data.
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Affiliation(s)
- Jeffrey M. Ashburner
- Division of General Internal MedicineMassachusetts General HospitalBostonMA
- Harvard Medical SchoolBostonMA
| | - Yuchiao Chang
- Division of General Internal MedicineMassachusetts General HospitalBostonMA
- Harvard Medical SchoolBostonMA
| | - Xin Wang
- Cardiovascular Research CenterMassachusetts General HospitalBostonMA
| | - Shaan Khurshid
- Cardiovascular Research CenterMassachusetts General HospitalBostonMA
- Division of CardiologyMassachusetts General HospitalBostonMA
| | | | - Kumar Dahal
- Department of Rheumatology, Inflammation, and ImmunityBrigham and Women’s HospitalBostonMA
| | - Dana Weisenfeld
- Department of Rheumatology, Inflammation, and ImmunityBrigham and Women’s HospitalBostonMA
| | - Tianrun Cai
- Harvard Medical SchoolBostonMA
- Department of Rheumatology, Inflammation, and ImmunityBrigham and Women’s HospitalBostonMA
| | - Katherine P. Liao
- Harvard Medical SchoolBostonMA
- Department of Rheumatology, Inflammation, and ImmunityBrigham and Women’s HospitalBostonMA
| | - Kavishwar B. Wagholikar
- Harvard Medical SchoolBostonMA
- Laboratory of Computer ScienceMassachusetts General HospitalBostonMA
| | - Shawn N. Murphy
- Harvard Medical SchoolBostonMA
- Research Information Science and ComputingMass General BrighamSomervilleMA
| | - Steven J. Atlas
- Division of General Internal MedicineMassachusetts General HospitalBostonMA
- Harvard Medical SchoolBostonMA
| | - Steven A. Lubitz
- Cardiovascular Research CenterMassachusetts General HospitalBostonMA
- Cardiac Arrhythmia ServiceMassachusetts General HospitalBostonMA
| | - Daniel E. Singer
- Division of General Internal MedicineMassachusetts General HospitalBostonMA
- Harvard Medical SchoolBostonMA
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27
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Schnabel RB, Marinelli EA, Arbelo E, Boriani G, Boveda S, Buckley CM, Camm AJ, Casadei B, Chua W, Dagres N, de Melis M, Desteghe L, Diederichsen SZ, Duncker D, Eckardt L, Eisert C, Engler D, Fabritz L, Freedman B, Gillet L, Goette A, Guasch E, Svendsen JH, Hatem SN, Haeusler KG, Healey JS, Heidbuchel H, Hindricks G, Hobbs FDR, Hübner T, Kotecha D, Krekler M, Leclercq C, Lewalter T, Lin H, Linz D, Lip GYH, Løchen ML, Lucassen W, Malaczynska-Rajpold K, Massberg S, Merino JL, Meyer R, Mont L, Myers MC, Neubeck L, Niiranen T, Oeff M, Oldgren J, Potpara TS, Psaroudakis G, Pürerfellner H, Ravens U, Rienstra M, Rivard L, Scherr D, Schotten U, Shah D, Sinner MF, Smolnik R, Steinbeck G, Steven D, Svennberg E, Thomas D, True Hills M, van Gelder IC, Vardar B, Palà E, Wakili R, Wegscheider K, Wieloch M, Willems S, Witt H, Ziegler A, Daniel Zink M, Kirchhof P. Early diagnosis and better rhythm management to improve outcomes in patients with atrial fibrillation: the 8th AFNET/EHRA consensus conference. Europace 2022; 25:6-27. [PMID: 35894842 PMCID: PMC9907557 DOI: 10.1093/europace/euac062] [Citation(s) in RCA: 86] [Impact Index Per Article: 28.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 04/11/2022] [Indexed: 11/13/2022] Open
Abstract
Despite marked progress in the management of atrial fibrillation (AF), detecting AF remains difficult and AF-related complications cause unacceptable morbidity and mortality even on optimal current therapy. This document summarizes the key outcomes of the 8th AFNET/EHRA Consensus Conference of the Atrial Fibrillation NETwork (AFNET) and the European Heart Rhythm Association (EHRA). Eighty-three international experts met in Hamburg for 2 days in October 2021. Results of the interdisciplinary, hybrid discussions in breakout groups and the plenary based on recently published and unpublished observations are summarized in this consensus paper to support improved care for patients with AF by guiding prevention, individualized management, and research strategies. The main outcomes are (i) new evidence supports a simple, scalable, and pragmatic population-based AF screening pathway; (ii) rhythm management is evolving from therapy aimed at improving symptoms to an integrated domain in the prevention of AF-related outcomes, especially in patients with recently diagnosed AF; (iii) improved characterization of atrial cardiomyopathy may help to identify patients in need for therapy; (iv) standardized assessment of cognitive function in patients with AF could lead to improvement in patient outcomes; and (v) artificial intelligence (AI) can support all of the above aims, but requires advanced interdisciplinary knowledge and collaboration as well as a better medico-legal framework. Implementation of new evidence-based approaches to AF screening and rhythm management can improve outcomes in patients with AF. Additional benefits are possible with further efforts to identify and target atrial cardiomyopathy and cognitive impairment, which can be facilitated by AI.
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Affiliation(s)
- Renate B Schnabel
- Atrial Fibrillation Network (AFNET), Muenster, Germany,Department of Cardiology, University Heart & Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany,German Centre for Cardiovascular Research (DZHK) partner site Hamburg/Kiel/Lübeck, Hamburg, Germany
| | | | - Elena Arbelo
- Arrhythmia Section, Cardiology Department, Hospital Clinic, Universitat de Barcelona, Barcelona, Spain,IDIBAPS, Institut d'Investigació August Pi i Sunyer, Barcelona, Spain,CIBERCV, Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares, Madrid, Spain
| | - Giuseppe Boriani
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Polyclinic of Modena, Modena, Italy
| | - Serge Boveda
- Cardiology—Heart Rhythm Management Department, Clinique Pasteur, 45 Avenue de Lombez, 31076 Toulouse, France,Universiteit Ziekenhuis, Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | | | - A John Camm
- Cardiology Clinical Academic Group, Molecular and Clinical Sciences Institute, St. George's University of London, London, UK
| | - Barbara Casadei
- RDM, Division of Cardiovascular Medicine, British Heart Foundation Centre of Research Excellence, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Winnie Chua
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
| | - Nikolaos Dagres
- Department of Electrophysiology, Heart Center Leipzig at University of Leipzig, Leipzig, Germany
| | - Mirko de Melis
- Medtronic Bakken Research Center, Maastricht, The Netherlands
| | - Lien Desteghe
- Research Group Cardiovascular Diseases, University of Antwerp, Antwerp, Belgium,Department of Cardiology, Antwerp University Hospital, Antwerp, Belgium,Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium,Heart Centre Hasselt, Jessa Hospital, Hasselt, Belgium
| | - Søren Zöga Diederichsen
- Department of Cardiology, Copenhagen University Hospital—Rigshospitalet, Copenhagen, Denmark
| | - David Duncker
- Hannover Heart Rhythm Center, Department of Cardiology and Angiology, Hannover Medical School, Hannover, Germany
| | - Lars Eckardt
- Atrial Fibrillation Network (AFNET), Muenster, Germany,Division of Electrophysiology, Department of Cardiology and Angiology, Münster, Germany
| | | | - Daniel Engler
- Department of Cardiology, University Heart & Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany,German Centre for Cardiovascular Research (DZHK) partner site Hamburg/Kiel/Lübeck, Hamburg, Germany
| | - Larissa Fabritz
- Atrial Fibrillation Network (AFNET), Muenster, Germany,Department of Cardiology, University Heart & Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany,German Centre for Cardiovascular Research (DZHK) partner site Hamburg/Kiel/Lübeck, Hamburg, Germany,Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK,University Center of Cardiovascular Science Hamburg, Hamburg, Germany
| | - Ben Freedman
- Heart Research Institute, The University of Sydney, Sydney, Australia
| | | | - Andreas Goette
- Atrial Fibrillation Network (AFNET), Muenster, Germany,St Vincenz Hospital, Paderborn, Germany
| | - Eduard Guasch
- Arrhythmia Section, Cardiology Department, Hospital Clinic, Universitat de Barcelona, Barcelona, Spain,IDIBAPS, Institut d'Investigació August Pi i Sunyer, Barcelona, Spain,CIBERCV, Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares, Madrid, Spain
| | - Jesper Hastrup Svendsen
- Department of Cardiology, Copenhagen University Hospital—Rigshospitalet, Copenhagen, Denmark,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Karl Georg Haeusler
- Atrial Fibrillation Network (AFNET), Muenster, Germany,Department of Neurology, Universitätsklinikum Würzburg, Würzburg, Germany
| | - Jeff S Healey
- Population Health Research Institute, McMaster University Hamilton, ON, Canada
| | - Hein Heidbuchel
- Research Group Cardiovascular Diseases, University of Antwerp, Antwerp, Belgium,Department of Cardiology, Antwerp University Hospital, Antwerp, Belgium
| | - Gerhard Hindricks
- Atrial Fibrillation Network (AFNET), Muenster, Germany,Department of Electrophysiology, Heart Center Leipzig at University of Leipzig, Leipzig, Germany
| | | | | | - Dipak Kotecha
- University of Birmingham & University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | | | | | - Thorsten Lewalter
- Atrial Fibrillation Network (AFNET), Muenster, Germany,Hospital Munich South, Department of Cardiology, Munich, Germany,Department of Cardiology, University of Bonn, Bonn, Germany
| | - Honghuang Lin
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA, USA
| | - Dominik Linz
- Department of Cardiology, Maastricht University Medical Center and Cardiovascular Research Institute Maastricht, Maastricht, The Netherlands,Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Gregory Y H Lip
- Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool, UK,Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| | - Maja Lisa Løchen
- Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway
| | - Wim Lucassen
- Amsterdam UMC (location AMC), Department General Practice, Amsterdam, The Netherlands
| | | | - Steffen Massberg
- Department of Cardiology, University Hospital, LMU Munich, Munich, Germany,German Centre for Cardiovascular Research (DZHK), partner site: Munich Heart Alliance, Munich, Germany
| | - Jose L Merino
- Arrhythmia & Robotic EP Unit, La Paz University Hospital, IDIPAZ, Madrid, Spain
| | | | - Lluıs Mont
- Arrhythmia Section, Cardiology Department, Hospital Clinic, Universitat de Barcelona, Barcelona, Spain,IDIBAPS, Institut d'Investigació August Pi i Sunyer, Barcelona, Spain,CIBERCV, Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares, Madrid, Spain
| | | | - Lis Neubeck
- Arrhythmia & Robotic EP Unit, La Paz University Hospital, IDIPAZ, Madrid, Spain
| | - Teemu Niiranen
- Medtronic, Dublin, Ireland,Centre for Cardiovascular Health Edinburgh Napier University, Edinburgh, UK
| | - Michael Oeff
- Atrial Fibrillation Network (AFNET), Muenster, Germany
| | - Jonas Oldgren
- University of Turku and Turku University Hospital, Turku, Finland
| | | | - George Psaroudakis
- Uppsala Clinical Research Center and Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Helmut Pürerfellner
- School of Medicine, Belgrade University, Cardiology Clinic, University Clinical Centre of Serbia, Belgrade, Serbia
| | - Ursula Ravens
- Atrial Fibrillation Network (AFNET), Muenster, Germany,Bayer AG, Leverkusen, Germany
| | - Michiel Rienstra
- Ordensklinikum Linz, Elisabethinen, Cardiological Department, Linz, Austria
| | - Lena Rivard
- Institute of Experimental Cardiovascular Medicine, University Hospital Freiburg, Freiburg, Germany
| | - Daniel Scherr
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Ulrich Schotten
- Atrial Fibrillation Network (AFNET), Muenster, Germany,Montreal Heart Institute, University of Montreal, Montreal, Canada
| | - Dipen Shah
- Division of Cardiology, Medical University of Graz, Graz, Austria
| | - Moritz F Sinner
- Atrial Fibrillation Network (AFNET), Muenster, Germany,Amsterdam UMC (location AMC), Department General Practice, Amsterdam, The Netherlands,Royal Brompton Hospital, London, UK
| | | | - Gerhard Steinbeck
- Atrial Fibrillation Network (AFNET), Muenster, Germany,MUMC+, Maastricht, The Netherlands
| | - Daniel Steven
- Atrial Fibrillation Network (AFNET), Muenster, Germany,University Hospital of Geneva, Cardiac Electrophysiology Unit, Geneva, Switzerland
| | - Emma Svennberg
- Center for Cardiology at Clinic Starnberg, Starnberg, Germany
| | - Dierk Thomas
- Atrial Fibrillation Network (AFNET), Muenster, Germany,University Hospital Cologne, Heart Center, Department of Electrophysiology, Cologne, Germany,Karolinska Institutet, Department of Medicine Huddinge, Karolinska University Hospital, Stockholm, Sweden,Department of Cardiology, Medical University Hospital, Heidelberg, Germany
| | - Mellanie True Hills
- HCR (Heidelberg Center for Heart Rhythm Disorders), Medical University Hospital Heidelberg, Heidelberg, Germany
| | - Isabelle C van Gelder
- DZHK (German Center for Cardiovascular Research), partner site Heidelberg/Mannheim, Heidelberg, Germany
| | - Burcu Vardar
- Uppsala Clinical Research Center and Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Elena Palà
- StopAfib.org, American Foundation for Women’s Health, Decatur, TX, USA
| | - Reza Wakili
- Atrial Fibrillation Network (AFNET), Muenster, Germany,Department of Cardiology, University Medical Center Groningen, University of Groningen, The Netherlands
| | - Karl Wegscheider
- Atrial Fibrillation Network (AFNET), Muenster, Germany,German Centre for Cardiovascular Research (DZHK) partner site Hamburg/Kiel/Lübeck, Hamburg, Germany,Neurovascular Research Laboratory, Vall d’Hebron Institute of Research (VHIR), Autonomous University of Barcelona, Barcelona, Spain
| | - Mattias Wieloch
- Department of Cardiology and Vascular Medicine, Westgerman Heart and Vascular Center, University of Duisburg-Essen, Essen, Germany,Institute of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Germany
| | - Stephan Willems
- Atrial Fibrillation Network (AFNET), Muenster, Germany,German Centre for Cardiovascular Research (DZHK) partner site Hamburg/Kiel/Lübeck, Hamburg, Germany,Department of Coagulation Disorders, Skane University Hospital, Lund University, Malmö, Sweden
| | | | | | - Matthias Daniel Zink
- Asklepios Hospital St Georg, Department of Cardiology and Internal Intensive Care Medicine, Faculty of Medicine, Semmelweis University Campus Hamburg, Hamburg, Germany
| | - Paulus Kirchhof
- Corresponding author. Tel: +49 40 7410 52438; Fax: +49 40 7410 55862. E-mail address:
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28
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Svennberg E, Tjong F, Goette A, Akoum N, Di Biase L, Bordachar P, Boriani G, Burri H, Conte G, Deharo JC, Deneke T, Drossart I, Duncker D, Han JK, Heidbuchel H, Jais P, de Oliveira Figueiredo MJ, Linz D, Lip GYH, Malaczynska-Rajpold K, Márquez MF, Ploem C, Soejima K, Stiles MK, Wierda E, Vernooy K, Leclercq C, Meyer C, Pisani C, Pak HN, Gupta D, Pürerfellner H, Crijns HJGM, Chavez EA, Willems S, Waldmann V, Dekker L, Wan E, Kavoor P, Turagam MK, Sinner M. How to use digital devices to detect and manage arrhythmias: an EHRA practical guide. Europace 2022; 24:979-1005. [PMID: 35368065 PMCID: PMC11636571 DOI: 10.1093/europace/euac038] [Citation(s) in RCA: 129] [Impact Index Per Article: 43.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Affiliation(s)
- Emma Svennberg
- Department of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden
| | - Fleur Tjong
- Heart Center, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Andreas Goette
- St. Vincenz Hospital Paderborn, Paderborn, Germany
- MAESTRIA Consortium/AFNET, Münster, Germany
| | - Nazem Akoum
- Heart Institute, University of Washington School of Medicine, Seattle, WA, USA
| | - Luigi Di Biase
- Albert Einstein College of Medicine at Montefiore Hospital, New York, NY, USA
| | | | - Giuseppe Boriani
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, Modena, Italy
| | - Haran Burri
- Cardiology Department, University Hospital of Geneva, Geneva, Switzerland
| | - Giulio Conte
- Cardiocentro Ticino Institute, Ente Ospedaliero Cantonale, Lugano, Switzerland
| | - Jean Claude Deharo
- Assistance Publique—Hôpitaux de Marseille, Centre Hospitalier Universitaire La Timone, Service de Cardiologie, Marseille, France
- Aix Marseille Université, C2VN, Marseille, France
| | - Thomas Deneke
- Heart Center Bad Neustadt, Bad Neustadt an der Saale, Germany
| | - Inga Drossart
- European Society of Cardiology, Sophia Antipolis, France
- ESC Patient Forum, Sophia Antipolis, France
| | - David Duncker
- Hannover Heart Rhythm Center, Department of Cardiology and Angiology, Hannover Medical School, Hannover, Germany
| | - Janet K Han
- Cardiac Arrhythmia Centers, Veterans Affairs Greater Los Angeles Healthcare System and University of California, Los Angeles, CA, USA
| | - Hein Heidbuchel
- Department of Cardiology, Antwerp University Hospital, Antwerp, Belgium
- Cardiovascular Research Group, Antwerp University, Antwerp, Belgium
| | - Pierre Jais
- Bordeaux University Hospital, Bordeaux, France
| | | | - Dominik Linz
- Department of Cardiology, Maastricht University Medical Centre and Cardiovascular Research Institute Maastricht, Maastricht, the Netherlands
| | - Gregory Y H Lip
- Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool, UK
- Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| | | | - Manlio F Márquez
- Department of Electrocardiology, Instituto Nacional de Cardiología, Mexico City, Mexico
- Cardiology, Electrophysiology Service, American British Cowdray Medical Center, Mexico City, México
| | - Corrette Ploem
- Department of Ethics, Law and Medical Humanities, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Kyoko Soejima
- Kyorin University School of Medicine, Mitaka, Tokyo, Japan
| | - Martin K Stiles
- Waikato Clinical School, University of Auckland, Hamilton, New Zealand
| | - Eric Wierda
- Department of Cardiology, Dijklander Hospital, Hoorn, the Netherlands
| | - Kevin Vernooy
- Department of Cardiology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Center, Maastricht, the Netherlands
| | | | - Christian Meyer
- Division of Cardiology/Angiology/Intensive Care, EVK Düsseldorf, Teaching Hospital University of Düsseldorf, Düsseldorf, Germany
| | - Cristiano Pisani
- Arrhythmia Unit, Heart Institute, InCor, University of São Paulo Medical School, São Paulo, Brazil
| | - Hui Nam Pak
- Yonsei University, Severance Cardiovascular Hospital, Yonsei University Health System, Seoul, Republic of Korea
| | - Dhiraj Gupta
- Faculty of Health and Life Sciences, Liverpool Heart and Chest Hospital, University of Liverpool, Liverpool, UK
| | | | - H J G M Crijns
- Em. Professor of Cardiology, University of Maastricht, Maastricht, Netherlands
| | - Edgar Antezana Chavez
- Division of Cardiology, Hospital General de Agudos Dr. Cosme Argerich, Pi y Margall 750, C1155AHB Buenos Aires, Argentina
- Division of Cardiology, Hospital Belga, Antezana 455, C0000 Cochabamba, Bolivia
| | | | - Victor Waldmann
- Electrophysiology Unit, European Georges Pompidou Hospital, Paris, France
- Adult Congenital Heart Disease Unit, European Georges Pompidou Hospital, Paris, France
| | - Lukas Dekker
- Catharina Ziekenhuis Eindhoven, Eindhoven, Netherlands
| | - Elaine Wan
- Cardiology and Cardiac Electrophysiology, Columbia University, New York, NY, USA
| | - Pramesh Kavoor
- Cardiology Department, Westmead Hospital, Westmead, New South Wales, Australia
| | | | - Moritz Sinner
- Univ. Hospital Munich, Campus Grosshadern, Munich, Germany
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Singer DE, Atlas SJ, Go AS, Lopes RD, Lubitz SA, McManus DD, Revkin JH, Mills D, Crosson LA, Lenane JC, Aronson RS. 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. Am Heart J 2022; 249:76-85. [PMID: 35472303 DOI: 10.1016/j.ahj.2022.04.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 03/28/2022] [Accepted: 04/19/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Screening for atrial fibrillation (AF) is attractive because AF independently raises the risk of ischemic stroke, this risk is largely reversible by long-term oral anticoagulant therapy (OAC), and many patients with AF remain undiagnosed and untreated. Recent trials of one-time brief screening for AF have not produced a significant increase in the proportion of patients diagnosed with AF. Trials of longer-term screening have demonstrated an increase in AF diagnoses, primarily paroxysmal AF. To date, however, no trials have demonstrated that screening for AF results in lower rates of stroke. Clinical practice guidelines conflict in their level of support for screening for AF. METHODS The GUARD-AF individually randomized trial is designed to test whether screening for AF in individuals age 70 years or greater using a 2-week single-lead electrocardiographic patch monitor can identify patients with undiagnosed AF and lead to treatment with OAC, resulting in a reduced rate of stroke in the screened population. The trial's efficacy end point is hospitalization for stroke (either ischemic or hemorrhagic) and the trial's safety end point is hospitalization for a bleeding event. End points will be ascertained via Medicare claims or electronic health records at 2.5 years after study start. Enrollment is based in primary care practices and the OAC decision for screen-detected cases is left to the patient and their physician. The initial planned target sample size was 52,000, with 26,000 allocated to either screening or to usual care. RESULTS Trial enrollment was severely hampered by the novel coronavirus disease 2019 (COVID-19) pandemic and stopped at a total enrollment of 11,931 participants. Of 5,965 randomized to the screening arm, 5,713 patients (96%) returned monitors with analyzable results. Incidence of screen-detected and clinically detected AF and associated stroke and bleeding outcomes will be ascertained. CONCLUSIONS GUARD-AF is the largest AF screening randomized trial using a longer-term patch-based continuous electrocardiographic monitor. The results will contribute important information on the yield of patch-based AF screening, the "burden" of AF detected (percent time in AF, longest episode), and physicians' OAC decisions as a function of AF burden. GUARD-AF's stroke and bleed results will contribute to pooled trial analyses of AF screening, thereby informing future studies and guidelines.
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Affiliation(s)
- Daniel E Singer
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA; Harvard Medical School, Boston, MA.
| | - Steven J Atlas
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA; Harvard Medical School, Boston, MA
| | - Alan S Go
- Division of Research, Kaiser Permanente Northern California, Oakland, CA; Department of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA; Departments of Epidemiology, Biostatistics and Medicine, University of California, San Francisco, San Francisco, CA
| | - Renato D Lopes
- Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC
| | - Steven A Lubitz
- Harvard Medical School, Boston, MA; Cardiac Arrhythmia Service and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
| | - David D McManus
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA
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30
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Verbiest-van Gurp N, Uittenbogaart SB, Lucassen WAM, Erkens PMG, Knottnerus JA, Winkens B, Stoffers HEJH, van Weert HCPM. Detection of atrial fibrillation in primary care with radial pulse palpation, electronic blood pressure measurement and handheld single-lead electrocardiography: a diagnostic accuracy study. BMJ Open 2022; 12:e059172. [PMID: 35768092 PMCID: PMC9244719 DOI: 10.1136/bmjopen-2021-059172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
OBJECTIVE To determine the diagnostic accuracy of three tests-radial pulse palpation, an electronic blood pressure monitor and a handheld single-lead ECG device-for opportunistic screening for unknown atrial fibrillation (AF). DESIGN We performed a diagnostic accuracy study in the intention-to-screen arm of a cluster randomised controlled trial aimed at opportunistic screening for AF in general practice. We performed radial pulse palpation, followed by electronic blood pressure measurement (WatchBP Home A) and handheld ECG (MyDiagnostick) in random order. If one or more index tests were positive, we performed a 12-lead ECG at shortest notice. Similarly, to limit verification bias, a random sample of patients with three negative index tests received this reference test. Additionally, we analysed the dataset using multiple imputation. We present pooled diagnostic parameters. SETTING 47 general practices participated between September 2015 and August 2018. PARTICIPANTS In the electronic medical record system of the participating general practices (n=47), we randomly marked 200 patients of ≥65 years without AF. When they visited the practice for any reason, we invited them to participate. Exclusion criteria were terminal illness, inability to give informed consent or visit the practice or having a pacemaker or an implantable cardioverter-defibrillator. OUTCOMES Diagnostic accuracy of individual tests and test combinations to detect unknown AF. RESULTS We included 4339 patients; 0.8% showed new AF. Sensitivity and specificity were 62.8% (range 43.1%-69.7%) and 91.8% (91.7%-91.8%) for radial pulse palpation, 70.0% (49.0%-80.6%) and 96.5% (96.3%-96.7%) for electronic blood pressure measurement and 90.1% (60.8%-100%) and 97.9% (97.8%-97.9%) for handheld ECG, respectively. Positive predictive values were 5.8% (5.3%-6.1%), 13.8% (12.2%-14.8%) and 25.2% (24.2%-25.8%), respectively. All negative predictive values were ≥99.7%. CONCLUSION In detecting AF, electronic blood pressure measurement (WatchBP Home A), but especially handheld ECG (MyDiagnostick) showed better diagnostic accuracy than radial pulse palpation. TRIAL REGISTRATION NUMBER Netherlands Trial Register No. NL4776 (old NTR4914).
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Affiliation(s)
- Nicole Verbiest-van Gurp
- Department of Family Medicine, School for Public Health and Primary Care (CAPHRI), Maastricht University, Maastricht, The Netherlands
| | - Steven B Uittenbogaart
- Department of General Practice, Amsterdam UMC Locatie Meibergdreef, Amsterdam, The Netherlands
| | - Wim A M Lucassen
- Department of General Practice, Amsterdam UMC Locatie Meibergdreef, Amsterdam, The Netherlands
| | - Petra M G Erkens
- Department of Health Services Research, School for Public Health and Primary Care (CAPHRI), Maastricht University, Maastricht, The Netherlands
| | - J André Knottnerus
- Department of Family Medicine, School for Public Health and Primary Care (CAPHRI), Maastricht University, Maastricht, The Netherlands
| | - Bjorn Winkens
- Department of Methodology and Statistics, School for Public Health and Primary Care (CAPHRI), Maastricht University, Maastricht, The Netherlands
| | - Henri E J H Stoffers
- Department of Family Medicine, School for Public Health and Primary Care (CAPHRI), Maastricht University, Maastricht, The Netherlands
| | - Henk C P M van Weert
- Department of General Practice, Amsterdam UMC Locatie Meibergdreef, Amsterdam, The Netherlands
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Engler D, Hanson CL, Desteghe L, Boriani G, Diederichsen SZ, Freedman B, Palà E, Potpara TS, Witt H, Heidbuchel H, Neubeck L, Schnabel RB. Feasible approaches and implementation challenges to atrial fibrillation screening: a qualitative study of stakeholder views in 11 European countries. BMJ Open 2022; 12:e059156. [PMID: 35728895 PMCID: PMC9214372 DOI: 10.1136/bmjopen-2021-059156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
OBJECTIVES Atrial fibrillation (AF) screening may increase early detection and reduce complications of AF. European, Australian and World Heart Federation guidelines recommend opportunistic screening, despite a current lack of clear evidence supporting a net benefit for systematic screening. Where screening is implemented, the most appropriate approaches are unknown. We explored the views of European stakeholders about opportunities and challenges of implementing four AF screening scenarios. DESIGN Telephone-based semi-structured interviews with results reported using Consolidated criteria for Reporting Qualitative research guidelines. Data were thematically analysed using the framework approach. SETTING AF screening stakeholders in 11 European countries. PARTICIPANTS Healthcare professionals and regulators (n=24) potentially involved in AF screening implementation. INTERVENTION Four AF screening scenarios: single time point opportunistic, opportunistic prolonged, systematic single time point/prolonged and patient-led screening. PRIMARY OUTCOME MEASURES Stakeholder views about the challenges and feasibility of implementing the screening scenarios in the respective national/regional healthcare system. RESULTS Three themes developed. (1) Current screening approaches: there are no national AF screening programmes, with most AF detected in symptomatic patients. Patient-led screening exists via personal devices, creating screening inequity. (2) Feasibility of screening: single time point opportunistic screening in primary care using single-lead ECG devices was considered the most feasible. Software algorithms may aid identification of suitable patients and telehealth services have potential to support diagnosis. (3) Implementation requirements: sufficient evidence of benefit is required. National screening processes are required due to different payment mechanisms and health service regulations. Concerns about data security, and inclusivity for those without primary care access or personal devices must be addressed. CONCLUSIONS There is an overall awareness of AF screening. Opportunistic screening appears the most feasible across Europe. Challenges are health inequalities, identification of best target groups for screening, streamlined processes, the need for evidence of benefit and a tailored approach adapted to national realities.
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Affiliation(s)
- Daniel Engler
- Department of Cardiology, University Medical Center Hamburg-Eppendorf, University Heart & Vascular Center Hamburg, Hamburg, Germany
- German Center for Cardiovascular Research (DZHK) partner site Hamburg/Kiel/Lübeck, Hamburg, Germany
| | - Coral L Hanson
- School of Health and Social Care, Edinburgh Napier University, Edinburgh, UK
| | - Lien Desteghe
- Heart Center Hasselt, Jessa Hospital, Hasselt, Belgium
- Department of Cardiology, Antwerp University Hospital, Antwerp, Belgium
- Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium
- Research Group Cardiovascular Diseases, University of Antwerp, Antwerp, Belgium
| | - Giuseppe Boriani
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, Modena, Italy
| | - Søren Zöga Diederichsen
- Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Ben Freedman
- Heart Research Institute, The University of Sydney, Sydney, New South Wales, Australia
- University of Sydney, Charles Perkins Centre, Sydney, New South Wales, Australia
- Deptartment of Cardiology, Concord Hospital, Concord, Sydney, Australia
| | - Elena Palà
- Neurovascular Research Laboratory, Vall d'Hebron Institute of Research (VHIR), Autonomous University of Barcelona, Barcelona, Spain
| | - Tatjana S Potpara
- Deptartment for Intensive Arrhythmia Care, Cardiology Clinic, Clinical Center of Serbia, Belgrade, Serbia
- School of Medicine, University of Belgrade, Beograd, Serbia
| | | | - Hein Heidbuchel
- Department of Cardiology, Antwerp University Hospital, Antwerp, Belgium
- Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium
- Research Group Cardiovascular Diseases, University of Antwerp, Antwerp, Belgium
| | - Lis Neubeck
- School of Health and Social Care, Edinburgh Napier University, Edinburgh, UK
- Sydney Nursing School, University of Sydney, Sydney, New South Wales, Australia
| | - Renate B Schnabel
- Department of Cardiology, University Medical Center Hamburg-Eppendorf, University Heart & Vascular Center Hamburg, Hamburg, Germany
- German Center for Cardiovascular Research (DZHK) partner site Hamburg/Kiel/Lübeck, Hamburg, Germany
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32
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Atrial fibrillation: NICE 2021 update and the focus on anticoagulation. Br J Gen Pract 2022; 72:193-195. [PMID: 35361605 PMCID: PMC8966932 DOI: 10.3399/bjgp22x719069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 01/31/2021] [Indexed: 10/31/2022] Open
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Affiliation(s)
- Fabrice Extramiana
- Assistance Publique-Hôpitaux de Paris, Hôpital Bichat, France (F.E., P.G.S.)
| | - Philippe Gabriel Steg
- Université de Paris, INSERM-1148, France (P.G.S.).,Assistance Publique-Hôpitaux de Paris, Hôpital Bichat, France (F.E., P.G.S.).,French Alliance for Cardiovascular Trials, Paris, France (P.G.S.).,Imperial College, Royal Brompton Hospital, London, UK (P.G.S.)
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Lubitz SA, Atlas SJ, Ashburner JM, Trisini Lipsanopoulos AT, Borowsky LH, Guan W, Khurshid S, Ellinor PT, Chang Y, McManus DD, Singer DE. Screening for Atrial Fibrillation in Older Adults at Primary Care Visits: VITAL-AF Randomized Controlled Trial. Circulation 2022; 145:946-954. [PMID: 35232217 PMCID: PMC8960369 DOI: 10.1161/circulationaha.121.057014] [Citation(s) in RCA: 61] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 01/19/2022] [Indexed: 12/30/2022]
Abstract
BACKGROUND Undiagnosed atrial fibrillation (AF) may cause preventable strokes. Guidelines differ regarding AF screening recommendations. We tested whether point-of-care screening with a handheld single-lead ECG at primary care practice visits increases diagnoses of AF. METHODS We randomized 16 primary care clinics 1:1 to AF screening using a handheld single-lead ECG (AliveCor KardiaMobile) during vital sign assessments, or usual care. Patients included were ages ≥65 years. Screening results were provided to primary care clinicians at the encounter. All confirmatory diagnostic testing and treatment decisions were made by the primary care clinician. New AF diagnoses during the 1-year follow-up were ascertained electronically and manually adjudicated. Proportions and incidence rates were calculated. Effect heterogeneity was assessed. RESULTS Of 30 715 patients without prevalent AF (n=15 393 screening [91% screened], n=15 322 control), 1.72% of individuals in the screening group had new AF diagnosed at 1 year versus 1.59% in the control group (risk difference, 0.13% [95% CI, -0.16 to 0.42]; P=0.38). In prespecified subgroup analyses, new AF diagnoses in the screening and control groups were greater among those aged ≥85 years (5.56% versus 3.76%, respectively; risk difference, 1.80% [95% CI, 0.18 to 3.30]). The difference in newly diagnosed AF between the screening period and the previous year was marginally greater in the screening versus control group (0.32% versus -0.12%; risk difference, 0.43% [95% CI, -0.01 to 0.84]). The proportion of individuals with newly diagnosed AF who were initiated on oral anticoagulants was not different in the screening (n=194, 73.5%) and control (n=172, 70.8%) arms (risk difference, 2.7% [95% CI, -5.5 to 10.4]). CONCLUSIONS Screening for AF using a single-lead ECG at primary care visits did not affect new AF diagnoses among all individuals aged 65 years or older compared with usual care. REGISTRATION URL: https://www. CLINICALTRIALS gov; Unique identifier: NCT03515057.
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Affiliation(s)
- Steven A. Lubitz
- Demoulas Center for Cardiac Arrhythmias and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Steven J. Atlas
- Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Jeffrey M. Ashburner
- Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | | | - Leila H. Borowsky
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Wyliena Guan
- University of North Carolina, Chapel Hill, NC, USA
| | - Shaan Khurshid
- Demoulas Center for Cardiac Arrhythmias and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Patrick T. Ellinor
- Demoulas Center for Cardiac Arrhythmias and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Yuchiao Chang
- Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - David D. McManus
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA, USA
| | - Daniel E. Singer
- Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
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35
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Himmelreich JCL, Harskamp RE, Geelhoed B, Virdone S, Lucassen WAM, Gansevoort RT, Rienstra M. Validating risk models versus age alone for atrial fibrillation in a young Dutch population cohort: should atrial fibrillation risk prediction be expanded to younger community members? BMJ Open 2022; 12:e057476. [PMID: 35173009 PMCID: PMC8852746 DOI: 10.1136/bmjopen-2021-057476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
BACKGROUND Advancing age is the primary selection criterion for community screening for atrial fibrillation (AF), with selection often restricted to those aged ≥65 years. If multivariable models were shown to have considerable additional value over age alone in predicting AF risk among younger individuals, AF screening could be expanded to patients with lower age, but with high AF risk as per a validated risk model. METHODS We validated risk models CHARGE-AF (Cohorts for Heart and Aging Research in Genomic Epidemiology model for AF) and FHS-AF (Framingham Heart Study model for AF), and risk scores CHA2DS2-VASc and CHA2DS2-VA, and presented their predictive abilities for 5-year and 10-year AF risk versus that of age alone in a young Dutch population cohort (PREVEND) free from AF at baseline. We assessed discrimination by the C-statistic and calibration by the calibration plot and stratified Kaplan-Meier plot using survey-weighted Cox models. RESULTS During 5-year and 10-year follow-up there were n=98 (2.46/1000 person-years) and n=249 (3.29/1000 person-years) new AF cases, respectively, among 8265 participants with mean age 49±13 years. CHARGE-AF and FHS-AF both showed good discrimination for 5-year and 10-year AF (C-statistic range 0.83-0.86) with accurate calibration for 5-year AF, but overestimation of 10-year AF risk in highest-risk individuals. CHA2DS2-VASc and CHA2DS2-VA relatively underperformed. Age alone showed similar discrimination to that of CHARGE-AF and FHS-AF both in the overall, young PREVEND cohort and in subgroups for lower age and lower stroke risk. CONCLUSION Multivariable models accurately discriminate for 5-year and 10-year AF risk among young European community-dwelling individuals. However, their additional discriminatory value over age alone was limited. Selection strategies for primary AF screening using multivariable models should not be expanded to younger individuals.
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Affiliation(s)
- Jelle C L Himmelreich
- Department of General Practice, Amsterdam Public Health, Amsterdam UMC Locatie AMC, Amsterdam, The Netherlands
| | - Ralf E Harskamp
- Department of General Practice, Amsterdam Public Health, Amsterdam UMC Locatie AMC, Amsterdam, The Netherlands
| | - Bastiaan Geelhoed
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Saverio Virdone
- Department of Statistics, Thrombosis Research Institute, London, UK
| | - Wim A M Lucassen
- Department of General Practice, Amsterdam Public Health, Amsterdam UMC Locatie AMC, Amsterdam, The Netherlands
| | - Ron T Gansevoort
- Department of Nephrology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Michiel Rienstra
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
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36
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Wong KC, Nguyen TN, Marschner S, Turnbull S, Burns MJ, Ne JYA, Gopal V, Indrawansa AB, Trankle SA, Usherwood T, Kumar S, Lindley RI, Chow CK. Patient-Led Mass Screening for Atrial Fibrillation in the Older Population Using Handheld Electrocardiographic Devices Integrated With a Clinician-Coordinated Remote Central Monitoring System: Protocol for a Randomized Controlled Trial and Process Evaluation. JMIR Res Protoc 2022; 11:e34778. [PMID: 35103614 PMCID: PMC8848249 DOI: 10.2196/34778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 01/10/2022] [Accepted: 01/11/2022] [Indexed: 11/18/2022] Open
Abstract
Background Atrial fibrillation (AF) is common in older people and increases the risk of stroke. The feasibility and effectiveness of the implementation of a patient-led AF screening program for older people are unknown. Objective This study aims to examine the feasibility and effectiveness of an AF screening program comprising patient-led monitoring of single-lead electrocardiograms (ECGs) with clinician-coordinated central monitoring to diagnose AF among community-dwelling people aged ≥75 years in Australia. Methods This is a nationwide randomized controlled implementation trial conducted via the internet and remotely among 200 community-dwelling adults aged ≥75 years with no known AF. Randomization will be performed in a 1:1 allocation ratio for the intervention versus control. Intervention group participants will be enrolled in the monitoring program at randomization. They will receive a handheld single-lead ECG device and training on the self-recording of ECGs on weekdays and submit their ECGs via their smartphones. The control group participants will receive usual care from their general practitioners for the initial 6 months and then commence the 6-month monitoring program. The ECGs will be reviewed centrally by trained personnel. Participants and their general practitioners will be notified of AF and other clinically significant ECG abnormalities. Results This study will establish the feasibility and effectiveness of implementing the intervention in this patient population. The primary clinical outcome is the AF detection rate, and the primary feasibility outcome is the patient satisfaction score. Other outcomes include appropriate use of anticoagulant therapy, participant recruitment rate, program engagement (eg, frequency of ECG transmission), agreement in ECG interpretation between the device automatic algorithm and clinicians, the proportion of participants who complete the trial and number of dropouts, and the impact of frailty on feasibility and outcomes. We will conduct a qualitative evaluation to examine the barriers to and acceptability and enablers of implementation. Ethics approval was obtained from the human research ethics committee at the University of Sydney (project number 2020/680). The results will be disseminated via conventional scientific forums, including peer-reviewed publications and presentations at national and international conferences. Conclusions By incorporating an integrated health care approach involving patient empowerment, centralized clinician-coordinated ECG monitoring, and facilitation of primary care and specialist services, it is possible to diagnose and treat AF early to reduce stroke risk. This study will provide new information on how to implement AF screening using digital health technology practicably and feasibly for older and frail populations residing in the community. Trial Registration Australian New Zealand Clinical Trials Registry ACTRN12621000184875; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=380877 International Registered Report Identifier (IRRID) DERR1-10.2196/34778
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Affiliation(s)
- Kam Cheong Wong
- Westmead Applied Research Centre, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
- Westmead Clinical School, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
- Bathurst Rural Clinical School, School of Medicine, Western Sydney University, Bathurst, Australia
- School of Rural Health, Faculty of Medicine and Health, The University of Sydney, Orange, Australia
| | - Tu N Nguyen
- Westmead Applied Research Centre, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Simone Marschner
- Westmead Applied Research Centre, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Samual Turnbull
- Westmead Applied Research Centre, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
- Department of Cardiology, Westmead Hospital, Westmead, Australia
| | - Mason Jenner Burns
- Westmead Applied Research Centre, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Jia Yi Anna Ne
- Westmead Applied Research Centre, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
- Department of Cardiology, Westmead Hospital, Westmead, Australia
| | - Vishal Gopal
- Westmead Applied Research Centre, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | | | - Steven A Trankle
- General Practice Department, School of Medicine, Western Sydney University, Campbelltown, Australia
| | - Tim Usherwood
- Westmead Applied Research Centre, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
- Westmead Clinical School, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
- The George Institute for Global Health, Sydney, Australia
| | - Saurabh Kumar
- Westmead Applied Research Centre, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
- Westmead Clinical School, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
- Department of Cardiology, Westmead Hospital, Westmead, Australia
| | - Richard I Lindley
- Westmead Applied Research Centre, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
- The George Institute for Global Health, Sydney, Australia
| | - Clara K Chow
- Westmead Applied Research Centre, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
- Westmead Clinical School, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
- Department of Cardiology, Westmead Hospital, Westmead, Australia
- The George Institute for Global Health, Sydney, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, Australia
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Meyre PB, Aeschbacher S, Blum S, Voellmin G, Kastner PM, Hennings E, Kaufmann BA, Kühne M, Osswald S, Conen D. Biomarkers associated with rhythm status after cardioversion in patients with atrial fibrillation. Sci Rep 2022; 12:1680. [PMID: 35102265 PMCID: PMC8803959 DOI: 10.1038/s41598-022-05769-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 01/13/2022] [Indexed: 01/13/2023] Open
Abstract
Biomarkers may help to improve our knowledge about the complex pathophysiology of atrial fibrillation (AF). In this study we sought to identify significant changes in biomarkers and clinical measures in patients with and without AF recurrence after electrical cardioversion. We measured 21 conventional and new biomarkers before and 30 days after electrical cardioversion and assessed the associations of changes in biomarker levels with rhythm status at follow-up. Significant between-group changes were observed for bone morphogenetic protein 10 (BMP10), N-terminal pro-B-type natriuretic peptide (NT-proBNP) and total bilirubin. Their respective changes were - 10.4%, - 62.0% and - 25.6% in patients with sinus rhythm, and 3.1%, 1.1% and - 9.4% in patients with recurrent AF, for a between-group difference of - 13.5% (95% confidence interval [CI] - 19.3% to - 7.6%; P < 0.001), - 63.1% (95% CI - 76.6% to - 49.6%; P < 0.001) and - 16.3% (95% CI - 27.9% to - 4.7%; P = 0.007). In multivariable models, the reductions of BMP10 and NT-proBNP were significantly associated with follow-up rhythm status (β coefficient per 1 - SD decrease, - 3.85; 95% CI - 6.34 to - 1.35; P = 0.003 for BMP10 and - 5.84; 95% CI - 10.22 to - 1.47; P = 0.009 for NT-proBNP. In conclusion, changes in BMP10 und NT-proBNP levels were independently associated with rhythm status after cardioversion, suggesting that these markers may be dependent on the actual heart rhythm.
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Affiliation(s)
- Pascal B Meyre
- Division of Cardiology, Department of Medicine, University Hospital Basel, Basel, Switzerland.
- Cardiovascular Research Institute Basel, University Hospital Basel, Spitalstrasse 2, 4031, Basel, Switzerland.
| | - Stefanie Aeschbacher
- Division of Cardiology, Department of Medicine, University Hospital Basel, Basel, Switzerland
- Cardiovascular Research Institute Basel, University Hospital Basel, Spitalstrasse 2, 4031, Basel, Switzerland
| | - Steffen Blum
- Division of Cardiology, Department of Medicine, University Hospital Basel, Basel, Switzerland
- Cardiovascular Research Institute Basel, University Hospital Basel, Spitalstrasse 2, 4031, Basel, Switzerland
| | - Gian Voellmin
- Division of Cardiology, Department of Medicine, University Hospital Basel, Basel, Switzerland
- Cardiovascular Research Institute Basel, University Hospital Basel, Spitalstrasse 2, 4031, Basel, Switzerland
| | | | - Elisa Hennings
- Division of Cardiology, Department of Medicine, University Hospital Basel, Basel, Switzerland
- Cardiovascular Research Institute Basel, University Hospital Basel, Spitalstrasse 2, 4031, Basel, Switzerland
| | - Beat A Kaufmann
- Division of Cardiology, Department of Medicine, University Hospital Basel, Basel, Switzerland
- Cardiovascular Research Institute Basel, University Hospital Basel, Spitalstrasse 2, 4031, Basel, Switzerland
| | - Michael Kühne
- Division of Cardiology, Department of Medicine, University Hospital Basel, Basel, Switzerland
- Cardiovascular Research Institute Basel, University Hospital Basel, Spitalstrasse 2, 4031, Basel, Switzerland
| | - Stefan Osswald
- Division of Cardiology, Department of Medicine, University Hospital Basel, Basel, Switzerland
- Cardiovascular Research Institute Basel, University Hospital Basel, Spitalstrasse 2, 4031, Basel, Switzerland
| | - David Conen
- Population Health Research Institute, McMaster University, Hamilton, ON, Canada
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Kahwati LC, Asher GN, Kadro ZO, Keen S, Ali R, Coker-Schwimmer E, Jonas DE. Screening for Atrial Fibrillation: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force. JAMA 2022; 327:368-383. [PMID: 35076660 DOI: 10.1001/jama.2021.21811] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
IMPORTANCE Atrial fibrillation (AF), the most common arrhythmia, increases the risk of stroke. OBJECTIVE To review the evidence on screening for AF in adults without prior stroke to inform the US Preventive Services Task Force. DATA SOURCES PubMed, Cochrane Library, and trial registries through October 5, 2020; references, experts, and literature surveillance through October 31, 2021. STUDY SELECTION Randomized clinical trials (RCTs) of screening among asymptomatic persons without known AF or prior stroke; test accuracy studies; RCTs of anticoagulation among persons with AF; systematic reviews; and observational studies reporting harms. DATA EXTRACTION AND SYNTHESIS Two reviewers assessed titles/abstracts, full-text articles, and study quality and extracted data; when at least 3 similar studies were available, meta-analyses were conducted. MAIN OUTCOMES AND MEASURES Detection of undiagnosed AF, test accuracy, mortality, stroke, stroke-related morbidity, and harms. RESULTS Twenty-six studies (N = 113 784) were included. In 1 RCT (n = 28 768) of twice-daily electrocardiography (ECG) screening for 2 weeks, the likelihood of a composite end point (ischemic stroke, hemorrhagic stroke, systemic embolism, all-cause mortality, and hospitalization for bleeding) was lower in the screened group over 6.9 years (hazard ratio, 0.96 [95% CI, 0.92-1.00]; P = .045), but that study had numerous limitations. In 4 RCTs (n = 32 491), significantly more AF was detected with intermittent and continuous ECG screening compared with no screening (risk difference range, 1.0%-4.8%). Treatment with warfarin over a mean of 1.5 years in populations with clinical, mostly persistent AF was associated with fewer ischemic strokes (pooled risk ratio [RR], 0.32 [95% CI, 0.20-0.51]; 5 RCTs; n = 2415) and lower all-cause mortality (pooled RR, 0.68 [95% CI, 0.50-0.93]) compared with placebo. Treatment with direct oral anticoagulants was also associated with lower incidence of stroke (adjusted odds ratios range, 0.32-0.44) in indirect comparisons with placebo. The pooled RR for major bleeding for warfarin compared with placebo was 1.8 (95% CI, 0.85-3.7; 5 RCTs; n = 2415), and the adjusted odds ratio for major bleeding for direct oral anticoagulants compared with placebo or no treatment ranged from 1.38 to 2.21, but CIs did not exclude a null effect. CONCLUSIONS AND RELEVANCE Although screening can detect more cases of unknown AF, evidence regarding effects on health outcomes is limited. Anticoagulation was associated with lower risk of first stroke and mortality but with increased risk of major bleeding, although estimates for this harm are imprecise; no trials assessed benefits and harms of anticoagulation among screen-detected populations.
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Affiliation(s)
- Leila C Kahwati
- RTI International-University of North Carolina at Chapel Hill Evidence-based Practice Center
- RTI International, Research Triangle Park, North Carolina
| | - Gary N Asher
- RTI International-University of North Carolina at Chapel Hill Evidence-based Practice Center
- Department of Family Medicine, University of North Carolina at Chapel Hill
| | - Zachary O Kadro
- RTI International-University of North Carolina at Chapel Hill Evidence-based Practice Center
- Department of Physical Medicine and Rehabilitation, University of North Carolina at Chapel Hill
| | - Susan Keen
- RTI International-University of North Carolina at Chapel Hill Evidence-based Practice Center
- Department of Family Medicine, University of North Carolina at Chapel Hill
| | - Rania Ali
- RTI International-University of North Carolina at Chapel Hill Evidence-based Practice Center
- RTI International, Research Triangle Park, North Carolina
| | - Emmanuel Coker-Schwimmer
- RTI International-University of North Carolina at Chapel Hill Evidence-based Practice Center
- Department of Internal Medicine, The Ohio State University College of Medicine, Columbus
| | - Daniel E Jonas
- RTI International-University of North Carolina at Chapel Hill Evidence-based Practice Center
- Department of Internal Medicine, The Ohio State University College of Medicine, Columbus
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39
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Davidson KW, Barry MJ, Mangione CM, Cabana M, Caughey AB, Davis EM, Donahue KE, Doubeni CA, Epling JW, Kubik M, Li L, Ogedegbe G, Pbert L, Silverstein M, Stevermer J, Tseng CW, Wong JB. Screening for Atrial Fibrillation: US Preventive Services Task Force Recommendation Statement. JAMA 2022; 327:360-367. [PMID: 35076659 DOI: 10.1001/jama.2021.23732] [Citation(s) in RCA: 81] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
IMPORTANCE Atrial fibrillation (AF) is the most common cardiac arrhythmia. The prevalence of AF increases with age, from less than 0.2% in adults younger than 55 years to about 10% in those 85 years or older, with a higher prevalence in men than in women. It is uncertain whether the prevalence of AF differs by race and ethnicity. Atrial fibrillation is a major risk factor for ischemic stroke and is associated with a substantial increase in the risk of stroke. Approximately 20% of patients who have a stroke associated with AF are first diagnosed with AF at the time of the stroke or shortly thereafter. OBJECTIVE To update its 2018 recommendation, the US Preventive Services Task Force (USPSTF) commissioned a systematic review on the benefits and harms of screening for AF in older adults, the accuracy of screening tests, the effectiveness of screening tests to detect previously undiagnosed AF compared with usual care, and the benefits and harms of anticoagulant therapy for the treatment of screen-detected AF in older adults. POPULATION Adults 50 years or older without a diagnosis or symptoms of AF and without a history of transient ischemic attack or stroke. EVIDENCE ASSESSMENT The USPSTF concludes that evidence is lacking, and the balance of benefits and harms of screening for AF in asymptomatic adults cannot be determined. RECOMMENDATION The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of screening for AF. (I statement).
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Affiliation(s)
| | - Karina W Davidson
- Feinstein Institutes for Medical Research at Northwell Health, Manhasset, New York
| | | | | | | | | | - Esa M Davis
- University of Pittsburgh, Pittsburgh, Pennsylvania
| | | | | | | | | | - Li Li
- University of Virginia, Charlottesville
| | | | - Lori Pbert
- University of Massachusetts Medical School, Worcester
| | | | | | - Chien-Wen Tseng
- University of Hawaii, Honolulu
- Pacific Health Research and Education Institute, Honolulu, Hawaii
| | - John B Wong
- Tufts University School of Medicine, Boston, Massachusetts
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40
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Passman R, Freedman B. Updated USPSTF Guidelines for Screening for Atrial Fibrillation. JAMA Cardiol 2022; 7:247-249. [DOI: 10.1001/jamacardio.2021.5873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Affiliation(s)
- Rod Passman
- Northwestern University Feinberg School of Medicine, Chicago, Illinois
- Northwestern University Center for Arrhythmia Research, Chicago, Illinois
| | - Ben Freedman
- The Heart Research Institute, Charles Perkins Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
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41
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Screening for paroxysmal atrial fibrillation in primary care using Holter monitoring and intermittent, ambulatory single-lead electrocardiography. Int J Cardiol 2021; 345:41-46. [PMID: 34687805 DOI: 10.1016/j.ijcard.2021.10.021] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 10/11/2021] [Accepted: 10/15/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND Timely detection of atrial fibrillation (AF) is important because of its increased risk of thrombo-embolic events. Single time point screening interventions fall short in detection of paroxysmal AF, which requires prolonged electrocardiographic monitoring, usually using a Holter. However, traditional 24-48 h Holter monitoring is less appropriate for screening purposes because of its low diagnostic yield. Intermittent, ambulatory screening using a single-lead electrocardiogram (1 L-ECG) device can offer a more efficient alternative. METHODS Primary care patients of ≥65 years participated in an opportunistic screening study for AF. We invited patients with a negative 12 L-ECG to wear a Holter monitor for two weeks and to use a MyDiagnostick 1 L-ECG device thrice daily. We report the yield of paroxysmal AF found by Holter monitoring and calculate the diagnostic accuracy of the 1 L-ECG device's built-in AF detection algorithm with the Holter monitor as reference standard. RESULTS We included 270 patients, of whom four had AF in a median of 8.0 days of Holter monitoring, a diagnostic yield of 1.5% (95%-CI: 0.4-3.8%). In 205 patients we performed simultaneous 1 L-ECG screening. For diagnosing AF based on the 1 L-ECG device's AF detection algorithm, sensitivity was 66.7% (95%-CI: 9.4-99.2%), specificity 68.8% (95%-CI: 61.9-75.1%), positive predictive value 3.1% (95%-CI: 1.4-6.8%) and negative predictive value 99.3% (95%-CI: 96.6-99.9%). CONCLUSION We found a low diagnostic yield of paroxysmal AF using Holter monitoring in elderly primary care patients with a negative 12 L-ECG. The diagnostic accuracy of an intermittently, ambulatory used MyDiagnostick 1 L-ECG device as interpreted by its built-in AF detection algorithm is limited.
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42
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Beerten SG, Proesmans T, Vaes B. The effect of a case-finding app on the detection rate of atrial fibrillation compared with opportunistic screening in primary care patients: protocol for a cluster randomized trial. Trials 2021; 22:525. [PMID: 34372905 PMCID: PMC8351454 DOI: 10.1186/s13063-021-05497-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Accepted: 07/28/2021] [Indexed: 11/23/2022] Open
Abstract
Background Atrial fibrillation is a cardiac arrhythmia commonly encountered in a primary care setting. Current screening is limited to pulse palpation and ECG confirmation when an irregular pulse is found. Paroxysmal atrial fibrillation will, however, still be difficult to pick up. With the advent of smartphones, screening could be more cost-efficient by making use of simple applications, lowering the need for intensive screening to discover (paroxysmal) atrial fibrillation. Methods/design This cluster randomized trial will examine the effect of using a smartphone-based application such as FibriCheck® on the detection rate of atrial fibrillation in a Flemish general practice population. This study will be conducted in 22 primary care practices across the Flanders region of Belgium and will last 12 months. Patients above 65 years of age will be divided in control and intervention groups on the practice level. The control group will be subjected to standard opportunistic screening only, while the intervention group will be prescribed the FibriCheck® app on top of this opportunistic screening. The difference in detection rate between control and intervention groups will be calculated at the end of the study. We will use the online platform INTEGO for pseudonymized data collection and analysis, and risk calculation. Discussion Smartphone applications might offer a way to cost-effectively screen for (paroxysmal) atrial fibrillation in a primary care setting. This could open the door for the update of future screening guidelines. Trial registration ClinicalTrials.gov NCT04545723. Registered on September 10, 2020.
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Affiliation(s)
| | | | - Bert Vaes
- Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium
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43
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Liran O, Banon T, Grossman A. Detection of occult atrial fibrillation with 24-hour ECG after cryptogenic acute stroke or transient ischaemic attack: A retrospective cross-sectional study in a primary care database in Israel. Eur J Gen Pract 2021; 27:152-157. [PMID: 34240675 PMCID: PMC8274499 DOI: 10.1080/13814788.2021.1947237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
Abstract
Background Ischaemic stroke or cerebrovascular accident (CVA) due to occult atrial fibrillation (AF) may cause severe morbidity and mortality. Diagnosing occult AF can be challenging and there is no consensus regarding the optimal duration of screening. A 24-hour Holter electrocardiogram (ECG) is frequently employed to detect occult AF following ischaemic CVA. Objectives Demonstration of occult AF detection rate using a 24-hour Holter ECG in a primary care setting with descriptive analyses of independent variables to compare AF detected and non-detected patients. Methods This retrospective cross-sectional study utilised primary care data and included patients 50 years and older with a new CVA or transient ischaemic attack (TIA) diagnosis followed by a 24-hour Holter examination within 6 months, between 01 January 2013 and 01 June 2019. The analyses included descriptive statistics comparing demographics and clinical characteristics in patients who had AF or Atrial Flutter (AFL) detection to those who did not. Results Out of 5015 eligible patients, 66 (1.3%) were diagnosed with AF/AFL, with a number needed to screen of 88.5. Compared with those without AF/AFL detection, those diagnosed were older (75.42 ± 7.89 vs. 69.89 ± 9.88, p = 0.050), had a higher prevalence of hypertension (80.3% vs. 66.8%, p = 0.021) and chronic kidney disease (CKD) (71.2% vs. 44.2%, p < 0.001). Conclusion 24-hour Holter has a low AF/AFL detection rate. Older persons and those with hypertension or CKD are more likely to be detected with AF/AFL using this method.
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Affiliation(s)
- Ori Liran
- Maccabi Healthcare Services, Tel-Aviv, Israel
| | - Tamar Banon
- Maccabi Healthcare Services, Tel-Aviv, Israel
| | - Alon Grossman
- Maccabi Healthcare Services, Tel-Aviv, Israel.,Department of Internal Medicine B, Rabin Medical Center, Petah Tikva, Israel
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44
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Wang L, Nielsen K, Goldberg J, Brown JR, Rumsfeld JS, Steinberg BA, Zhang Y, Matheny ME, Shah RU. Association of Wearable Device Use With Pulse Rate and Health Care Use in Adults With Atrial Fibrillation. JAMA Netw Open 2021; 4:e215821. [PMID: 34042996 PMCID: PMC8160588 DOI: 10.1001/jamanetworkopen.2021.5821] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 02/24/2021] [Indexed: 02/04/2023] Open
Abstract
Importance Increasingly, individuals with atrial fibrillation (AF) use wearable devices (hereafter wearables) that measure pulse rate and detect arrhythmia. The associations of wearables with health outcomes and health care use are unknown. Objective To characterize patients with AF who use wearables and compare pulse rate and health care use between individuals who use wearables and those who do not. Design, Setting, and Participants This retrospective, propensity-matched cohort study included 90 days of follow-up of patients in a tertiary care, academic health system. Included patients were adults with at least 1 AF-specific International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) code from 2017 through 2019. Electronic medical records were reviewed to identify 125 individuals who used wearables and had adequate pulse-rate follow-up who were then matched using propensity scores 4 to 1 with 500 individuals who did not use wearables. Data were analyzed from June 2020 through February 2021. Exposure Using commercially available wearables with pulse rate or rhythm evaluation capabilities. Main Outcomes and Measures Mean pulse rates from measures taken in the clinic or hospital and a composite health care use score were recorded. The composite outcome included evaluation and management, ablation, cardioversion, telephone encounters, and number of rate or rhythm control medication orders. Results Among 16 320 patients with AF included in the analysis, 348 patients used wearables and 15 972 individuals did not use wearables. Prior to matching, patients using wearables were younger (mean [SD] age, 64.0 [13.0] years vs 70.0 [13.8] years; P < .001) and healthier (mean [SD] CHA2DS2-VASc [congestive heart failure, hypertension, age ≥ 65 years or 65-74 years, diabetes, prior stroke/transient ischemic attack, vascular disease, sex] score, 3.6 [2.0] vs 4.4 [2.0]; P < .001) compared with individuals not using wearables, with similar gender distribution (148 [42.5%] women vs 6722 women [42.1%]; P = .91). After matching, mean pulse rate was similar between 125 patients using wearables and 500 patients not using wearables (75.01 [95% CI, 72.74-77.27] vs 75.79 [95% CI, 74.68-76.90] beats per minute [bpm]; P = .54), whereas mean composite use score was higher among individuals using wearables (3.55 [95% CI, 3.31-3.80] vs 3.27 [95% CI, 3.14-3.40]; P = .04). Among measures in the composite outcome, there was a significant difference in use of ablation, occurring in 22 individuals who used wearables (17.6%) vs 37 individuals who did not use wearables (7.4%) (P = .001). In the regression analyses, mean composite use score was 0.28 points (95% CI, 0.01 to 0.56 points) higher among individuals using wearables compared with those not using wearables and mean pulse was similar, with a -0.79 bpm (95% CI -3.28 to 1.71 bpm) difference between the groups. Conclusions and Relevance This study found that follow-up health care use among individuals with AF was increased among those who used wearables compared with those with similar pulse rates who did not use wearables. Given the increasing use of wearables by patients with AF, prospective, randomized, long-term evaluation of the associations of wearable technology with health outcomes and health care use is needed.
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Affiliation(s)
- Libo Wang
- Division of Cardiovascular Medicine, University of Utah School of Medicine, Salt Lake City
| | - Kyron Nielsen
- Division of Cardiovascular Medicine, University of Utah School of Medicine, Salt Lake City
| | - Joshua Goldberg
- Department of Internal Medicine, University of Utah, Salt Lake City
| | - Jeremiah R. Brown
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire
- Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire
| | | | - Benjamin A. Steinberg
- Division of Cardiovascular Medicine, University of Utah School of Medicine, Salt Lake City
| | - Yue Zhang
- Department of Internal Medicine, University of Utah, Salt Lake City
- Study Design and Biostatistics Center, Center for Clinical and Translational Science, University of Utah, Salt Lake City
| | - Michael E. Matheny
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
- Geriatric Research Education and Clinical Center, Tennessee Valley Healthcare System, Nashville VA Medical Center, Nashville
| | - Rashmee U. Shah
- Division of Cardiovascular Medicine, University of Utah School of Medicine, Salt Lake City
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Gladstone DJ, Wachter R, Schmalstieg-Bahr K, Quinn FR, Hummers E, Ivers N, Marsden T, Thornton A, Djuric A, Suerbaum J, von Grünhagen D, McIntyre WF, Benz AP, Wong JA, Merali F, Henein S, Nichol C, Connolly SJ, Healey JS. Screening for Atrial Fibrillation in the Older Population: A Randomized Clinical Trial. JAMA Cardiol 2021; 6:558-567. [PMID: 33625468 DOI: 10.1001/jamacardio.2021.0038] [Citation(s) in RCA: 114] [Impact Index Per Article: 28.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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.
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Affiliation(s)
- David J Gladstone
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, and Division of Neurology, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Rolf Wachter
- Clinic and Policlinic for Cardiology, University Hospital, Leipzig, Germany.,Department of Cardiology, University Medical Center Göttingen, Göttingen, Germany.,DZHK (German Centre for Cardiovascular Research), partner site Göttingen, Göttingen, Germany
| | - Katharina Schmalstieg-Bahr
- Department of General Practice, University Medical Center Göttingen, Göttingen, Germany.,Department of General Practice and Primary Care, University Medical Center Hamburg-Eppendorf, Hamburg-Eppendorf, Germany
| | - F Russell Quinn
- Libin Cardiovascular Institute, University of Calgary, Calgary, Alberta, Canada
| | - Eva Hummers
- DZHK (German Centre for Cardiovascular Research), partner site Göttingen, Göttingen, Germany.,Department of General Practice, University Medical Center Göttingen, Göttingen, Germany
| | - Noah Ivers
- Women's College Hospital, Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Tamara Marsden
- Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada
| | - Andrea Thornton
- Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada
| | - Angie Djuric
- Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada
| | - Johanna Suerbaum
- Department of Cardiology, University Medical Center Göttingen, Göttingen, Germany.,DZHK (German Centre for Cardiovascular Research), partner site Göttingen, Göttingen, Germany
| | - Doris von Grünhagen
- Clinic for Cardiology and Pneumology, University Medicine Göttingen, Göttingen, Germany
| | - William F McIntyre
- Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada
| | - Alexander P Benz
- Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada
| | - Jorge A Wong
- Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada
| | | | - Sam Henein
- Southlake Regional Health Centre, Newmarket, Ontario, Canada
| | - Chris Nichol
- Camrose Primary Care Network, Camrose, Alberta, Canada
| | - Stuart J Connolly
- Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada
| | - Jeff S Healey
- Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada
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Boriani G, Palmisano P, Malavasi VL, Fantecchi E, Vitolo M, Bonini N, Imberti JF, Valenti AC, Schnabel RB, Freedman B. Clinical Factors Associated with Atrial Fibrillation Detection on Single-Time Point Screening Using a Hand-Held Single-Lead ECG Device. J Clin Med 2021; 10:729. [PMID: 33673209 PMCID: PMC7917757 DOI: 10.3390/jcm10040729] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 02/05/2021] [Accepted: 02/08/2021] [Indexed: 02/07/2023] Open
Abstract
Our aim was to assess the prevalence of unknown atrial fibrillation (AF) among adults during single-time point rhythm screening performed during meetings or social recreational activities organized by patient groups or volunteers. A total of 2814 subjects (median age 68 years) underwent AF screening by a handheld single-lead ECG device (MyDiagnostick). Overall, 56 subjects (2.0%) were diagnosed with AF, as a result of 12-lead ECG following a positive/suspected recording. Screening identified AF in 2.9% of the subjects ≥ 65 years. None of the 265 subjects aged below 50 years was found positive at AF screening. Risk stratification for unknown AF based on a CHA2DS2VASc > 0 in males and >1 in females (or CHA2DS2VA > 0) had a high sensitivity (98.2%) and a high negative predictive value (99.8%) for AF detection. A slightly lower sensitivity (96.4%) was achieved by using age ≥ 65 years as a risk stratifier. Conversely, raising the threshold at ≥75 years showed a low sensitivity. Within the subset of subjects aged ≥ 65 a CHA2DS2VASc > 1 in males and >2 in females, or a CHA2DS2VA > 1 had a high sensitivity (94.4%) and negative predictive value (99.3%), while age ≥ 75 was associated with a marked drop in sensitivity for AF detection.
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Affiliation(s)
- Giuseppe Boriani
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (E.F.); (M.V.); (N.B.); (J.F.I.); (A.C.V.)
| | - Pietro Palmisano
- Cardiology Unit, “Card. G. Panico” Hospital, 73039 Tricase, Italy;
| | - Vincenzo Livio Malavasi
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (E.F.); (M.V.); (N.B.); (J.F.I.); (A.C.V.)
| | - Elisa Fantecchi
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (E.F.); (M.V.); (N.B.); (J.F.I.); (A.C.V.)
| | - Marco Vitolo
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (E.F.); (M.V.); (N.B.); (J.F.I.); (A.C.V.)
- Clinical and Experimental Medicine PhD Program, University of Modena and Reggio Emilia, 41125 Modena, Italy
| | - Niccolo’ Bonini
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (E.F.); (M.V.); (N.B.); (J.F.I.); (A.C.V.)
| | - Jacopo F. Imberti
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (E.F.); (M.V.); (N.B.); (J.F.I.); (A.C.V.)
| | - Anna Chiara Valenti
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (E.F.); (M.V.); (N.B.); (J.F.I.); (A.C.V.)
| | - Renate B. Schnabel
- German Cardiovascular Research Center (DZHK), Partner Site Hamburg/Kiel/Lübeck, University Heart and Vascular Centre, 20251 Hamburg, Germany;
| | - Ben Freedman
- Heart Research Institute, Charles Perkins Centre, and Concord Hospital Cardiology, University of Sydney, Sydney 2006, Australia;
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47
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Screening auf Vorhofflimmern lohnt sich nicht. Dtsch Med Wochenschr 2021. [DOI: 10.1055/a-1292-0642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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