AER 9.4 by Radcliffe Cardiology

Volume 9 • Issue 4 • Winter 2020

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Sudden Cardiac Death Risk Stratification and Prevention in Chagas Disease: A Non-systematic Review of the Literature Roberto Keegan, Cynthia Yeung and Adrian Baranchuk

Management of Cardiac Sarcoidosis in 2020 Nisha Gilotra, David Okada, Apurva Sharma and Jonathan Chrispin

Cardiac MRI to Manage Atrial Fibrillation Yan Zhao, Lilas Dagher, Chao Huang, Peter Miller and Nassir F Marrouche

Anisotropic Cardiac Conduction Irum Kotadia, John Whitaker, Caroline Roney, Steven Niederer, Mark O’Neill, Martin Bishop and Matthew Wright

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18F-Fluorodeoxyglucose Uptake in the Atrium in a Patient with AF

Quantification of Left Atrial Wall Fibrosis

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Functional Re-entry Circuit Demonstrating the Leading Circle Concept

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Volume 9 • Issue 4 • Winter 2020

www.AERjournal.com Official journal of

Editor-in-Chief Demosthenes G Katritsis Hygeia Hospital, Athens

Section Editor – Clinical Electrophysiology and Ablation

Section Editor – Arrhythmia Mechanisms / Basic Science

Section Editor – Atrial Fibrillation

Johns Hopkins Medicine, Baltimore, MD

Royal Papworth and Addenbrooke’s Hospitals, Cambridge

Section Editor – Implantable Devices

Section Editor – Arrhythmia Risk Stratification

Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool

Pier D Lambiase

Section Editor – Imaging in Electrophysiology

Virginia Commonwealth University School of Medicine, Richmond, VA

Institute of Cardiovascular Science, University College London, and Barts Heart Centre, London

Stanford University Medical Center, CA

Hugh Calkins

Ken Ellenbogen

Editorial Board

Andrew Grace

Gregory YH Lip

Sanjiv M Narayan

Joseph G Akar

Carsten W Israel

Douglas Packer

Yale University School of Medicine, New Haven, CT

JW Goethe University, Frankfurt

Mayo Clinic, St Mary’s Campus, Rochester, MN

Charles Antzelevitch

Warren Jackman

Carlo Pappone

Heart Rhythm Institute, University of Oklahoma Health Sciences Center, Oklahoma City, OK

IRCCS Policlinico San Donato, Milan

Sunny Po

Pierre Jaïs

Heart Rhythm Institute, University of Oklahoma Health Sciences Center, Oklahoma City, OK

Lankenau Institute for Medical Research, Pennsylvania, PA

Angelo Auricchio Fondazione Cardiocentro Ticino, Lugano

Carina Blomström-Lundqvist Uppsala University, Uppsala

Johannes Brachmann Klinikum Coburg, II Med Klinik, Coburg

Josep Brugada Hospital Sant Joan de Déu, University of Barcelona, Barcelona

Pedro Brugada

University of Bordeaux, CHU Bordeaux

Roy John Northshore University Hospital, New York, NY

Prapa Kanagaratnam

Edward Rowland Barts Heart Centre, St Bartholomew’s Hospital, London

Frédéric Sacher

Imperial College Healthcare NHS Trust, London

Bordeaux University Hospital, Electrophysiology and Heart Modelling Institute, Bordeaux

Josef Kautzner

Richard Schilling

Institute for Clinical and Experimental Medicine, Prague

Barts Health NHS Trust, London

University of Brussels, UZ-Brussel-VUB

Roberto Keegan

Afzal Sohaib

Alfred Buxton

Hospital Privado del Sur, Bahia Blanca, Argentina

Imperial College London and Barts Health NHS Trust, London

Beth Israel Deaconess Medical Center, Boston, MA

Karl-Heinz Kuck

William Stevenson

Asklepios Klinik St Georg, Hamburg

Vanderbilt School of Medicine, Nashville, TN

Cecilia Linde

Richard Sutton

David J Callans University of Pennsylvania, Philadelphia, PA

A John Camm St George’s University of London, London

Shih-Ann Chen National Yang Ming University School of Medicine and Taipei Veterans General Hospital, Taipei

Harry Crijns Maastricht University Medical Center, Maastricht

Sabine Ernst

National Heart and Lung Institute, Imperial College London, London

Karolinska University, Stockholm

Francis Marchlinski University of Pennsylvania Health System, Philadelphia, PA

John Miller Indiana University School of Medicine, Indiana, IN

Fred Morady Cardiovascular Center, University of Michigan, MI

Royal Brompton & Harefield NHS Foundation Trust, London

Andrea Natale

Hein Heidbuchel Antwerp University and University Hospital, Antwerp

Texas Cardiac Arrhythmia Institute, St David’s Medical Center, Austin, TX

Gerhard Hindricks

Mark O’Neill

University of Leipzig, Leipzig

St Thomas’ Hospital and King’s College London, London

Panos Vardas Heraklion University Hospital, Heraklion

Marc A Vos University Medical Center Utrecht, Utrecht

Hein Wellens University of Maastricht, Maastricht

Katja Zeppenfeld Leiden University Medical Center, Leiden

Douglas P Zipes Krannert Institute of Cardiology, Indiana University School of Medicine, Indianapolis, IN

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Established: October 2012 | Frequency: Quarterly | Current issue: Winter 2020

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• Arrhythmia & Electrophysiology Review is an international, English language, peer-reviewed, open access quarterly journal that publishes articles on www.AERjournal.com. • Arrhythmia & Electrophysiology Review aims to assist time-pressured physicians to stay abreast of key advances and opinion in heart failure. • Arrhythmia & Electrophysiology Review comprises balanced and comprehensive articles written by leading authorities, addressing the most pertinent developments in the field. • Arrhythmia & Electrophysiology Review provides comprehensive updates on a range of salient issues to support physicians in continuously developing their knowledge and effectiveness in day-to-day clinical practice.

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Contents

Foreword Anisotropic Conduction and Re-entry in the Heart

174

Demosthenes G Katritsis DOI: https://doi.org/10.15420/aer.2020.48

Clinical Arrhythmias Sudden Cardiac Death Risk Stratification and Prevention in Chagas Disease: A Non-systematic Review of the Literature

175

Roberto Keegan, Cynthia Yeung and Adrian Baranchuk DOI: https://doi.org/10.15420/aer.2020.27

Management of Cardiac Sarcoidosis in 2020

182

Nisha Gilotra, David Okada, Apurva Sharma and Jonathan Chrispin DOI: https://doi.org/10.15420/aer.2020.09

Cardiac MRI to Manage Atrial Fibrillation

189

Yan Zhao, Lilas Dagher, Chao Huang, Peter Miller and Nassir F Marrouche DOI: https://doi.org/10.15420/aer.2020.21

Frequency and Determinants of Spontaneous Conversion to Sinus Rhythm in Patients Presenting to the Emergency Department with Recent-onset Atrial Fibrillation: A Systematic Review

195

Nikki AHA Pluymaekers, Astrid NL Hermans, Dominik K Linz, Elton AMP Dudink, Justin GLM Luermans, Bob Weijs, Kevin Vernooy and Harry JGM Crijns DOI: https://doi.org/10.15420/aer.2020.34

Electrophysiology & Ablation Anisotropic Cardiac Conduction

202

Irum Kotadia, John Whitaker, Caroline Roney, Steven Niederer, Mark O’Neill, Martin Bishop and Matthew Wright DOI: https://doi.org/10.15420/aer.2020.04

Decrement Evoked Potential Mapping to Guide Ventricular Tachycardia Ablation: Elucidating the Functional Substrate

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Abhishek Bhaskaran, John Fitzgerald, Nicholas Jackson, Sigfus Gizurarson, Kumaraswamy Nanthakumar and Andreu Porta-Sánchez DOI: https://doi.org/10.15420/aer.2020.25

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Foreword

Anisotropic Conduction and Re-entry in the Heart

Citation: Arrhythmia & Electrophysiology Review 2020;9(4):174. DOI: https://doi.org/10.15420/aer.2020.48 Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for non-commercial purposes, provided the original work is cited correctly.

ollowing the seminal paper by Madison Spach and Mark Josephson, clinicians have been aware of anisotropic re-entry as an established mechanism of arrhythmogenesis, although the exact mechanisms responsible remain uncertain.1 Nevertheless, changes in microanatomical structures, such as cellular coupling, gap junction distribution and function and fibre disarray, lead to anisotropic conduction, i.e. dependence of myocardial velocity on myocyte orientation.2 Anisotropic conduction was initially attributed to conduction tissue, such as the atrioventricular (AV) node, but we know now that in cardiac tissue, in general, conduction velocity is anisotropic. Particularly in disease states, such as postinfarction myocardium, anisotropic conduction and spatial inhomogeneity of refractoriness may be implicated in the genesis of re-entrant, or even focal, arrhythmias. The length of the re-entrant pathway is determined by subtle electrophysiological–anatomical changes, and there may be an excitable gap. In this issue of Arrhythmia & Electrophysiology Review, Kotadia et al. present an elegant update on the topic, providing very interesting perspectives. Anisotropy is the property of directional dependence, in that the orientation of myocardial activation and velocity are determined by myocyte direction. Thus, the speed of conduction is greatest in the direction parallel to the longitudinal orientation of myocytes. However, myocyte orientation may be identified using diffusion tensor MRI in explanted hearts, and multisite pacing protocols have been proposed to estimate myocyte orientation and anisotropic conduction in vivo. These tools have the potential to contribute to the understanding of the role of myocyte disarray and anisotropic conduction in arrhythmic states. If identifiable during clinical procedures, areas of enhanced anisotropic conduction may represent novel targets in which ablative therapy could be trialled if demonstrated to promote fibrillation. This is an exciting hypothesis that, if proven to have clinical utility, may contribute to our efforts towards substrate characterisation and subsequent modification of arrhythmias difficult to eradicate, such as ventricular tachycardias and, perhaps, AF. Unravelling the mysteries of anisotropic conduction may also provide further insights into arrhythmias apparently unrelated to structural heart disease, such as atrioventricular nodal re-entry tachycardia and its enigmatic circuit. This really is a brave new world in the study and therapy of arrhythmias.

Demosthenes G Katritsis Editor-in-Chief, Arrhythmia & Electrophysiology Review Hygeia Hospital, Athens, Greece

1. 2.

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Spach MS, Josephson ME. Initiating reentry: the role of nonuniform anisotropy in small circuits. J Cardiovasc Electrophysiol 1994;5:182–209. https://doi.org/10.1111/j.1540-8167.1994. tb01157.x; PMID: 8186887. Valderrabano M. Influence of anisotropic conduction properties in the propagation of the cardiac action potential. Prog Biophys Mol Biol 2007;94:144–68. https://doi.org/10.1016/j. pbiomolbio.2007.03.014; PMID: 17482242.

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Clinical Arrhythmias

Sudden Cardiac Death Risk Stratification and Prevention in Chagas Disease: A Non-systematic Review of the Literature Roberto Keegan,1 Cynthia Yeung2 and Adrian Baranchuk2 1. Electrophysiology Service, Hospital Privado del Sur and Hospital Español, Bahia Blanca, Argentina; 2. Department of Cardiology, Queen’s University, Kingston, Canada

Abstract Chagas disease is an important public health problem in Latin America. However, migration and globalisation have resulted in the increased presence of Chagas disease worldwide. Sudden cardiac death is the leading cause of death in people with Chagas disease, most often due to ventricular fibrillation. Although more common in patients with documented ventricular arrhythmias, sudden cardiac death can also be the first manifestation of Chagas disease in patients with no previous symptoms or known heart failure. Major predictors of sudden cardiac death include cardiac arrest, sustained and non-sustained ventricular tachycardia, left ventricular dysfunction, syncope and bradycardia. The authors review the predictors and risk stratification score developed by Rassi et al. for death in Chagas heart disease. They also discuss the evidence for anti-arrhythmic drugs, catheter ablation, ICDs and pacemakers for the prevention of sudden cardiac death in these patients. Given the widespread global burden, understanding the risk stratification and prevention of sudden cardiac death in Chagas disease is of timely concern.

Keywords Chagas disease, Chagas cardiomyopathy, sudden cardiac death, review, risk stratification, prevention Disclosure: The authors have no conflicts of interest to declare. Received: 12 June 2020 Accepted: 10 October 2020 Citation: Arrhythmia & Electrophysiology Review 2020;9(4):175–81. DOI: https://doi.org/10.15420/aer.2020.27 Correspondence: Roberto Keegan, Electrophysiology Service, Hospital Privado del Sur and Hospital Español, 70th Amancay Av, Bahia Blanca, Argentina, B8002GRN. E: robertokeegan@gmail.com Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for noncommercial purposes, provided the original work is cited correctly.

Chagas disease is an important public health problem in Latin America. Almost 25% of the population (approximately 65 million individuals) are at risk of infection and another 6 million people are affected.1 However, migration and globalisation have resulted in the increased presence of Chagas disease worldwide, particularly in the US and Europe.

Sudden cardiac death (SCD) is the leading cause of death in Chagas disease. Although the incidence is unknown, the estimated annual mortality rate is approximately 12,000, with the majority (55–65%) being sudden. Other causes of death in Chagas disease are heart failure (25–30%) and thromboembolic events (10–15%).3–6

Chagas disease is caused by a parasite, the flagellate Trypanosoma cruzi, which is usually transmitted by haematophagous triatominae insects (most commonly Triatoma infestans). The progression of Chagas disease can be categorised into three phases: acute, indeterminate and chronic. The acute phase occurs after the initial transmission or because of reactivation of a chronic infection in an immunosuppressed individual. Patients in the acute phase may range from completely asymptomatic to having a severe presentation (<1%), including fulminant myocarditis or meningoencephalitis. The indeterminate phase of Chagas disease is defined by the presence of infection (by serology) and absence of clinical signs or symptoms. Although most patients with Chagas disease remain in the indeterminate phase for life, 30% progress to the chronic phase several decades later. The chronic phase has several end-organ manifestations, including cardiac (new ECG abnormality or cardiomyopathy), nervous (dysautonomia) and gastrointestinal (megaoesophagus or megacolon). Dilated cardiomyopathy is the one most severe sequelae of chronic Chagas disease.2

SCD in Chagas disease is more common in males and occurs more frequently between the ages of 30 and 50 years.7-9 Although more common in patients with documented ventricular arrhythmias, SCD can also be the first manifestation of Chagas disease in patients with no previous symptoms or known heart failure.

The aim of this review is to provide an update on SCD in Chagas disease, examining predictors and risk stratification along with evidence on the use of drug treatment, catheter ablation, ICDs and pacemakers in people with Chagas disease.

Literature and Sources We conducted a non-systematic review of the literature using the PubMed and SciELO databases and searching for all available references until July 2020. We also searched relevant grey literature from international and governmental organisations, including the Pan American Health Organization and the WHO. Search terms included: Chagas or chagasic; and sudden death or sudden cardiac death;

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Clinical Arrhythmias Table 1: Predictors of Sudden Cardiac Death in Chronic Chagasic Cardiomyopathy • Cardiac arrest • Sustained ventricular tachycardia • Non-sustained ventricular tachycardia on Holter monitoring or exercise stress test (along with left ventricular dysfunction) • Left ventricular dysfunction • Syncope/pre-syncope • Severe bradycardia (sinus node dysfunction or atrioventricular block) • Male sex • Late potentials (signal-averaged ECG) • Myocardial fibrosis (MRI)

Table 2: Rassi’s Score: Risk Factors Risk Factor

Points

NYHA functional class III–IV

Cardiomegaly (chest X-ray)

Global/segmental motility abnormality (echocardiogram)

Non-sustained ventricular tachycardia (Holter monitoring)

Low voltage (ECG)

Male sex

NYHA = New York Heart Association.

ventricular arrhythmia or ventricular arrhythmias; cardiac implantable defibrillator, implantable defibrillator or defibrillator; pacemaker; or catheter ablation. Inclusion criteria encompassed clinical trials, observational studies, case series and reviews. We excluded case reports, opinion papers and editorials. Searches were not restricted by language and the reference lists of selected articles were examined for additional citations. A total of 571 references were screened for the initial analysis of titles and abstracts by two independent investigators (RK and CY) and finally 102 references were considered relevant to be included for the review.

Mechanisms of Sudden Cardiac Death The main accepted mechanism of SCD due to Chagas disease is VF. This is supported by the fact that Chagas disease is an arrhythmogenic condition with a high prevalence of ventricular arrhythmias, the fibrotic nature of the disease with frequent myocardial dyskinesia and/or akinesia and the reentrant mechanism of sustained ventricular tachycardia (VT) induced by programmed ventricular stimulation (PVS).10–19 Less frequently, a bradycardia (sinus node dysfunction or atrioventricular [AV] block) or pulseless electrical activity can be the cause.20 Other mechanisms are possible, such as the spontaneous ventricular rupture of an apical aneurysm.21,22

Risk Stratification SCD in Chagas disease is more common in patients with documented ventricular arrhythmias but can also be the first manifestation in patients with no previous symptoms or known heart failure. However, most authors agree that patients in the indeterminate phase of the disease (positive serological test and normal ECG, chest X-ray and echocardiogram) carry a good prognosis with mortality rates similar to the general population.23–27 The variables identified as predictors of SCD in Chagas disease are shown in Table 1.

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Spontaneous, exercise-induced or PVS-induced VT are major predictors of SCD. The survival of patients with spontaneous VT with no treatment was less than 10% at 8 years follow-up, with more than 70% of deaths occurring during the first 2 years and with 90% of deaths occurring suddenly.4 In a 2-year follow-up study, SCD was found in 16% of 44 patients with exercise-induced VT compared to none of 24 patients with no VT during exercise stress test.28 PVS-induced VT was associated with a survival of 25% at 56 months follow-up in a group of patients with nonsustained VT and mean ejection fraction of 47 ± 18% compared to a survival of 62% in a group of patients with non-inducible VT. Polymorphic VT and VF were not associated with an adverse prognosis.29,30 Non-sustained VT (NSVT), a frequent finding in chronic Chagas cardiomyopathy, is another major risk factor in predicting SCD, particularly when associated with a reduced left ventricular ejection fraction (LVEF).30–32 New York Heart Association (NYHA) functional class and left ventricular dysfunction are also important prognostic variables in chagasic patients. Survival is 97% at the 3-year follow-up for patients in NYHA Class II but only 16% for patients in NYHA Class IV. Likewise, survival at the 3-year follow-up is 100% when the LVEF is >50%, 70% when LVEF is 31–50% and only 16% when the LVEF is ≤30%.33 Recent publications have highlighted that the wall motion score index is a prognostic marker, independent of LVEF.34 Furthermore, in some instances, SCD may occur in patients with exercise-induced VT despite a relatively preserved ejection fraction.28 Pre-syncope and syncope are frequent symptoms in chronic Chagas cardiomyopathy and can be due to bradycardia or tachycardia. NSVT and bradyarrhythmias are frequent on 24-hour Holter monitoring in patients with pre-syncope or syncope (80% and 30%, respectively), and sustained VT can be induced in up to 36% of patients with syncope. Using electrophysiology studies, node dysfunction or abnormalities of the His-Purkinje conduction system were found in 40% of patients with pre-syncope or syncope.30 Complete AV block is also associated with a poor prognosis in Chagas disease. In one study of 147 patients, only 33% with no treatment survived at the 3.6-year follow-up, and most deaths were sudden.20 In 2006, Rassi et al. developed a risk score to predict death in Chagas heart disease.35,36 The Rassi score was developed in 424 patients with Chagas cardiomyopathy and was then validated in a separate cohort of 153 patients.37 In the initial cohort, the mean patient age was 47 years and there was a 31% mortality rate during the 7.9-year mean follow-up. Death was sudden in 62%. Multivariate analysis identified six independent predictors of mortality, and each predictor was assigned a point value (Table 2). The 5- and 10-year mortality for the low-, intermediate- and high-risk categories based on summed total points are presented in Table 3. The C statistic for the point system was 0.84 in the development cohort and 0.81 in the validation cohort.37 Further analysis of these variables demonstrated that the most consistent and strongest predictors of total mortality, SCD, or cardiovascular death were NYHA functional class III or IV, cardiomegaly on chest X-ray, left ventricular dysfunction evaluated by echocardiogram or cardiac ventriculography and NSVT on 24-hour Holter monitoring.35,38–40 More recently, myocardial fibrosis evaluated by cardiac MRI was shown to be a risk predictor of total mortality. In multivariate analysis, fibrosis

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

Sudden Cardiac Death in Chagas Disease (as a continuous variable) was an independent predictor of total mortality (adjusted HR 1.028; 95% CI [1.051–10.0005]; p=0.017). Each gram of additional fibrosis was associated with a 2.8% increase in mortality. In univariate analysis, a mass of 12.3 g or more (as a categorical variable) was an independent predictor of total mortality. However, it was not a predictor in the multivariate analysis.41 In addition to mortality, the presence of scar by late gadolinium enhancement is strongly associated with other major adverse outcomes, such as cardiovascular death, sustained ventricular tachycardia and cardiovascular hospitalisation.42 Moreover, myocardial delayed enhancement by MRI also quantifies myocardial fibrosis that can be detected in the early asymptomatic stages and additionally parallels well-established prognostic factors, including NYHA class, LVEF and left ventricular wall motion abnormalities.43 Furthermore, regardless of ventricular function, the degree of fibrosis seems to correlate with the presence of ventricular arrhythmias.44

Prevention of Sudden Cardiac Death Anti-arrhythmic Drugs Propafenone, disopyramide, mexiletine, sotalol and amiodarone are effective for ventricular arrhythmia control in chronic Chagas cardiomyopathy.45–54 However, these anti-arrhythmic drugs do not reduce mortality in clinical trials.55–57 Unlike Class I anti-arrhythmic drugs, randomised clinical trials and meta-analysis have demonstrated that amiodarone reduces mortality in patients with coronary artery disease or idiopathic dilated cardiomyopathy stratified as high risk due to complex ventricular arrhythmias and/or heart failure.58–65 Although there are no randomised clinical trials on the use of amiodarone in chagasic patients, based on extrapolation of the existing data, some experts suggest amiodarone for the treatment of chagasic patients with complex ventricular arrhythmias, particularly NSVT associated with left ventricular dysfunction.30 Leite et al. studied the effect of amiodarone on patients with chagasic cardiomyopathy and symptomatic VT. Patients were divided into three groups based on baseline electrophysiology studies. Group 1 (n=23) had no sustained VT induced, group 2 (n=45) had only tolerated sustained VT induced and group 3 (n=47) had haemodynamically unstable sustained VT induced. Total mortality at 52 ± 32 months followup was significantly higher in group 3 (69%; 52 ± 10.7 years, LVEF 47 ± 17%) than group 2 (22%; 52 ± 10.6 years, LVEF 49 ± 13%) and group 1 (26%; 53 ± 8.6 years, LVEF 48 ± 13%). Cardiac mortality and SCD were also higher in group 3 compared to groups 1 and 2.66 There are no data on the effect of sotalol on mortality in Chagas cardiomyopathy. In general, heart failure due to Chagas cardiomyopathy is treated with standard pharmacological treatment for heart failure with reduced or mid-range ejection fraction, including beta blockade. Although patients with Chagas cardiomyopathy often have bradycardia that may limit their use, beta-blockers may confer a survival benefit. A subanalysis of the Repetitive Education and Monitoring for ADherence for Heart Failure (REMADHE) prospective trial – in which survival was lower in patients with Chagas heart disease as compared with other aetiologies – when only patients under beta-blockers were considered, the survival of patients with Chagas disease was similar to that of other aetiologies.67

Table 3: Rassi’s Score: Risk Stratification Total Points

Total Mortality

Risk

5 years (%)

10 years (%)

0–6

Low

7–11

Intermediate

12–20

High

The most common localisation of the reentrant circuits is the inferolateral basal aspect of left ventricle.68 Epicardial ablation techniques have been specifically developed to improve results in Chagas cardiomyopathy patients, in whom the reentrant circuit is generally not subendocardial.69 However, the complexity of the substrates in chagasic VT – which are frequently multiple, large and epicardial – has contributed to the relatively low success rate of this technique (approximately 60%).70 Preliminary studies on simultaneous epicardial and endocardial substrate mapping and radiofrequency catheter ablation as first-line treatment for VT and frequent ICD shocks in chronic chagasic cardiomyopathy demonstrated an 83% acute success rate, of which 78% were event-free at an average follow-up period of 10.4 months.71 Moreover, a recently published randomised clinical trial comparing efficacy and safety of endocardial versus endocardial/epicardial ablation in patients with Chagas diseases demonstrated that combining endocardial and epicardial VT catheter ablation significantly increases short- and long-term freedom from all ventricular arrhythmias, without an increase of periprocedural complication rates.72 However, the impact of catheter ablation on mortality in chagasic cardiomyopathy is still yet to be definitively determined.

ICDs Although there are many studies showing the benefit of ICDs on secondary and primary prevention of total mortality and SCD in patients with structural heart disease, controversy persists about the efficacy in Chagas cardiomyopathy.73–80 Despite sudden death being the main cause of death in the population with Chagas disease, patients with ICDs maintain high mortality rates. The major causes of death are progression of heart failure and sudden non-arrhythmogenic death unrelated to ICDs – for example, secondary to stroke.81 Particularly in the context of Chagas cardiomyopathy, the latter is closely associated with thromboembolic events. The distinguishing hallmark of chronic Chagas cardiomyopathy is the left ventricular apical aneurysm, which predisposes not only to VT but also to thrombus formation.82 Furthermore, the progressive inflammation and atrial fibrosis due to persistent Trypanosoma cruzi infection contribute to the anatomical substrate that increases the risk of AF, which in turn, translates to an increased risk of stroke in chagasic patients.83–85 Possible other reasons for this discrepancy include the different proportion of patients on other treatments (angiotensin converting enzyme inhibitors (ACEI), beta-blockers, spironolactone, amiodarone and catheter ablation), as well as differences in device programming employed between studies.86

Catheter Ablation This technique is an alternative for persistent VT or recurrent VT when amiodarone is not tolerated or not effective. VT is inducible during an electrophysiology study in 63–95% of patients with spontaneous VT.16–18

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

Indications for ICD in Chagas cardiomyopathy are based on nonrandomised retrospective observational studies from tertiary centres and by data extrapolation of studies in other cardiomyopathies.26

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Clinical Arrhythmias Table 4: ICDs in Secondary Prevention Study

Men (%)

Age (years)*

LVEF (%)*

Follow-up (months)*

Mortality (annual total, %)

SCD (%)

Cardinalli-Neto et al. 200788

59 ± 11

47 ± 13

63 ± 48

16.6

Di Toro et al. 201195

148

60 ± 9

40 ± 11

12 ± 7

10.2

27 0

116

54 ± 11

42 ± 16

45 ± 32

7.1

Barbosa et al. 201392

59†

37†

22†

12.3

Pavao et al. 201896

111

60 ± 12

41 ± 15

8.4

Gali et al. 201993

56 ± 11

42 ± 12

59 ± 27

4.8

Martinelli et al. 2012

*Values are expressed as mean ± SD, except where indicated otherwise. †Median. LVEF = left ventricular ejection fraction; SCD = sudden cardiac death.

ICDs in Secondary Prevention Although data derived from small, non-randomised and retrospective trials have shown that total annual mortality in chagasic patients with ICDs is low – mainly driven by a reduction of SCD – and is lower than observed in patients treated with only anti-arrhythmic drugs, there is disagreement between investigators about the benefit of ICDs in secondary prevention. Key issues include the range in total mortality rates observed in different studies, in addition to the overlapping of mortality rate between patients receiving only anti-arrhythmic drugs (5.1–11.9%) and those implanted with an ICD (4.8–16.6%; Table 4).30,66,87–94 Cardinalli-Neto et al. found a high annual total mortality (16.6%) in a group of 90 chagasic patients with ICDs (59 ± 11 years and LVEF 47 ± 13%; 28% of patients with no left ventricular dysfunction). SCD represented 7% of all deaths.88 Barbosa et al. showed a total mortality of 12.3% in 65 patients (59 years and LVEF 37%) at 266 days follow-up. SCD accounted for 25% of all deaths.92 Di Toro et al. found an annual total mortality of 10.2% in 148 patients included in a Latin American registry (60.1 ± 9.4 years and LVEF 40.1 ± 11.3%), where most patients (91.9%) had a secondary prevention indication. Age >65 years and LVEF <30% were independent predictors of mortality.95 Martinelli et al. studied a group of 116 chagasic patients with a secondary prevention indication for ICD implantation (54 ± 10.7 years and LVEF 42 ± 16%) and observed a total mortality of 7.1%. No SCD was observed. The low rate of total mortality in this study could be explained by the fact that patients with frequent episodes of VT before ICD implantation and electrical storm were treated with catheter ablation.91 In a retrospective study of 111 patients with ICDs for secondary prevention by Pavao et al. (60 ± 12 years and LVEF 41 ± 15%), the annual mortality rate was 8.4%, mostly due to refractory heart failure or noncardiac causes. SCD only comprised of 10% of deaths. After adjusting for confounders, low LVEF, age and female gender were independently associated with death.96 Gali et al. studied a group of 89 patients (56 ± 11 years and LVEF 42 ± 12%) and did not observe benefit in a subgroup of patients >65 years old with LVEF <35% when a composite end point of total mortality or heart transplant was analysed. The annual risk of this composite end point was 20.4% in this group of patients compared to 1.4% observed in patients <65 years old with LVEF >35%.93 Although a high rate of

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annual appropriate therapies was observed (16%), this variable did not affect the primary end point. The low annual total mortality of 4.8% observed in this study was attributed to differences in alternative treatments, especially high rates of ACEI, beta-blocker and spironolactone use. A recent meta-analysis suggested that an ICD does not reduce total mortality in chagasic patients compared to those treated with only amiodarone.86 Therefore, controversy about the role of an ICD in secondary prevention in chagasic patients still persists, and randomised clinical trials are needed to determine the efficacy in this group of patients.

ICDs in Primary Prevention Although there is some evidence for ICDs in secondary prevention of SCD in Chagas cardiomyopathy, there is not enough evidence to support the indication in primary prevention.97,98 However, available evidence shows that the incidence of malignant ventricular arrhythmias and SCD in chagasic patients is higher than in other cardiomyopathies when similar degrees of left ventricular dysfunction are compared.30,92,99,100 The CHronic use of Amiodarone aGAinSt Implantable cardioverterdefibrillator therapy for primary prevention of death in patients with Chagas cardiomyopathy Study (CHAGASICS) is an on-going randomised, multicentre trial that will compare total mortality at 4.5-year follow-up in patients with a chronic chagasic cardiomyopathy, NSVT and a Rassi Score of 10 or more assigned to receive an ICD or amiodarone.101

Pacemakers In an observational study of 147 chagasic patients with complete AV block and no anti-bradycardia therapy, the survival rates at 1, 5 and 10 years were 70%, 37% and 6%, respectively. On the contrary, in patients implanted with a VVI pacemaker, the survival rates were significantly higher (86%, 57% and 44%, respectively). SCD was observed in 87% of patients who did not receive a pacemaker compared to 67% who did.30 In a prospective cohort study (n=396), chronic Chagas cardiomyopathy patients with pacemakers had a high annual mortality rate (8.6%), despite that pacemaker-related variables were not predictors of death. The most prevalent cause of death was SCD at 34%, followed by heart failure at 32%.102

Discussion Considering SCD as a major cause of death in advanced Chagas cardiomyopathy, many variables have been investigated to predict the risk in patients with no documented sustained ventricular arrhythmias

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

Sudden Cardiac Death in Chagas Disease or less advanced stages of the disease. Clinical variables related to the extent of left ventricular myocardial dysfunction (NYHA class, ECG voltage criteria, cardiomegaly and LVEF) and cardiac arrhythmias (NSVT) have been found to be the most relevant predictors.30–33 Myocardial fibrosis evaluated by MRI is a promising new risk stratification tool that could add accuracy in selecting patients at higher risk of SCD.41 The American Heart Association also recommends cardiac MRI when complex ventricular arrhythmias (especially VT) are present in patients with Chagas cardiomyopathy.26 After identifying a patient at definitive higher risk for SCD, the challenging next step is optimising evidence-based treatment options. Anti-arrhythmic drugs other than amiodarone have no demonstrated benefit in reducing mortality in chagasic patients.55,56 Although there is some evidence that amiodarone reduces mortality in patients with coronary artery disease or idiopathic dilated cardiomyopathy stratified as high risk due to complex ventricular arrhythmias and/or heart failure,58–65 there is no randomised clinical trial supporting its benefit in Chagas cardiomyopathy. Similarly, there is no randomised clinical trial on the efficacy of ICDs in secondary or primary prevention of total mortality and SCD for patients with Chagas cardiomyopathy; controversy about its role in this group of patients still persists. The indications are based on non-randomised retrospective observational studies and by extrapolation of studies in other cardiomyopathies.26 Some experts cite the high rate of appropriate ICD interventions associated with a low rate of SCD as a compelling argument for ICD implantation as standard therapy for the secondary prevention of SCD in patients with Chagas cardiomyopathy. By the same token, some authors therefore extrapolate that a randomised controlled trial comparing ICD versus amiodarone would be imprudent and unethical. However, others have speculated that the deleterious effects of ICD shocks on myocardial tissue could merely change the mode of death from arrhythmia to pump failure.94 The results of on-going clinical trials

WHO. Chagas disease in Latin America: an epidemiological update based on 2010 estimates. Wkly Epidemiol Rec 2015;90:33–43. PMID: 25671846. 2. Marin-Neto JA, Cunha-Neto E, Maciel BC, et al. Pathogenesis of chronic Chagas heart disease. Circulation 2007;115:1109–23. https://doi.org/10.1161/CIRCULATIONAHA.106.624296; PMID: 17339569. 3. de Souza AC, Salles G, Hasslocher-Moreno AM, et al. Development of a risk score to predict sudden death in patients with Chaga’s heart disease. Int J Cardiol 2015;187:700–4. https://doi.org/10.1016/j.ijcard.2015.03.372; PMID: 25919755. 4. Rassi A Jr, Rassi SG, Rassi A. Sudden death in Chagas’ disease. Arq Bras Cardiol 2001;76:75–96. https://doi.org/10.1590/S0066782X2001000100008; PMID: 11175486. 5. Healy C, Viles-Gonzalez JF, Saenz LC, et al. Arrhythmias in chagasic cardiomyopathy. Card Electrophysiol Clin 2015;7:251–68. https://doi.org/10.1016/j.ccep.2015.03.016; PMID: 26002390. 6. Manzullo EC, Chuit R. Risk of death due to chronic chagasic cardiopathy. Mem Inst Oswaldo Cruz 1999;94(Suppl 1):317–20. https://doi.org/10.1590/S0074-02761999000700060; PMID: 10677746. 7. Prata A, Lopes ER, Chapadeiro E. Sudden death. In: Cançado JR, Chuster M, eds. Chagas Disease. Belo Horizonte, Minas Gerais: Fundação Carlos Chagas de Pesquisa Médica, 1985;114–20 [in Portuguese]. 8. de Menezes M, Rocha A, da Silva AC, et al. Basic causes of death in elderly patients with Chagas’ disease. Arquivos Brasileiros de Cardiologia 1989;52:75–8 [in Portuguese]. PMID: 2512897. 9. Bestetti RB, Freitas OC, Muccillo G, et al. Clinical and morphological characteristics associated with sudden cardiac death in patients with Chagas’ disease. Eur Heart J 1993;14:1610–4. https://doi.org/10.1093/eurheartj/14.12.1610; PMID: 7510637. 10. Chiale PA, Halpern MS, Nau GJ, et al. Malignant ventricular arrhythmias in chronic chagasic myocarditis. Pacing Clin

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may shed light on the best treatment strategies for the prevention of SCD in patients with Chagas cardiomyopathy.101 Furthermore, approaches to further reduce ICD shocks through enhanced ICD programming strategies, broader use of amiodarone plus beta-blockers and adjunct radiofrequency catheter ablation may provide additional clinical benefit.

Conclusion SCD is the leading cause of death in Chagas disease. Although more common in patients with documented ventricular arrhythmias, SCD can also be the first manifestation of Chagas disease in patients with no previous symptoms or known heart failure. Given the widespread global burden of Chagas disease, understanding the risk stratification and prevention of SCD in Chagas disease is of timely concern.

Clinical Perspective • Major predictors of SCD in Chagas disease include cardiac arrest, sustained and non-sustained ventricular tachycardia, left ventricular dysfunction, syncope and bradycardia. • Amiodarone may be beneficial for the treatment of chagasic patients with complex ventricular arrhythmias, particularly nonsustained ventricular tachycardia associated with left ventricular dysfunction. • Catheter ablation is an alternative treatment for persistent or recurrent ventricular tachycardia. However, the complexity of the substrates in chagasic ventricular tachycardia results in a relatively low success rate. • Controversy about the role of ICDs for primary and secondary prevention in chagasic patients persists, and randomised clinical trials are currently being conducted to determine the efficacy in this group of patients.

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Kadish A, Dyer A, Daubert JP, et al. Prophylactic defibrillator implantation in patients with nonischemic dilated cardiomyopathy. N Engl J Med 2004;350:2151–8. https://doi. org/10.1056/NEJMoa033088; PMID: 15152060. 79. Bardy GH, Lee KL, Mark DB, et al. Amiodarone or an implantable cardioverter-defibrillator for congestive heart failure. N Engl J Med 2005;352:225–37. https://doi.org/10.1056/ NEJMoa043399; PMID: 15659722. 80. da Matta JA, Aras R Jr, de Macedo CR, et al. Stroke correlates in chagasic and non-chagasic cardiomyopathies. PLoS One 2012;7:e35116. https://doi.org/10.1371/journal.pone.0035116; PMID: 22523572. 81. Nunes MC, Kreuser LJ, Ribeiro AL, et al. Prevalence and risk factors of embolic cerebrovascular events associated with Chagas heart disease. Glob Heart 2015;10:151–7. https://doi. org/10.1016/j.gheart.2015.07.006; PMID: 26407510. 82. Enriquez A, Conde D, Femenia F, et al. Relation of interatrial block to new-onset atrial fibrillation in patients with Chagas cardiomyopathy and implantable cardioverter-defibrillators. Am J Cardiol 2014;113:1740–3. https://doi.org/10.1016/j. amjcard.2014.02.036; PMID: 24698463. 83. Carod-Artal FJ, Vargas AP, Horan TA, et al. Chagasic cardiomyopathy is independently associated with ischemic stroke in Chagas disease. Stroke 2005;36:965–70. https://doi. org/10.1161/01.STR.0000163104.92943.50; PMID: 15845889. 84. Paixao LC, Ribeiro AL, Valacio RA, et al. Chagas disease: independent risk factor for stroke. Stroke 2009;40:3691–4. https://doi.org/10.1161/STROKEAHA.109.560854; PMID: 19834017. 85. Carmo AAL, de Sousa MR, Agudelo JF, et al. Implantable cardioverter-defibrillator in Chagas heart disease: A systematic review and meta-analysis of observational studies. Int J Cardiol 2018;267:88–93. https://doi.org/10.1016/j.ijcard.2018.05.091; PMID: 29871807. 86. Scanavacca MI, Sosa EA, Lee JH, et al. Empiric therapy with amiodarone in patients with chronic Chagas cardiomyopathy and sustained ventricular tachycardia. Arq Bras Cadiol 1990;54:367–71 [in Portugese]. PMID: 2288524. 87. Cardinalli-Neto A, Bestetti RB, Cordeiro JA, et al. Predictors of all-cause mortality for patients with chronic Chagas’ heart disease receiving implantable cardioverter defibrillator therapy. J Cardiovasc Elecrophysiol 2007;18:1236–40. https://doi.org/10.1111/j.1540-8167.2007.00954.x; PMID: 17900257. 88. Muratore CA, Batista Sa LA, Chiale PA, et al. Implantable cardioverter defibrillators and Chagas’ disease: results of the ICD Registry Latin America. Europace 2009;11:164–8. https:// doi.org/10.1093/europace/eun325; PMID: 19056745. 89. Sarabanda AV, Marin-Neto JA. Predictors of mortality in patients with Chagas’ cardiomyopathy and ventricular tachycardia not treated with implantable cardioverterdefibrillators. Pacing Clin Electrophysiol 2011;34:54–62. https:// doi.org/10.1111/j.1540-8159.2010.02896.x; PMID: 20946310. 90. Martinelli M, de Siqueira SF, Sternick EB, et al. Long-term follow-up of implantable cardioverter-defibrillator for secondary prevention in Chagas’ heart disease. Am J Cardiol 2012;110:1040–5. https://doi.org/10.1016/j. amjcard.2012.05.040; PMID: 22727179. 91. Barbosa MP, da Costa Rocha MO, de Oliveira AB, et al. Efficacy and safety of implantable cardioverter-

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Sudden Cardiac Death in Chagas Disease defibrillators in patients with Chagas disease. Europace 2013;15:957–62. https://doi.org/10.1093/europace/eut011; PMID: 23376978. 92. Gali WL, Sarabanda AV, Baggio JM, et al. Predictors of mortality and heart transplantation in patients with Chagas’ cardiomyopathy and ventricular tachycardia treated with implantable cardioverter-defibrillators. Europace 2019;21:1070–78. https://doi.org/10.1093/europace/euz012; PMID: 30820579. 93. Rassi FM, Minohara L, Rassi A Jr, et al. Systematic review and meta-analysis of clinical outcome after implantable cardioverter-defibrillator therapy in patients with Chagas heart disease. JACC Clin Electrophysiol 2019;5:1213–23. https://doi. org/10.1016/j.jacep.2019.07.003; PMID: 31648747. 94. di Toro D, Muratore C, Aguinaga L, et al. Predictors of all-cause 1-year mortality in implantable cardioverter defibrillator patients with chronic Chagas’ cardiomyopathy. Pacing Clin

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95.

96.

97.

98.

Electrophysiol 2011;34:1063–9. https://doi.org/10.1111/ j.1540-8159.2011.03108.x; PMID: 21535031. Pavao M, Arfelli E, Scorzoni-Filho A, et al. Long-term follow-up of Chagas heart disease patients receiving an implantable cardioverter-defibrillator for secondary prevention. Pacing Clin Electrophysiol 2018;41:583–8. https://doi.org/10.1111/ pace.13333; PMID: 29578582. Mitelman J, Descalzo A, Gimenez L, et al. Consensus statement on Chagas-Mazza disease. Rev Argent Cardiol 2011;79:544-64. Andrade JP, Marin Neto JA, Paola AA, et al. I Latin American Guidelines for the diagnosis and treatment of Chagas’ heart disease: executive summary. Arq Bras Cardiol 2011;96:434–42 [in Portugese, Spanish]. https://doi.org/10.1590/S0066-782X2011000600002; PMID: 21789345. Barbosa MP, Rocha MO, Lombardi F, et al. ICDs in Chagas heart

disease: the standard treatment for secondary prevention of sudden death. Europace 2013;15:1383–4. https://doi. org/10.1093/europace/eut123; PMID: 23696626. 99. Barbosa MP, Carmo AA, Rocha MO, et al. Ventricular arrhythmias in Chagas disease. Rev Soc Bras Med Trop 2015;48:4–10. https://doi.org/10.1590/0037-8682-0003-2014; PMID: 25714933. 100. Martinelli M, Rassi A, Jr, Marin-Neto JA, et al. CHronic use of Amiodarone aGAinSt Implantable cardioverter-defibrillator therapy for primary prevention of death in patients with Chagas cardiomyopathy Study: rationale and design of a randomized clinical trial. Am Heart J 2013;166:976–82.e4. https://doi.org/10.1016/j.ahj.2013.08.027; PMID: 24268211. 101. Peixoto GL, Martinelli Filho M, Siqueira SF, et al. Predictors of death in chronic Chagas cardiomyopathy patients with pacemaker. Int J Cardiol 2018;250:260–5. https://doi. org/10.1016/j.ijcard.2017.10.031; PMID: 29079412.

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Clinical Arrhythmias

Management of Cardiac Sarcoidosis in 2020 Nisha Gilotra, David Okada, Apurva Sharma and Jonathan Chrispin Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, US

Abstract Sarcoidosis is an inflammatory granulomatous disease that can affect any organ. Up to one-quarter of patients with systemic sarcoidosis may have evidence of cardiac involvement. The clinical manifestations of cardiac sarcoidosis (CS) include heart block, atrial arrhythmias, ventricular arrhythmias and heart failure. The diagnosis of CS can be challenging given the patchy infiltration of the myocardium but, with the increased availability of advanced cardiac imaging, more cases of CS are being identified. Immunosuppression with corticosteroids remains the standard therapy for the acute inflammatory phase of CS, but there is an evolving role of steroid-sparing agents. In this article, the authors provide an update on the diagnosis of CS, including the role of imaging; review the clinical manifestations of CS, namely heart block, atrial and ventricular arrhythmias and heart failure; discuss updated management strategies, including immunosuppression, electrophysiological and heart failure therapies; and identify the current gaps in knowledge and future directions for cardiac sarcoidosis.

Keywords Sarcoid, cardiac sarcoid, heart failure, arrhythmias, immunosuppression Disclosure: JC is the recipient of the Robert E Meyerhoff Professorship. All other authors have no conflicts of interest to declare. Received: 13 March 2020 Accepted: 16 September 2020 Citation: Arrhythmia & Electrophysiology Review 2020;9(4):182–8. DOI: https://doi.org/10.15420/aer.2020.09 Correspondence: Jonathan Chrispin, Johns Hopkins University School of Medicine, Division of Cardiology, 600 N Wolfe St/Carnegie 592B, Baltimore, MD 21287, US. E: Chrispin@jhmi.edu Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for noncommercial purposes, provided the original work is cited correctly.

Sarcoidosis is an inflammatory granulomatous disease that can affect any organ. Systemic sarcoidosis is known to affect young adults, with a second peak in women >50 years of age, as demonstrated in Scandinavian and Japanese studies.1–4 In the US, the lifetime risk of sarcoidosis is 2.4% for black people and 0.85% for white people.1 The incidence of cardiac involvement has been increasingly recognised, with one large 25-year Finnish cohort study reporting an exponential increase from 1988 to 2012, with a prevalence of 2.2 per 100,000 adults.2 Among patients with systemic sarcoidosis, an estimated 5% will have clinically manifest cardiac sarcoidosis (CS), whereas more than 25% may have evidence of cardiac involvement on autopsy or imaging studies.1,5 The diagnosis of CS can be challenging given the low sensitivity of endomyocardial biopsy. However, advanced cardiac imaging techniques permit non-invasive detection of cardiac involvement. Accordingly, current guidelines provide both histological and clinical pathways for diagnosis, and emphasise the important role of cardiac imaging.6 The diagnosis of cardiac involvement in sarcoidosis has important clinical and prognostic ramifications, including an increased risk of heart failure, ventricular arrhythmias (VAs) and sudden death. Optimal management strategies of patients with CS are evolving as the evidence base expands. Immunosuppression remains the mainstay of therapy, and corticosteroids are often the initial treatment of choice. However, steroid-sparing agents have emerged as an important adjunctive treatment in an effort to decrease the long-term side effects related to corticosteroid therapy. Furthermore, many studies have

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refined our understanding of which patients are at increased risk for developing VAs and may benefit from device-based therapy.7 In this review, we provide an update on the diagnostic criteria for CS, discuss the utility of imaging modalities in the diagnosis and monitoring of CS and review current management strategies for the cardinal clinical manifestations of CS, namely conduction disease, arrhythmia and cardiomyopathy.

Diagnosis of Cardiac Sarcoidosis Despite multiple existing guidelines and diagnostic criteria for CS, the largest current limitation is the emphasis on a tissue diagnosis. Histopathological examination of the myocardium involved by sarcoidosis reveals non-caseating granulomas, multinucleated giant cells and asteroid bodies (Figure 1). Eosinophils and myocyte necrosis are rare and can help distinguish CS from other causes of inflammation, such as giant cell myocarditis. In certain presentations of cardiomyopathy, endomyocardial biopsy is indicated for diagnosis, but the role of biopsy is limited in CS due to low sensitivity, which may be due to the patchy nature of the disease.8 In cases where biopsy is pursued, guidance with electroanatomical voltage mapping may increase the diagnostic yield.9 In patients with a clinical diagnosis of CS, a positive endomyocardial biopsy is known to be a poor prognostic indicator.10 One of the initial guidelines for the diagnosis of CS was developed by the Japanese Ministry of Health and Welfare (JMHW) in 1993 and later revised in 2007.11,12 These guidelines included characteristic clinical

Management of Cardiac Sarcoid manifestations as major criteria and late gadolinium enhancement cardiac MRI (LGE-CMR) and perfusion defect on nuclear imaging as minor criteria. However, these guidelines did not include abnormal PET imaging as a criterion.11,12 Furthermore, it has been suggested that advanced imaging techniques may have a higher sensitivity for CS diagnosis compared with the modified JMHW criteria.13,14

Figure 1: Haematoxylin and Eosin Staining of Native Explanted Heart Tissue of a Patient Undergoing Heart Transplantation

The World Association of Sarcoidosis and Other Granulomatous Disorders (WASOG) provided an alternative approach to diagnosis based on the results of a detailed survey completed by sarcoidosis experts.15,16 The WASOG Sarcoidosis Organ Assessment Instrument established whether specific pathological, laboratory, clinical and imaging criteria supported a highly probable, probable or possible diagnosis of CS, where the experts voted using Delphi study methodology and consensus was achieved with ≥70% agreement.15 In this diagnostic approach, a ≥90% likelihood of CS matched a highly probable diagnosis of CS, a ≥50% likelihood matched a probable diagnosis and a <50% likelihood matched a possible diagnosis. The Heart Rhythm Society (HRS) published an expert consensus statement in association with the American College of Chest Physicians, American Heart Association, Asia Pacific Heart Rhythm Society, European Heart Rhythm Association and WASOG in 2014.6 The HRS guidelines recognised both histological (definite) and clinical (probable) pathways for the diagnosis of CS. Importantly, these guidelines included abnormal PET or CT as a diagnostic criterion. However, both abnormal PET/CT and abnormal LGE-CMR were still considered minor, rather than major, criteria. This made the diagnosis of isolated CS challenging in cases where endomyocardial biopsy was not feasible or was negative. Not until recently has there been a movement to diagnose CS without histopathological confirmation. These efforts were supported by the recently published Japanese Circulation Society guidelines, which include a clinical diagnosis pathway using abnormal PET or CT and LGECMR as major criteria for CS diagnosis.17 Furthermore, these guidelines outline a specific pathway for the clinical diagnosis of isolated CS in cases where endomyocardial biopsy is not available.17 This recent shift in diagnostic practice will have future implications on disease definition when deciding on treatment strategies or inclusion in research studies.

Imaging Various imaging modalities play a role in the diagnosis and monitoring of cardiac involvement in sarcoidosis. In addition to more traditional echocardiography and MRI, the greatest advancement has been in nuclear imaging, with a shift away from gallium scans to the use of cardiac PET.

Echocardiography Although echocardiography has limited sensitivity and specificity for the diagnosis of CS, it is often the initial imaging study acquired in the evaluation of patients with suspected cardiomyopathy. Echocardiographic findings that may support the diagnosis of CS include ventricular hypertrophy, diastolic dysfunction or restrictive filling pattern, and systolic dysfunction of either the left ventricle (LV) or right ventricle with non-coronary distribution wall motion abnormalities and aneurysms.18,19 The more recently developed speckle tracking echocardiography has allowed measurement of global longitudinal strain (GLS) in CS. As in other cardiomyopathies, GLS may have both diagnostic and prognostic utility in CS, and is independently associated with poorer clinical outcomes in patients with CS.20,21

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The image shows inflammatory infiltrate, non-necrotising granuloma and a multinucleated giant cell consistent with cardiac sarcoidosis.

Cardiac PET 18

F-Fluorodeoxyglucose (FDG) is a glucose analogue taken up by macrophages.22 Cardiac PET using 18F-FDG has emerged as a cornerstone in the clinical diagnosis, prognostic evaluation and monitoring of therapy in patients with CS. Several patterns of 18F-FDG uptake have been described in CS, namely focal uptake and focal-ondiffuse uptake.23,24 Diffuse uptake is often interpreted to represent poor suppression of normal myocardial glucose uptake. Metabolic imaging is often performed in conjunction with perfusion imaging. In these cases, the classic pattern demonstrated in CS is one of ‘perfusion–metabolism’ mismatch, in which areas of 18F-FDG uptake correspond to areas of reduced or absent perfusion.23 FDG-PET/CT has a fair diagnostic accuracy for CS, with a recent meta-analysis reporting a pooled sensitivity of 89% and specificity of 78%.25 FDG-PET/CT may also be complementary to LGE-CMR in the diagnosis of CS.24 Abnormal FDG uptake is also important for prognosis and is associated with increased rates of VAs and death, especially when located in the right ventricle.14 Finally, serial PET imaging is useful in monitoring disease activity and response to immunosuppressive therapy.23,26

Cardiac MRI LGE-CMR plays an important role in the diagnosis of CS and risk stratification of patients with CS. The main strength of LGE-CMR is its early detection and high sensitivity.27 Patel et al. demonstrated a higher sensitivity of LGE-CMR that that of the JMHW criteria.13 Although the presence of LGE may be a non-specific finding in the evaluation of non-ischemic cardiomyopathy, multifocal distribution, high signal intensity and contiguous extension from the left to the right ventricle may increase the specificity of this finding for the diagnosis of CS (Figure 2).24 Many studies have also demonstrated the prognostic utility of LGE-CMR in patients with CS.28–30 A meta-analysis by Coleman et al. including 760 patients with known or suspected CS demonstrated that the presence of LGE is associated with an odds ratio of 10 for the composite endpoint of VAs and all-cause mortality.31 Hybrid CMR-PET imaging has also been proposed as a future tool in CS, because studies have shown incremental value to this approach in determining disease activity and pattern.32

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Clinical Arrhythmias Figure 2: Cardiac MRI with Late Gadolinium in Patients With Cardiac Sarcoid

Treatment of atrial arrhythmias in the setting of CS has been limited to case reports. Although immunosuppression remains the cornerstone for treatment of inflammation, to date there are no specific guidelines on the role of anti-arrhythmic therapy and catheter ablation in patients with CS. It is generally agreed that class I anti-arrhythmics should be avoided, whereas beta-blockers, calcium channel blockers and drugs that block potassium currents (e.g. sotalol, dofetilide and amiodarone) are acceptable choices.6

Ventricular Arrhythmias Different patterns exist (yellow arrows), including A: transmural, B: focal and C: diffuse mid-myocardial delayed enhancement.

Figure 3: 18F-Fluorodeoxyglucose PET Imaging

A: Axial and B: coronal PET images show 18F-fluorodeoxyglucose uptake in the atrium (yellow arrows) in a patient with AF.

Clinical Manifestations When involving the heart, sarcoidosis classically presents with atrioventricular (AV) conduction disease, arrhythmia and cardiomyopathy causing heart failure. Less commonly, CS may manifest as pericardial, valvular or coronary disease.

Heart Block AV nodal disease is a common mode of presentation among patients with CS. In a series of 110 Finnish patients with histologically confirmed CS, 48 (45%) presented with AV nodal disease, 35 (32%) of whom had third-degree AV block requiring permanent pacemaker implantation.2 Among patients with CS who present with other initial clinical manifestations, there are no known predictors for the development of AV nodal disease; however, LGE in the basal anteroseptal region on CMR may portend increased risk for AV nodal disease.33 Treatment includes corticosteroids and device therapy, both of which are discussed below.

Atrial Arrhythmias Atrial arrhythmias are common in CS. Hypotheses as to the mechanism of atrial arrhythmias include triggered activity from active inflammation to re-entry secondary to scar formation (Figure 3). In a study of 100 patients with CS, supraventricular arrhythmias were detected in 32% based on ambulatory ECG and cardiovascular implantable electronic device monitoring, with the most prevalent atrial arrhythmia being AF in 18% of all patients studied.34 Cain et al. performed a CMR study in which 36% of patients with ventricular myocardial LGE had documented atrial arrhythmias.35 CS is known to infiltrate the atrium, based on a 1977 clinicopathological study in which five of the 26 hearts studied had sarcoidosis granulomas in the right or left atrium.36 In that series, four had documented atrial arrhythmias.36 In a similar study performed by Tavora et al., the prevalence of atrial involvement of granulomas was lower at 3.7%.37

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Patients with CS are at increased risk of ventricular tachycardia (VT) and sudden cardiac death (SCD), although the precise incidence of VAs in CS is not well defined.7 Kandolin et al. observed that, among 18 patients presenting with AV nodal disease and ultimately diagnosed with CS, 10 went on to develop VA during a mean follow-up of 48 months.38 In a much larger study, Nordenswan et al. observed that among 143 patients with CS and Mobitz II second-degree heart block or complete heart block, 42 developed VT or SCD during a median follow-up of 2.8 years.39 Importantly, even patients with CS and preserved LV systolic function are at increased risk of VA.14,39 Among the 90 patients with preserved LV ejection fraction (LVEF) in the study of Nordenswan et al., the 5-year incidence of subsequent SCD or VT was 24%.39 Although VT is generally monomorphic in CS, polymorphic VT has also been described.40 Myocardial scar resulting from granulomatous inflammation is thought to be the dominant substrate for VT in patients with CS; however, the role of active inflammation in arrhythmogenesis has not been well characterised and may be an important therapeutic target in patients presenting with VT.41â&#x20AC;&#x201C;43 Circuits supporting re-entrant VT may localise to either ventricle, and to any myocardial depth (i.e. subepicardial, mid-myocardial, subendocardial or transmural).41 Finally, the Hisâ&#x20AC;&#x201C;Purkinje system may be an important component of the arrhythmogenic substrate in some patients with CS.42 Risk stratification for SCD may be challenging in CS. Non-invasive strategies include LGE on CMR and abnormal 18F-FDG uptake on cardiac PET. As mentioned above, in a meta-analysis including 10 studies and 760 patients with CS undergoing CMR, those with LGE on CMR had a 10-fold increased risk of the combined endpoint of VA or all-cause mortality over a mean follow-up of 3 years.31 Among those with LVEF >50%, the presence of LGE conferred a 19-fold increased risk of the combined endpoint.31 Blankstein et al. studied 118 patients with suspected CS, among whom the presence of abnormal 18F-FDG uptake corresponded to an approximately fourfold increased risk of VT or death over a median follow-up of 1.5 years.14 The role of invasive risk stratification with programmed electrical stimulation (PES) has been assessed in several analyses (Figure 4). Among 25 patients with CS undergoing PES at the Johns Hopkins University School of Medicine, 10 had inducible VA, all of whom had clinical VA events during a mean follow-up of 5 years, whereas 15 had no inducible VA, only one of whom went on to have clinical VA.44 In a larger study, Mehta et al. observed that six of the eight patients who had inducible VA on PES had clinical VA events over a mean follow-up of 5 years, whereas only one of the 69 who had no inducible VA went on to have clinical VA.45 Electrophysiological studies for the purpose of arrhythmic risk stratification in patients with CS and LVEF >35% is a Class IIb recommendation in the current guidelines.6

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Management of Cardiac Sarcoid Figure 4: Late Gadolinium Enhancement on Cardiac MRI and Electrophysiological Testing

A: Late gadolinium enhancement on cardiac MRI shows substantial enhancement involving the ventricular septum (yellow arrow). B: On electrophysiological testing, the patient exhibited easily inducible monomorphic ventricular tachycardia.

The treatment of VA in CS includes medical therapy in the form of both anti-arrhythmic drugs and immunosuppression, device therapy in the form of secondary prevention ICD and catheter ablation. These are discussed separately below in the â&#x20AC;&#x2DC;Managementâ&#x20AC;&#x2122; section.

Heart Failure Sarcoidosis is gaining increasing recognition as an aetiology for nonischemic cardiomyopathy, particularly with advancements in cardiac imaging. Depending on the cohort studies, approximately 50% of patients with CS have cardiomyopathy.46 Granulomatous inflammation and subsequent scarring can result in both systolic ventricular dysfunction and diastolic dysfunction and a restrictive physiology similar to other infiltrative cardiomyopathies. Sarcoidosis can also involve either ventricle, and may be a cause for isolated right ventricular dysfunction.47 CS requires distinction from other cardiomyopathies, which can have overlap in presentation. For example, arrhythmogenic right ventricular cardiomyopathy (ARVC) also presents in relatively young patients with VA and right ventricular dysfunction, and patients with sarcoidosis may meet Task Force Criteria for ARVC.48 However, management is significantly different for ARVC and CS. Patients with CS can also present like patients with giant cell myocarditis, a lethal form of myocarditis characterised by acute cardiac failure, VA and conduction disease that is diagnosed on endomyocardial biopsy and treated with immunosuppressive therapy, but often requires mechanical support and heart transplantation. Compared with patients with dilated cardiomyopathy, patients with CS-related cardiomyopathy have been noted to more likely be women and have AV block, LV hypertrophy and focal LV wall involvement.49 These patients have poorer prognosis than those with other dilated cardiomyopathies.49 In addition, when manifesting with isolated CS, patients are more likely to present with LV systolic dysfunction than patients who also have extracardiac disease. In the cohort of Kandolin et al., 69% of those with isolated CS had LV systolic dysfunction on presentation, compared with 41% of those with both extracardiac and CS.39 The presence of heart failure has implications on survival among patients with CS, as demonstrated in several retrospective cohorts. In the Finnish cohort, 10-year transplantation-free cardiac survival was only 53% among those presenting with heart failure, whereas the overall

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cohort survival was 83%.1 In a more recent multicentre analysis, Fussner et al. described a cohort of 91 patients with CS, of which 47 (52%) had a primary presentation of cardiomyopathy.46 Those with cardiomyopathy had a significantly lower survival free of LV assist device (LVAD) placement, heart transplantation or death.46 Among patients with sarcoidosis-related cardiomyopathy, independent predictors of mortality include worse New York Heart Association functional class, larger LV diastolic dimension, lower LVEF and the concomitant presence of sustained VT.39,50 In addition, right ventricular involvement, particularly on FDG-PET scans, is predictive of poorer survival.14

Management Immunosuppression The mainstay of medical therapy for CS, as with other organ involvement, is immunosuppression, namely in the form of corticosteroids (Figure 5). In addition, a number of different steroid-sparing agents may be used to avoid untoward side-effects of chronic corticosteroid use. Data on immunosuppressive management of CS is largely extrapolated from non-cardiac sarcoidosis literature and from limited retrospective cohorts of CS patients.51 Consensus guidelines and prospective randomised studies are lacking. Therefore, ambiguity and clinical practice variation exist in the treatment of CS. Immunosuppressive regimens are generally tailored towards response to treatment, assessed both by clinical events and imaging. In an attempt to further elucidate the role and efficacy of corticosteroids in CS, Sadek et al. performed a meta-analysis of 10 studies comprising a total of 257 patients with CS who received corticosteroids and 42 who did not.51 That meta-analysis was limited by fair-quality studies that were mostly small, single-centre retrospective cohorts, and thus limited any significant conclusions regarding the efficacy of corticosteroids. Although randomised data are lacking, corticosteroid therapy is thought to play an important role in the treatment of AV nodal disease in CS. Among the 35 patients with third-degree AV block in the series of Kandolin et al., seven recovered AV conduction after the initiation of corticosteroids.2 In the meta-analysis of 10 studies assessing the utility of corticosteroids in CS by Sadek et al., 27 of 57 patients with AV nodal disease treated with corticosteroids showed clinical improvement, whereas none of the 16 patients with AV nodal disease not treated with corticosteroids showed clinical improvement.51

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Clinical Arrhythmias Figure 5: 18F-Fluorodeoxyglucose PET Imaging

18 F-Fluorodeoxyglucose -PET imaging showed A: significant inflammation involving the left and right ventricles and B: resolution of inflammation with corticosteroid therapy.

Observational data support the use of corticosteroids in the treatment of VA in patients with CS and evidence of active inflammation.43 In that study, Yalagudri et al. studied 18 patients presenting with VT who were ultimately diagnosed with CS. All patients underwent FDG-PET examination, with 14 demonstrating abnormal myocardial FDG uptake. Among these, nine were successfully treated with a combination of prednisolone and methotrexate and did not require chronic maintenance with antiarrhythmic drugs, whereas five required either intensification of immunosuppression or radiofrequency ablation.43 The data on LVEF responses to prednisone are mixed, with some studies suggesting those with severely depressed LVEF tend to improve more and others reporting the opposite.2,46,51 However, the efficacy of steroids in suppression of FDG uptake, and the resulting association with clinical improvement, has been demonstrated in small series.52–54 The dosing and duration of prednisone treatment for CS varies widely. In a retrospective analysis by Yazaki et al. of 95 Japanese patients, 75 of whom received prednisone, survival was similar among those who received ≤30 and >30 mg prednisone.50 Our group recently described a cohort of 32 patients with CS undergoing serial FDG-PET and treatment with corticosteroids.53 There was a significant reduction in cardiac inflammation measured by maximum standard uptake value and the number of LV segments involved after steroid treatment, but results were similar for patients who received high (≥40 mg) and low (<40 mg) doses of prednisone upfront.53 In the context of limited available data, the general approach to treatment of CS includes early initiation of prednisone at 30–40 mg/ day, with subsequent monitoring and tapering as tolerated. If the decision to discontinue treatment is made, patients should be monitored closely due to the risk of clinical worsening after discontinuation.55 Steroid-sparing agents used most commonly include mycophenolate mofetil, methotrexate and azathioprine.46,52 Biological agents, such as tumour necrosis factor alpha inhibitors, may be reserved for refractory disease.56–58 Given the current limitations, there has been a call for randomised clinical trials to address gaps in knowledge regarding the treatment of CS. The Cardiac Sarcoidosis Multi-Center Randomized Controlled Trial (CHASM CS– RCT) is the first of its kind and is currently evaluating low- versus standard-dose prednisone in combination with methotrexate.59

Cardiac Medications In addition to immunosuppression, patients with CS should be treated with guideline-directed medical therapies (GDMT) for electrophysiological and heart failure manifestations. In the setting of reduced LV systolic function, treatment with heart failure GDMT is

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typically initiated and includes beta-blockers and renin–angiotensin system blockade with angiotensin-converting enzyme inhibitors, angiotensin receptor blockers or a neprilysin inhibitor–angiotensin receptor combination (sacubitril/valsartan).60 For symptomatic patients, the addition of a mineralocorticoid receptor antagonist is indicated. Diuretics are used for symptomatic management of volume overload. Data are lacking on outcomes related to the use of heart failure GDMT specifically in CS; however, the benefit of such therapy is extrapolated from existing, well-established data in patients with reduced LVEF.61,62 Similarly, although often used as adjunctive therapy to ICDs and catheter ablation, there are limited and inconclusive data regarding the use of anti-arrhythmic drugs in the management of patients with CS and VA.51 Class I anti-arrhythmics should be avoided in the setting of myocardial scar and structural heart disease. Thus, class III antiarrhythmics, such as sotalol, dofetilide and amiodarone, are preferred for the management of atrial and ventricular arrhythmias.

Device Therapy Device therapy with permanent pacemakers and/or ICDs is an essential component of the therapeutic approach to patients with CS and arrhythmic events. In general, indications for pacemaker implantation among patients with CS mirror those applying to patients with bradyarrhythmias.6 Implantation of a permanent pacemaker is the definitive treatment for AV nodal disease in CS, and may be appropriate even in cases of transiently recovered AV conduction. Among patients with CS presenting with a VA event, secondary prevention ICD implantation is warranted, whereas among patients with CS and LVEF <35% despite optimally tolerated GDMT, primary prevention ICD implantation is warranted. The utility of primary prevention devices among patients with CS and mid-range or preserved LVEF is less straightforward. Although PES for risk stratification is supported only with Class IIb guideline recommendations, in patients with inducible VA the placement of a primary prevention ICD carries a Class IIa recommendation.6 Finally, in patients with CS and AV nodal disease, there are Class IIa guidelines for implantation of a primary prevention ICD rather than a pacing system alone, even in patients with preserved LVEF.6 Indeed, available data support this recommendation and suggest a high rate of subsequent SCD among patients with CS who initially present with AV nodal disease, as discussed above.39 Among patients with depressed LVEF needing a high burden of pacing, or with heart failure with a left bundle branch block, chronic resynchronisation therapy is warranted and has been shown to be as efficacious in patients with CS as in patients with other non-ischemic cardiomyopathies.63 The risks associated with device implantation in patients with CS may exceed those in the broader population. Kron et al. studied 235 patients with CS and primary or secondary prevention ICDs.64 The overall rate of inappropriate tachytherapies was 24%. In all, 41 patients experienced 46 other adverse events, including seven device-related infections and 25 lead dislodgements or fractures.64 Although there is no definitive evidence to suggest a higher rate of device-related infections among patients with CS, given frequent concomitant treatment with immunosuppressive agents, heightened alertness for possible devicerelated infections may be reasonable. Indeed, in the study by Kron et al., among six patients with device-related infections, five were being treated with immunosuppression and two of the infections involved epicardial systems.64

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Management of Cardiac Sarcoid Catheter Ablation Depending on the substrate (i.e. scar or inflammation mediated), catheter ablation may be an effective component of the therapeutic approach in patients with CS and VA.7 The efficacy of catheter ablation in patients with CS and VA has not been assessed in a randomised manner, but is reported to range from 25% to 56% if complete absence of recurrent VA is the endpoint.41,43,65–69 For this reason, catheter ablation is recommended only in cases of VA refractory to antiarrhythmic drugs and immunosuppression, with Level IIa strength.6

Advanced Heart Failure Therapies Despite immunosuppression and heart failure GDMT, a significant proportion of patients will not recover LV function or may have a decline in LVEF over time.46 In patients who develop refractory heart failure or VA, the primary drivers of mortality in this cohort, advanced heart failure therapies, such as mechanical circulatory support or heart transplantation, may be considered. When evaluating patient candidacy for advanced heart failure therapies, there are a few special considerations specific to the CS population. The extent of extracardiac organ involvement should be thoroughly assessed to ensure longevity after heart transplantation and safety of undergoing cardiac surgery. With regard to LVAD evaluation, right ventricular involvement should be assessed by imaging and using guideline-directed haemodynamic assessments in order to determine the risk of right ventricular failure after LVAD placement.70 CS patients presenting primarily with refractory VA may benefit from a direct transplant approach, because LVAD placement may contribute to further scar and arrhythmic nidus formation. Notably, a subset of patients may go unrecognised and only attain a diagnosis of sarcoidosis after examination native heart tissue at the time of LVAD placement or transplantation.71,72 Analyses from the United Network for Organ Sharing (UNOS) have demonstrated similar or better post-transplant survival outcomes for patients undergoing transplant for CS compared with other cardiomyopathies.73,74 In addition, among those undergoing mechanical circulatory support as a bridge to transplantation, survival was similar in those with and without CS.74 There is some theoretical risk of sarcoidosis recurrence in the transplanted heart, but in published case reports this is typically in the setting of weaning off corticosteroids.75,76 More contemporary single-centre case series of cardiac transplantation in CS have reported no recurrence of CS in the allograft.72,77 After transplantation, the general approach is to maintain indefinite low-

Statement on sarcoidosis. Joint Statement of the American Thoracic Society (ATS), the European Respiratory Society (ERS) and the World Association of Sarcoidosis and Other Granulomatous Disorders (WASOG) adopted by the ATS Board of Directors and by the ERS Executive Committee, February 1999. Am J Respir Crit Care Med 1999;160:736–55. https://doi. org/10.1164/ajrccm.160.2.ats4-99; PMID: 10430755. Kandolin R, Lehtonen J, Airaksinen J, et al. Cardiac sarcoidosis: epidemiology, characteristics, and outcome over 25 years in a nationwide study. Circulation 2015;131:624–32. https://doi. org/10.1161/CIRCULATIONAHA.114.011522; PMID: 25527698. Milman N, Selroos O. Pulmonary sarcoidosis in the Nordic countries 1950–1982. Epidemiology and clinical picture. Sarcoidosis 1990;7:50–7. PMID: 2345819. Iwai K, Sekiguti M, Hosoda Y, et al. Racial difference in cardiac sarcoidosis incidence observed at autopsy. Sarcoidosis 1994;11:26–31. PMID: 8036339. Silverman KJ, Hutchins GM, Bulkley BH. Cardiac sarcoid: a clinicopathologic study of 84 unselected patients with systemic sarcoidosis. Circulation 1978;58:1204–11. https://doi. org/10.1161/01.CIR.58.6.1204; PMID: 709777. Judson MA, Baughman RP, Teirstein AS, et al. Defining organ involvement in sarcoidosis: the ACCESS proposed instrument. ACCESS Research Group. A case control etiologic study of

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dose prednisone therapy in patients transplanted for CS. Patients undergoing LVAD placement may also be maintained with immunosuppression afterwards, weighing the benefits of sarcoidosis disease suppression with LVAD-related infection risk.

Cardiac Sarcoidosis in 2020: Where We Are and a Look to the Future CS is an increasingly recognised cause of heart block, VA and cardiomyopathy. Past limitations in diagnosis and management have included small single-centre or single-country studies limiting generalisability, a need for histopathological diagnosis and a lack of prospective trials for treatment efficacy. Over the past decade, advancements in cardiac imaging and newer expert consensus guidelines have lifted some of the prior challenges to the diagnosis of CS. These advancements may allow earlier recognition, and thus treatment, of CS moving forward, ideally prior to the development of irreversible cardiac inflammation and fibrosis. Although corticosteroids are the mainstay of therapy, prospective clinical trials are needed to determine the optimal dosing and treatment duration. In addition, retrospective studies of steroid-sparing agents in CS are only now starting to be published. The role of these agents needs to be further defined in efforts to decrease the morbidity associated with corticosteroids. Much remains to be learned on how best to diagnose and manage patients with CS. For example, how do we best screen patients for CS who have known extracardiac sarcoidosis? How do we better risk stratify patients with preserved or low normal LVEF with no prior history of VA? Should we treat patients with clinically silent CS? Ultimately, prospective multicentre studies are needed to elucidate answers to these questions to move the care of patients with CS forward.

Clinical Perspective • The clinical manifestation of cardiac sarcoidosis (CS) includes advanced-degree heart block, atrial tachycardia, ventricular arrhythmias and heart failure. • Cardiac MRI and PET imaging are important imaging tools for the diagnosis of CS and risk stratification. • In selected patients, ICD therapy is warranted to decrease the risk of sudden cardiac death. • Immunosuppressive therapy is the mainstay of treatment for active, inflammatory CS.

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Clinical Arrhythmias

Cardiac MRI to Manage Atrial Fibrillation Yan Zhao, Lilas Dagher, Chao Huang, Peter Miller and Nassir F Marrouche Tulane Research Innovation for Arrhythmia Discoveries (TRIAD), Heart and Vascular Institute, Tulane University School of Medicine, LA, US

Abstract AF is the most common arrhythmia in clinical practice. In addition to the severe effect on quality of life, patients with AF are at higher risk of stroke and mortality. Recent studies have suggested that atrial and ventricular substrate play a major role in the development and maintenance of AF. Cardiac MRI has emerged as a viable tool for interrogating the underlying substrate in AF patients. Its advantage includes localisation and quantification of structural remodelling. Cardiac MRI of the atrial substrate is not only a tool for management and treatment of arrhythmia, but also to individualise the prevention of stroke and major cardiovascular events. This article provides an overview of atrial imaging using cardiac MRI and its clinical implications in the AF population.

Keywords AF, cardiac MRI, atrial myopathy, imaging Disclosure: The authors have no conflicts of interest to declare. Received: 28 April 2020 Accepted: 6 October 2020 Citation: Arrhythmia & Electrophysiology Review 2020;9(4):189–94. DOI: https://doi.org/10.15420/aer.2020.21 Correspondence: Nassir F Marrouche, Tulane Research Innovation for Arrhythmia Discoveries (TRIAD), Heart and Vascular Institute, Tulane University School of Medicine, 1430 Tulane Avenue, Box 8548, New Orleans, LA 70112, US. E: nmarrouche@tulane.edu Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for noncommercial purposes, provided the original work is cited correctly.

AF is a common arrhythmia in clinical practice, with a prevalence of 2.7 million–6.1 million that is expected to rise to 5.6 million–12 million by 2050 in the US alone.1,2 Patients with AF have an increased risk of stroke and mortality and a decreased quality of life.3 In addition, management of AF increases the cost of healthcare.4,5,6 The mechanisms of AF are complex and are associated with electric and structural remodelling.7,8 What comes first: the AF or the atrial tissue damage or myopathy? A ‘chicken or egg’ question.

recovery preparation. To minimise the effect of LA motion, imaging data are acquired during the diastolic phase of the cardiac cycle prior to atrial kick. Data acquisition is usually limited to 15–20% of the cardiac cycle. Scan time for LGE-MRI of the LA is expected not to exceed 5–12 minutes, depending on patient heart rate and respiratory pattern. The typical scan parameters are a transverse imaging volume with voxel size of 1.25 × 1.25 × 2.5 mm (reconstructed to 0.625 × 0.625 × 1.25 mm) and inversion time of 230–320 ms.13

Over the last decade, significant developments in imaging atrial and ventricular tissue using cardiac MRI (CMR) have led to a measurable advancement in AF management. Utility includes localisation and quantification of the extent of cardiac substrate or myopathy, as well as the cardiac chamber shape, size and function.9–11 In this review, we highlight the most recent innovations and advances in the role of CMR in defining the AF substrate and the implications for the management of AF.

Several tools have been developed to analyse images acquired with CMR. Most of our experience has been with Corview (Marrek), a clinical and research software used to stage atrial myopathy and LA morphology in patients with AF.13,15,16 In summary, the epicardial and endocardial LA boundaries are segmented using a semi-automated fast grow-cut algorithm and then further refined by manual contouring.17 A 3D model of the left atrium is rendered, and atrial tissue changes are quantified by selecting intensity thresholds that correspond with LGE in the LA wall (Figure 1). Intensity thresholds in the range of 2–4 SDs from the mean are used to detect enhanced tissue.

Cardiac MRI Acquisition and Processing Quantification of left atrial (LA) structure and function using CMR has previously been presented.9,12–14 In brief, the MRI scan is performed on either a 1.5 or 3 Tesla scanner using conventional body and spine phased-array coils or specialised cardiac coils. Cardiac magnetic resonance angiography (MRA) is acquired during continuous gadolinium-based agent injection. High-resolution 3D late gadolinium enhancement (LGE) scans of the LA are typically acquired 15–30 minutes after contrast agent injection in the same imaging session. The imaging technique for LGE-MRI is based on respiratory navigated, ECGgated, gradient echo pulse sequence with fat suppression and inversion

Atrial Myopathy and AF Clinical and experimental studies have demonstrated a correlation between AF and atrial myopathy and vice versa. In histological examinations, the presence of AF is always associated with varying atrial myopathy in both atria.18,19 AF is known to initiate and perpetuate electrical and structural remodelling, which can ultimately lead to maladaptive consequences including myocardial apoptosis and subsequent collagen deposition, known as replacement fibrosis. Subsequently, this pathological substrate has been shown to maintain

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Clinical Arrhythmias Figure 1: Process of Quantification of Left Atrial Wall Fibrosis A

Healthy

Fibrotic

A: High-resolution 3D late gadolinium enhancement MRI scans of the left atrium are acquired; B: Epicardial and endocardial borders are contoured in each MRI slice to define the left atrial wall and quantified for fibrosis-based intensity of contrast enhancement; C: A model of the left atrium is rendered and visualisation of enhancement intensities are projected on the surface of the 3D model.

AF and can lead to other arrhythmias such as atrial tachycardia and sick sinus syndrome. In addition, this atrial myopathic substrate is also identified in patients with structural heart disease and even those without apparent heart disease.20,21 This indicates that structural alterations are already prevalent before the initiation of AF and AF may represent as an arrhythmic manifestation of the atrial myopathy.10,22,23 Therefore, an earlier and better characterisation of the atrial substrate is of clinical and experimental importance. The location and extent of atrial myopathy can be quantitatively assessed by CMR. The Delayed Enhancement-MRI Determinant of Successful Catheter Ablation of Atrial Fibrillation (DECAAF) study used CMR and classified LA myopathy based on the extent of LA late enhancement as Utah stages: stage I with <10%, stage II with ≥10% to <20%, stage III with ≥20% to <30% and stage IV with ≥30% LGE. Masson’s trichrome staining of human tissue samples showed that regions with interstitial fibrosis were correlated with high gadolinium enhancement.16 In contrast, minimal collagen staining was detected in the region with low gadolinium enhancement.2 Data from electroanatomic mapping during ablation also revealed that the regions of extreme low voltages correlated with enhanced regions on LGE-MRI.24 The benefit of CMR being non-invasive and having low spatial error, allows for insights into atrial myopathy to be appreciated.

Cardiac MRI and Stroke Risk Assessment of AF Patients AF patients suffer a fivefold higher stroke risk and AF-related stroke is more likely to be fatal and causes more severe functional disabilities.25 Current guidelines suggest the use of CHA2DS2-VASc score for assessment of stroke risk.26,27 However, conflicting data seem to suggest CHA2DS2-VASc performs poorly in estimating stroke risk.28–30 Emerging CMR markers of atrial myopathy have been shown to strongly correlate with embolic stroke risk regardless of heart rhythm, offering a promising alternative to conventional risk assessment tools.

Left Atrial Fibrosis and Stroke Risk Atrial fibrosis measured on CMR is an element of stroke risk assessment.31 A retrospective analysis of 387 patients with AF demonstrated that those with extensive LA enhancement had nearly four-times the odds of experiencing thromboembolic events.32 When combined with CHAD (excluding stroke itself) risk factors, a markedly

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improved predictive accuracy was observed, with the C statistic signiﬁcantly increasing from 0.58 to 0.72. King et al. demonstrated that a severe LA enhancement was associated with an increased risk of major adverse cardiovascular and cerebrovascular events, mainly driven by elevated risk of stroke.33 Furthermore, LA enhancement on CMR was associated with higher incidence of LA spontaneous echo contrast (SEC) and left atrial appendage (LAA) thrombus formation detected during transoesophageal echocardiography testing.34 This can be explained by increased tissue thrombogenicity and impaired atrial contractility as a result of the atrial myopathy.

Left Atrial Function Quantitative analysis of LA function has been shown to have prognostic value in stroke risk assessment.35–39 Assessed by LA reservoir strain with speckle-tracking, each 1% decrease in LA ejection fraction resulted in a 7% increased risk of having a cardio-embolic stroke.38 The association between CMR-assessed LA reservoir function and a history of stroke or transient ischaemic attack (TIA) has been shown in patients with AF.36 This is consistent with a cross-sectional study from Ciuffo et al., who concluded that LA mechanical dyssynchrony during sinus rhythm was associated with a history of stroke/TIA.39 A sub-analysis of the Multi-Ethnic Study of Atherosclerosis (MESA) study demonstrated that reduced total LA ejection fraction on CMR was associated with ischaemic cerebrovascular events independent of clinical risk factors.40 One can expect that a lower LA reservoir function may increase blood stasis and participate in subsequent thrombus formation. Notably, most of these findings are evaluated in AF patients with sinus rhythm. In patients with persistent and long-standing AF, there is a need for more research to obtain an integrated analysis of LA function and stroke risk.

Left Atrial Morphology Studies now focus on features of LA shape on MRA and its relationship with stroke risk. Bisbal et al. described the LA sphericity analysing the LA geometry by CMR and claimed a higher LA sphericity was the only factor associated with prior thrombus events with an OR of 1.26 for each 1% increase in LA sphericity.41,42 It stands to reason a more spherical shape has more areas of stagnant flow and may reduce the generation of eddy current and promote the formation of blood stasis and thrombosis. Cates et al. developed a more descriptive and comprehensive shape score for identifying LA shape changes using particle-based modelling (PBM).14,43 They extracted the LA surface

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CMR and AF management contours from MRA, and used the LA endocardial surface correspondence points to calculate the ratio of the maximum anterior to posterior distance to the maximum left to right distance.14 Shape scores are computed by coefficients from the model and LA shape is divided into four classes. From this PBM-based method, a higher LA shape score tends to have a more spherical shape and thus potentially serve as a substrate for stroke development. Clinical studies are needed to relate this score system to stroke risk.

Left Atrial Appendage Morphology The LAA is responsible for approximately 90% of the thrombus in patients with nonvalvular AF.44,45 Beinart et al. analysed the geometry and dimensions of the LAA derived from CMR of 144 patients.46 A larger LAA neck dimension is associated with a history of TIA or stroke in AF patients. Cates et al. applied PBM to LAA acquired with CMR and compared LAA morphology between patients with and without SEC based on LAA length and orientation parameters.14 Morphologies with longer, thinner LAAs and LAAs that curved anteriorly were more likely to present SEC on transoesophageal echocardiography. The underlying mechanism may be that a longer and more curved LAA structure might be more restrictive of blood flow in the chamber, increasing blood stasis and thus stroke risk.

measured by CMR strongly correlates with increased fibrofatty myocardial replacement.57 In patients with AF, the lower pre-ablation function was correlated with higher LA enhancement and lower AF ablation procedural success.58

Cardiac MRI During Ablative Treatment of AF Applying CMR imaging before treating AF also helps define an ablation target. A sub-analysis of the DECAAF study suggested that residual fibrosis, defined as preexisting fibrosis not altered by the ablation procedure, was associated with higher incidence of recurrent atrial arrhythmia.59 This observation was confirmed in another 172-patient study demonstrating that a higher residual ﬁbrosis correlated with poor ablation success rate.60 This evidence suggests that targeting areas of atrial myopathy during an ablation procedure could convert a heterogeneous arrhythmogenic fibrotic tissue to homogeneous scar tissue. This so-called scar homogenisation could lead to improvement in procedural outcome. The on-going DECAAFII trial enrolled more than 800 AF patients and aims to investigate the hypothesis that targeting atrial myopathy during catheter ablation can improve the treatment success rate, as well as clinical outcomes (NCT02529319).

In summary, we propose that atrial myopathy markers on CMR including LA fibrosis, LA and LAA morphology and LA function could indeed have strong predictive value in stroke risk assessment. These CMR markers may be implemented into risk stratification methods for AF. Large clinical trials focused on validating CMR-based morphometric analyses are warranted to revolutionise stroke prevention strategies and provide more accurate, personalised stroke risk management for high-risk patients with and without AF.

Real-time MRI-guided ablation has shown great potential in improving the catheter ablation procedure. It is useful in visualising and localising both ablation lesions and scar formation in animal models.61,62 Data of real-time MRI-guided electrophysiology in patients are limited.63–66 Nazarian et al. reported the first successful electrophysiological study in two patients.63 A recent pilot study demonstrated that real-time CMR-guided ablation for typical right atrial ﬂutter is safe and highly efficacy.66 Until now, real-time CMR-guided ablation is not yet applied to AF patients. In addition, advanced CMR devices and imaging techniques are essential to broad clinical use.

Cardiac MRI and AF Treatment Strategy Cardiac MRI Helps Define a Treatment Plan

Role of Cardiac MRI in Patients After Ablative Treatment

Catheter ablation of AF is emerging as a first-line treatment option to restore sinus rhythm and improve long-term clinical outcomes.47,48 Despite dramatic improvements in techniques over the last 2 decades, the short and long-term success rate of catheter ablation is still modest.49–52 Moreover, the catheter ablation community is still operating under ‘one-size-fits-all’ approach. Not every patient is an ablation candidate – personalised ablation strategies are urgently needed.

Detection of ablation lesion after ablation of AF is a major strength of CMR.67–70 Pulmonary vein (PV) reconnection is a main reason for AF recurrence. In a study by Badger et al., circumferential scarring of all four PVs was only achieved in 6.9% of patients.69 Nevertheless, many patients with at least one non-isolated PV remained in sinus rhythm.59 Poor scar formation transferred from acute electrical isolation is also a key factor. Although electrical isolation was achieved during the AF ablation procedure, only 33.9% of lesions were permanently scarred 3 months later on CMR.67

Over the last 13 years, a significant amount of data has emerged supporting the use of CMR in defining appropriate candidates for catheter ablation independent of approach and tools used. In the DECAAF study, the pre-ablation extent of LGE was an independent predictor of arrhythmia recurrence.16 A baseline LGE extent of more than 30% was associated with a poor response to the procedure in the ﬁrst year after ablation.53 In a 5-year follow-up study, every 10% increase in atrial ﬁbrosis pre-procedure accounted for a 45% increased risk of AF recurrence.54 Moreover, patients with minimal LA enhancement experienced better outcomes after ablation. LA remodelling is associated with change of LA geometry, leading to a greater LA diameter and higher LA volume.55,56 Functional measurements by echocardiography does not allow appreciation of LA shape. Bisbal et al. introduced the concept that LA sphericity measure by CMR was associated with a larger LA diameter and higher risk of AF recurrence.41 LA functional remodelling also serves as a key factor to atrial myopathy. Histologic analysis demonstrated that decreased LA function as

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CMR can quantify and localise the gaps among PVs and ablationinduced scar. An increase of 10% relative gap length increased the likelihood of AF recurrence by 16%.71 This emphasises the potential benefit of targeting CMR-detected gaps as a feasible approach during repeat ablation. Among 102 patients who underwent second procedure, Fochler et al. used a de-channelling ablation procedure involving targeting channels/gaps and superficial ablation lesions as detected by either electroanatomic mapping or post-ablation CMR. They found that after 1 year of follow-up, patients had similar recurrence rates regardless of the de-channelling ablation strategy whether it was guided by electroanatomic mapping or CMR.68 In patients with repeated procedures, aggressive ablative strategies are always recommended. However, high scar burden leads to a reduction of LA function independent of AF recurrence.72,73 Based on the pre-repeat procedure CMR, the operator can save time and effort spent on the electroanatomic mapping, as well as avoid extensive ablation and scar formation.

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Clinical Arrhythmias Figure 2: Personalised Treatment for Patients with Symptomatic AF Based on Cardiac MRI

Stroke prevention

Management of symptomatic AF

LA shape

Atrial fibrosis

Class 1

Class 2

Class 3

First treatment

Redo procedure

Class 4

Residual fibrosis ablation

<10%

Posterior

PVI ± substrate homogenisation

Superior

≥10% to <20%

Left

De-channelling

High stroke risk

≥20% to <30%

(awaiting large study)

LAA shape Stroke less likely

Appendage ‘length’ (superior view)

Scattered

Stroke more likely

Opening to LA

Appendage ‘curvature’ (superior view)

Distal tip

Gap

Localised

Substrate homogenisation or non-ablative management

≥30% (awaiting DECAAF II)

−2.0σ

−1.0σ

Mean

+ 1.0σ

+ 2.0σ

Atrial fibrosis is categorised as Utah stages based on the extent of LA late enhancement: stage I with <10%, stage II with ≥10% to <20%, stage III with ≥20% to <30% and stage IV with ≥30% LGE. LA morphology is calculate by the ratio of the maximum anterior to posterior distance to the maximum left to right distance based on the PBM. LAA morphology was classified based on the PBM by both LAA length and orientation parameters. CMR = cardiac MRI; LA = left atrial; LAA = left atrial appendage; LGE = late gadolinium enhancement; PBM = particle-based modelling; PVI = pulmonary vein isolation.

Moreover, atrial myopathy is a dynamic disease. A recent study marked fibrotic progression ≥21% after catheter ablation as a novel predictor of long-term procedural success. For every 1% increase in new-onset fibrosis, the risk of post-ablation AF recurrence increased by 3%.74 On the other hand, atrial myopathy may continue to exist independent of AF. In patients with lone AF, the subtle atrial dysfunction did not normalise after ablation and this further indicates that atrial myopathy may be a cause of arrhythmia.75 Therefore, it is important to monitor atrial myopathy even in patients without recurrence.

Personalised Approach for AF Management Based on Cardiac MRI The understanding of AF is changing from a sole rhythm disease to that of an atrial myopathy disease.10,22,23 Recent innovations in imaging techniques help advance the concept of atrial myopathy as a clinically relevant entity. CMR is valuable in characterising the thrombogenic and arrhythmogenic remodelling process associated with atrial myopathy. From this perspective, we have developed a treatment algorithm to individualise AF ablation strategies (Figure 2). Based on the data discussed above, we recommend ablation as a first line therapy for patients with low extent of LA fibrosis (e.g. Utah stage I and Utah stage II). For patients with higher Utah classes (e.g. Utah stage III with diffuse ﬁbrosis and Utah stage IV), a non-invasive approach or fibrosis homogenisation should only be considered. The DECAAF II study will provide more insight into atrial myopathy and guidance on its treatment. Gaps between ablated-scar and progression of atrial myopathy should be considered in cases of arrhythmia recurrence. It needs to be stressed that – regardless of the treatment – monitoring ablation lesion behaviour and progression of atrial myopathy using CMR is necessary.

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Atrial myopathy markers detected by CMR also predict the risk of having a cardio-embolic stroke. As such, anticoagulants could be prescribed for patients with extensive atrial myopathy, regardless of the CHA2DS2-VASc score. Moreover, anticoagulation should be continued after ablation even without evidence of recurrent atrial arrhythmia. Large clinical trials are needed to verify this treatment algorithm and establish a more powerful prediction model based on imaging markers to better personalise treatment of AF.

Conclusion AF and atrial myopathy are two epidemics that often coexist with complex bidirectional interactions. With recent developments in advanced imaging techniques, CMR, in particular, is establishing itself as a powerful tool for assessment of cardiac myopathy and guiding treatment strategies for the AF patient. Further standardisation and large randomised clinical trials are needed to integrate personalised CMR algorithms into definitive guidelines and revealing a new era in the treatment of the atrial disease.

Clinical Perspective • Current understanding of AF has been enhanced from a sole rhythm disease towards a cardiomyopathy based on arrhythmia substrates. • CMR is a viable tool for characterising the thrombogenic and arrhythmogenic remodelling process associated with atrial myopathy. • Applying CMR for AF patients allows for a strategy of an individual and substrate-guided management of AF.

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Left atrial mechanical function and incident ischemic cerebrovascular events independent of AF: insights from the MESA study. JACC Cardiovasc Imaging 2019;12:2417–27. https://doi.org/10.1016/j. jcmg.2019.02.021; PMID: 31005519. 41. Bisbal F, Guiu E, Calvo N, et al. Left atrial sphericity: a new method to assess atrial remodeling. Impact on the outcome of atrial fibrillation ablation. J Cardiovasc Electrophysiol 2013;24:752–9. https://doi.org/10.1111/jce.12116; PMID: 23489827. 42. Bisbal F, Gomez-Pulido F, Cabanas-Grandio P, et al. Left atrial

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Tailored atrial substrate modification based on low-voltage areas in catheter ablation of atrial fibrillation. Circ Arrhythm Electrophysiol 2014;7:825–33. https://doi.org/10.1161/CIRCEP.113.001251; PMID: 25151631. Verma A, Jiang CY, Betts TR, et al. Approaches to catheter ablation for persistent atrial fibrillation. N Engl J Med 2015;372:1812–22. https://doi.org/10.1056/NEJMoa1408288; PMID: 25946280. Calkins H, Hindricks G, Cappato R, et al. 2017 HRS/ EHRA/ECAS/APHRS/SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation. Heart Rhythm 2017;14:e275–e444. https://doi. org/10.1016/j.hrthm.2017.05.012; PMID: 28506916. Khurram IM, Habibi M, Gucuk Ipek E, et al. Left atrial LGE and arrhythmia recurrence following pulmonary vein isolation for paroxysmal and persistent AF. JACC Cardiovasc Imaging 2016;9:142–8. https://doi.org/10.1016/j.jcmg.2015.10.015; PMID: 26777218. Chelu MG, King JB, Kholmovski EG, et al. Atrial fibrosis by late gadolinium enhancement magnetic resonance imaging and catheter ablation of atrial fibrillation: 5-year follow-up data. J Am Heart Assoc 2018;7:e006313. https://doi.org/10.1161/ JAHA.117.006313; PMID: 30511895. Benito EM, Carlosena-Remirez A, Guasch E, et al. Left atrial fibrosis quantification by late gadolinium-enhanced magnetic resonance: a new method to standardize the thresholds for reproducibility. Europace 2017;19:1272–9. https://doi. org/10.1093/europace/euw219; PMID: 27940935. Berruezo A, Tamborero D, Mont L, et al. Pre-procedural predictors of atrial fibrillation recurrence after circumferential pulmonary vein ablation. Eur Heart J 2007;28:836–41. https:// doi.org/10.1093/eurheartj/ehm027; PMID: 17395676. Huber AT, Lamy J, Rahhal A, et al. Cardiac MR strain: a noninvasive biomarker of fibrofatty remodeling of the left atrial myocardium. Radiology 2018;286:83–92. https://doi. org/10.1148/radiol.2017162787; PMID: 28813234. Csecs I, Yamaguchi T, Kheirkhahan M, et al. Left atrial functional and structural changes associated with ablation of atrial fibrillation – cardiac magnetic resonance study. Int J Cardiol 2019. https://doi.org/10.1016/j.ijcard.2019.12.010; PMID: 31874788. Akoum N, Wilber D, Hindricks G, et al. MRI assessment of ablation-induced scarring in atrial fibrillation: analysis from the DECAAF Study. J Cardiovasc Electrophysiol 2015;26:473–80. https://doi.org/10.1111/jce.12650; PMID: 25727106. Akoum N, Morris A, Perry D, et al. substrate modification is a better predictor of catheter ablation success in atrial fibrillation than pulmonary vein isolation: an LGE-MRI study. Clin Med Insights Cardiol 2015;9:25–31. https://doi.org/10.4137/ CMC.S22100; PMID: 25983561. Vergara GR, Vijayakumar S, Kholmovski EG, et al. Real-time magnetic resonance imaging-guided radiofrequency atrial ablation and visualization of lesion formation at 3 Tesla. Heart Rhythm 2011;8:295–303. https://doi.org/10.1016/j. hrthm.2010.10.032; PMID: 21034854. Kholmovski EG, Coulombe N, Silvernagel J, et al. Real-time MRI-guided cardiac cryo-ablation: a feasibility study. J Cardiovasc Electrophysiol 2016;27:602–8. https://doi. org/10.1111/jce.12950; PMID: 26856381.

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ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

Clinical Arrhythmias

Frequency and Determinants of Spontaneous Conversion to Sinus Rhythm in Patients Presenting to the Emergency Department with Recent-onset Atrial Fibrillation: A Systematic Review Nikki AHA Pluymaekers,1 Astrid NL Hermans,1 Dominik K Linz,1,2 Elton AMP Dudink,1 Justin GLM Luermans,1,2 Bob Weijs,1 Kevin Vernooy1,2 and Harry JGM Crijns1 1. Department of Cardiology, Maastricht University Medical Centre and Cardiovascular Research Institute Maastricht, Maastricht, the Netherlands; 2. Department of Cardiology, Radboud University Medical Centre, Nijmegen, the Netherlands

Abstract The exact frequency and clinical determinants of spontaneous conversion (SCV) in patients with symptomatic recent-onset AF are unclear. The aim of this systematic review is to provide an overview of the frequency and determinants of SCV of AF in patients presenting at the emergency department. A comprehensive literature search for studies about SCV in patients presenting to the emergency department with AF resulted in 25 articles – 12 randomised controlled trials and 13 observational studies. SCV rates range between 9–83% and determinants of SCV also varied between studies. The most important determinants of SCV included short duration of AF (<24 or <48 hours), low number of episodes, normal atrial dimensions and absence of previous heart disease. The large variation in SCV rate and determinants of SCV was related to differences in duration of the observation period, inclusion and exclusion criteria and in variables used in the prediction models.

Keywords Spontaneous conversion, AF, determinants, systematic review, emergency care Disclosure: The authors have no conflicts of interest to declare. Received: 26 July 2020 Accepted: 11 November 2020 Citation: Arrhythmia & Electrophysiology Review 2020;9(4):195–201. DOI: https://doi.org/10.15420/aer.2020.34 Correspondence: Nikki AHA Pluymaekers, Department of Cardiology, Maastricht University Medical Centre, P Debyelaan 25, 6229 HX Maastricht, the Netherlands. E: nikki.pluymaekers@mumc.nl Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for noncommercial purposes, provided the original work is cited correctly.

In patients presenting at the emergency department (ED) with symptomatic recent-onset AF, immediate restoration of sinus rhythm by pharmacological cardioversion (PCV) or electrical cardioversion (ECV) is frequently performed.1,2 Nevertheless, most of these patients convert spontaneously to sinus rhythm without the need of additional interventions.3–7 Several studies have indicated that rate control to manage symptoms and waiting for spontaneous conversion (SCV) to sinus rhythm is a reasonable alternative for the acute treatment of patients with recent-onset haemodynamically stable AF.4,8 ECV is a relatively expensive procedure and, dependent on local protocols, requires the involvement of nurses, an anaesthesiologist and a cardiologist or emergency physician. Point-of-care identification of patients with recent-onset AF who will convert spontaneously after presentation and therefore qualify for a wait-and-see approach would lower the number of PCV and ECV procedures performed in the ED setting and therefore reduce healthcare costs. The exact frequency as well as clinical predictors of SCV to sinus rhythm in patients with symptomatic recent-onset AF are unclear. Appropriate selection of patients with a high likelihood of SCV is key to the wait-andsee approach. The present review focuses on the frequency and determinants of SCV of AF in patients presenting at the ED.

Methods Search Methods and Study Selection A literature search was performed to identify all articles published in English that discussed SCV to sinus rhythm in patients presenting to the ED with AF. A Boolean search of PubMed, Embase and Cochrane Library was performed using the phrases “spontaneous conversion”, “SCV”, “self-terminating”, “self terminating”, “wait-and-see”, “wait and see” AND “atrial fibrillation”, “AF”, “AFib” AND “recent onset”, “recent-onset”, “acute”, “paroxysmal”, “first detected”, “first-detected”. The reference lists of included articles were reviewed to identify additional articles. All original articles were included if they discussed SCV to sinus rhythm in patients presenting to the ED with AF. There were no exclusion criteria. We focused on patients who presented to the ED rather than the regular outpatient or clinical department, since this is a clinically identifiable group of patients for whom unnecessary future ED visits and cardioversion may by avoided by knowing their SCV characteristics. The literature search and screening for eligibility were performed by two of the authors (NAHAP and ANLH) independently and any disagreements were resolved by discussion until consensus was reached.

Outcome and Data Collection The primary outcome was the SCV rate. Secondary outcomes were determinants for SCV and adverse events. Data on

Access at: www.AERjournal.com

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Clinical Arrhythmias Figure 1: Flow Chart of Literature Search PubMed, Embase, Cochrane Library, reference lists n=138 Excluded by title n=77 Not dealing with the subject of the review, not original articles 61 selected articles Excluded by abstract n=27 Not dealing with the subject of the review, not original articles or not set in the ED 34 selected articles Excluded after critical review n=9 Not dealing with the subject of the review, not original articles or not at the ED 25 included articles

study design, patient characteristics, intervention and treatment were extracted.

Quality Assessment All included articles were independently assessed for the risk of bias by the two reviewers using the Cochrane tool to assess the risk of bias for randomised controlled trials (RCT) and the Risk of Bias in Nonrandomized Studies of Interventions (ROBINS-I) tool for the nonrandomised studies.9,10 Inclusion of consecutive patients was considered to be a relevant confounding domain for the primary outcome. Disagreements between the reviewers were resolved by discussion.

Definitions For the purpose of this review, conversion was defined as spontaneous if the patient converted to sinus rhythm without active cardioversion (either PCV or ECV), with rate control and/or placebo medication allowed. If patients were treated with placebo, digoxin, beta blockers or non-dihydropyridine calcium channel blockers and converted to sinus rhythm, it was considered SCV for this review. The reported time until evaluation of the rhythm was used as observation time. If not reported it was considered to have no standardised observation time. Determinants of SCV were accumulated if the studies performed an analysis for determinants of SCV.

Results Screening and Included Studies A comprehensive literature search identified 138 potentially relevant articles. After screening of title and abstract, exclusion of duplicates and critical review of the full text, 25 articles were included in this systematic review (Figure 1). Of the 25 included articles, 12 were RCTs, seven were prospective observational cohort studies and six were retrospective observational cohort studies. An overview of abstracted data from included studies is provided in Table 1.

Quality Assessment Four of the 12 RCTs were multicentre clinical trials, nine trials compared acute cardioversion with placebo/rate control, two trials compared rate control versus placebo and one trial compared two different rate control strategies. A complete overview of assessment of risk of bias for the RCTs are reported in Figure 2a and Supplementary Material Table 1.

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An overview of the risk of bias assessment for the observational studies is reported in Figure 2b and Supplementary Material Table 2. Eight studies were assessed to have a serious risk of bias and five a moderate risk of bias.

Spontaneous Conversion After a Short Observation Period Early SCV (<2.5 hours) was described in four studies and conversion rates ranged from 8.7–28.6% (Figure 3).11–14 The mean age was 64 years and 41% were women. The main difference between the studies was the duration of the onset of symptoms. Perrea et al., Vinson et al. and Hohnloser et al. included only patients with an onset of symptoms <48 hours.12–14 Scheuermeyer et al. included all patients with AF irrespective of the time of symptom onset.11 An overview of inclusion and exclusion criteria is shown in Supplementary Material Table 3.

Spontaneous Conversion After a Long Observation Period Three trials reported a SCV rate at 8 hours ranging from 37–48%. Two were RCTs which compared oral propafenone versus placebo and one trial compared oral flecainide to IV amiodarone and placebo.15–17 Those trials were comparable regarding the inclusion and exclusion criteria and patient characteristics (mean age 58, 58.5 and 60 years; and mean AF duration 28, 30.5 and 35 hours). A longer observation period of up to 24 hours was described by nine trials and SCV rates varied in those trials from 32–73%.6,7,18–24 Seven studies were RCTs and two were observational. Baseline characteristics were similar among all these studies, with a mean age of 64 years and on average 47% of patients being women. Notably, inclusion criteria differed with respect to the duration of onset of symptoms at presentation, ranging from <24 hours up to 7 days. A higher SCV rate (52–77%) was reported in the studies with a long observation period of up to 48 hours (mean age 63 years, 38% women).4,5,8,13,25–28 In two observational studies the observation period extended beyond 48 hours. Danias et al. reported an SCV rate of 68% after a median observation time of 4.6 days.3 Abadie et al. reported a SCV rate of 63% at 48 hours and up to 83% after 30 days (Figure 3).29

Determinants of Spontaneous Conversion Determinants of SCV varied among studies (Table 2). Only one study reported on determinants of early SCV, therefore no comparison was made between early and late SCV determinants. Perrea et al. reported a formula ([heart rate/systolic blood pressure] + 0.1 × number of past AF episodes) to determine the likelihood of SCV.12 Using this formula, a cut-off value of 1.3 was found to have a sensitivity of 78.6% and specificity of 77.9% for predicting SCV. Duration of the AF episode at presentation at the ED appeared to be an important determinant for SCV in three studies. Dell’Orfano et al. and Lindberg et al. reported a higher likelihood of SCV in patients with AF duration <48 hours. Danias et al. reported a higher SCV rate in patients with AF duration <24 hours. Apart from episode duration, first episode of AF, absence of previous supraventricular arrhythmias and normal left atrial dimensions were found to be important determinants of SCV.6,7,19,21 Patients without heart failure or underlying heart disease also had a higher SCV rate.7,16,23 Remarkably, Choudhary et al. reported a higher SCV rate in patients with ischaemic heart disease.19 Also in this study, a

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

Spontaneous Conversion to Sinus Rhythm of Recent-onset AF Table 1: Overview of Abstracted Data from Included Studies

Study, Country

Centres (n)/ Study Design, Patients (n) Intervention

Setting/Observation Time

RCTs

Included

SCV rate n (%)

Falk et al. 1987,24 US

1/36

RCT, oral digoxin versus placebo

ED/hospitalised, 18 h observation

New-onset AF seen in the ED or on the wards (duration <7 days)

17/36 (47.2%)

1/62

RCT, oral flecainide versus ED/hospitalised, 8 h IV amiodaron versus placebo observation

Recent-onset AF (<7 days)

10/21 (48%)

Capucci et al. 1994,15 1/181 Italy

RCT, oral propafenone versus ED/hospitalised, 8 h oral flecainide versus observation placebo

Recent-onset AF (<7 days) (if AF >72 h only if chronically anticoagulated)

24/62 (39%)

Bellandi et al. 1996,20 1/182 Italy

RCT, IV propafenone versus placebo

ED/hospitalised, 24 h observation

Paroxysmal AF lasting >30 min but <7 days

27/84 (32%)

Galve et al. 1996,21 Spain

1/100

RCT, IV amiodaron versus placebo

ED/hospitalised, 24 h observation

Recent-onset AF (<7 days)

30/50 (60%)

DAAF trial 1997,18 Sweden

13/239

RCT, IV digoxin versus IV placebo

ED/hospitalised, 16 h observation

Recent-onset AF (<7 days)

116/239 (48.5%)

Azpitarte et al. 1997,22 1/55 Spain

RCT, oral propafenone versus placebo

ED/hospitalised, 24 h observation

All patients with acute AF presenting at the ED

19/26 (73%)

Boriani et al. 1997,16 Italy

3/240

RCT, oral propafenone versus placebo

ED/hospitalised, 8 h observation

Recent-onset AF (<7 days) (if AF >72 h only if chronically anticoagulated)

45/121(37.2%)

Cotter et al. 1999,7 Israel

1/100

RCT, IV amiodaron versus placebo

ED/hospitalised, 24 h observation

Paroxysmal AF <48 h and at least one previous episode of paroxysmal AF

32/50 (64%)

Hohnloser et al. 2004,14 Germany

34/201

RCT, IV tedisamil versus placebo

ED/hospitalised, 2.5 h observation

Symptomatic AF or AFL of 3–48 h duration, BP >90 mmHg systolic and BP <105 mmHg diastolic.

4/46 (8.7%)

Hassan et al. 2007,23 US

2/50

RCT IV diltiazem versus IV esmolol

ED 24h observation (time after drug infusion)

New-onset or paroxysmal AF and a rapid 20/50 (40%) ventricular rate (>100 BPM over 10 min)

Pluymaekers et al. 15/437 2019,8 the Netherlands

RCT, early cardioversion versus wait-and-see

ED 48h observation

Haemodynamic stable, symptomatic patients with AF <36h

Non-RCTs

Capucci et al. 1992, Italy

150/218 (69%)

Danias et al. 1998,3 US

2/356

Prospective

ED/hospitalised, observation AF <72 h 4.6 days (time to CV 1.7 days)

Dell’Orfano et al. 1999,25 US

1/114

Retrospective

ED <48 h observation

Primary diagnosis of AF, documentation of the arrhythmia by single-channel or 12-lead ECG

57/114 (50%)

Mattioli et al. 2000,28 Italy

1/140

Prospective

ED/hospitalised, 48 h observation

Ione AF with a clinically estimated duration of <6 h

108/140 (77.1%)

Mattioli et al. 2005,27 Italy

1/116

Prospective, case control

ED 48 h after onset of symptoms

Haemodynamically stable patients, hospitalised for an acute episode of lone AF (<6 h onset of symptoms)

72/116 (62.1%)

Geleris et al. 2001,6 Greece

1/153

Prospective

ED 24 h observation

Consecutive patients with recent onset AF (< 24 h)

109/153 (71.2%)

Dixon et al. 2005,26 US

1/135

Retrospective

ED/hospitalised, in general monitoring up to 48 h

Primary diagnosis of AF (essential reason for hospital admission)

71/135 (52.6%)

Doyle et al. 2011,4 Australia

1/35

Prospective, wait-and-see

ED 48 h wait-and-see

Patients with stable acute AF <48 h

22/35 (62.9%)

Perrea et al. 2011,12 Greece

1/141

Retrospective pilot study: SCV, amiodaron

ED no observation time

AF at the time of presentation (<48 h)

28/141 (19.6%)

2/927

Retrospective

ED no observation time

Consecutive patients with AF

121/927 (13.1%)

1/374

Retrospective

ED <48 h observation

Consecutive patients admitted to hospital with first onset AF

203/374 (54%)

Vinson et al. 2012,13 US

3/206

Prospective

ED no observation, small subgroup 48 h wait-and-see

Recent-onset AF (<48 h)

59/206 (28.6%) 11/16 (68.8%) WAS

Choudhary et al. 2013,19 Sweden

1/148

Retrospective

ED SCV <18 h after symptom Patients with paroxysmal AF <48 h onset

48/148 (32.4%)

Abadie et al. 2019,29 US

1/157

Prospective

ED 30–90 days observation

48h 98/157 (63%), 30 days 113/136 (83%)

Scheuermeyer et al. 2012,11 Canada Lindberg et al. 2012, Denmark

Low-to-moderate risk AF patient

242/356 (68%)

AFL = atrial flutter; BP = blood pressure; CV = conversion; ED = emergency department; RCT = randomised controlled trial, SCV = spontaneous conversion; WAS = wait-and-see approach.

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Clinical Arrhythmias

Falk et al. 198724

Danias et al. 19983 Dell’Orfano et al. 199925

Capucci et al. 199217

Capucci et al. 199415

Galve et al. 199621

DAAF trial 199718

Azpitarte et al. 199722

Boriani et al. 199716

Cotter et al. 19997

Bellandi et al. 199620

Overall bias

Bias in selection of the reported result

Bias in measurements of outcomes

Bias due to missing data

Bias due to deviations from intended interventions

Geleris et al. 20016 Dixon et al. 200526 Doyle et al. 20114 Perrea et al. 201112 Scheuermeyer et al. 201211

Lindberg et al. 20125

Vinson et al. 201213

Hassan et al. 2007

Choudhary et al. 201319

Bias in classification of interventions

Mattioli et al. 200527

Hohnloser et al. 2004

Bias in the selection of participants into the study

Mattioli et al. 200028

? ?

Bias due to confounding

Other bias

B Selective reporting (reporting bias)

Incomplete outcome data (attrition bias)

Blinding of outcome assessment (detection bias)

Blinding of participants and personnel (performance bias)

Random sequence generation (selection bias)

Allocation concealment (selection bias)

Figure 2: Risk of Bias Assessment

Pluymaekers et al. 20198

Abadie et al. 201929

A: Overview of risk of bias assessment for the randomised controlled trials. Green circles represent a low risk of bias. For white circles with question marks, the risk of bias could not be established. B: Overview of risk of bias assessment for the observational studies. Green circles represent a low risk of bias, orange circles an intermediate risk of bias, red circles a high risk of bias.

Adverse Events and Thromboembolic Complications

Figure 3: Spontaneous Conversion Rate for Different Periods of Observation Times

Adverse events were mainly reported in the RCTs and in only two observational studies.4,7,8,13–18,20–23 An overview of reported adverse events is in Supplementary Material Table 3. Overall adverse events were higher in the cardioversion group compared to the rate control/placebo groups (Supplementary Material Table 4). Reported adverse events in the rate control and placebo group were sustained atrial flutter/tachycardia, pauses >2 seconds and/or bradycardia, vomiting, hypotension and, in one case, heart failure. In the Digitalis in Acute AF (DAAF) trial, one patient in the digoxin group experienced circulatory distress due to previously undiagnosed hypertrophic obstructive cardiomyopathy.18 Hohnloser et al. reported ventricular tachycardia in 2% of cases in the placebo group but no further details were provided.14 Cotter et al. reported a small non-Q wave MI 24 hours after admission in one patient.7

100

Spontaneous conversion rare (%)

0 12

>48

Duration of observation in hours Randomised controlled trials = green; observational studies = orange. The diameter of the circle represents the size of the population included in the trial.

lower AF rate was associated with a higher SCV rate. Mattioli et al. compared personality, socio-economic factors and acute stress in patients with SCV to a matched control group. Patients with acute stress or a type A behaviour pattern had the highest probability of SCV; coffee consumption and a high BMI reduced the SCV rate. Of note, multivariate analyses to determine independent determinants of SCV were not performed in every study and the strategy to include variables in the prediction models varied between studies.

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Only six studies (two RCTs and four observational) reported on thromboembolic or bleeding complications, which rarely occurred. Lindberg et al. and Doyle et al. did not observe thromboembolic complications.4,5 Cotter et al. reported one transient ischaemic attack 10 hours after admission while the patient was in AF.7 Stroke risk scores, such as CHA2DS2-VASc or CHADS2, were not available at the time of this trial and therefore not known for this patient.30,31 Scheuermeyer et al. reported two strokes within 30 days; a 59-year-old man on rate control medication and known to have a history of diabetes, hypertension and treated with warfarin presented at day 27 with a stroke due to bleeding (international normalised ratio = 4.1).11 The other was an 82-year-old man, in whom no specific AF treatment was performed and who had a stroke 24 days after visiting the ED. This patient was not on anticoagulant treatment due to a high perceived bleeding risk. Vinson et al. reported two strokes within 48 hours of the ED visit; neither patient was on anticoagulation therapy. In one patient,

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Spontaneous Conversion to Sinus Rhythm of Recent-onset AF Table 2: Determinants of Spontaneous Conversion Author, Country

Determinants of SCV

Galve et al. 1996,21 Spain

Absence of congestive heart failure and history of SVT, smaller left atrial size

Boriani et al. 1997, Italy

Patients without heart disease (defined as the absence of cardiac abnormalities other than AF)*

Cotter et al. 1999,7 Israel

(Univariable) left atrial size <45 mm, EF >45% and no significant mitral regurgitation

Non-RCT

Danias et al. 1998,3 US

Duration of AF <24 h

Dell’Orfano et al. 1999,25 US

Duration of AF <48 h

Mattioli et al. 2000,28 Italy

Onset AF during sleep, elevated ANP

Mattioli et al. 2005,27 Italy

Patients with acute stress showed the highest probability of SCV followed by patients with Type A behaviour

Geleris et al. 2001,6 Greece

Left atrial dimension (univariable)

Perrea et al. 2011, Greece

[HR/systolic blood pressure] + 0.1 × number of past AF episodes

Lindberg et al. 2012,5 Denmark

Duration of AF <48 h

Choudhary et al. 2013,19 Sweden

AFR <350 fpm, presence of IHD and first-ever episode of AF

*Boriani et al. reported in the same population divided by age, patients with age <60 years as predictor for SCV.35 We excluded studies that did not report on determinants of SCV. AFR = atrial fibrillatory rate; ANP = atrial natriuretic peptide; EF = ejection fraction; fpm = fibrillations per minute; HR = heart rate; IHD = ischaemic heart disease; SCV = spontaneous conversion; SVT = supraventricular tachycardia (previous atrial arrhythmias).

anticoagulation was withheld after successful ECV because of previous haemorrhagic complications and one stroke patient underwent rate control during the ED visit but refused anticoagulation treatment.13 In the Rate Control Versus Electrical Cardioversion Trial 7–Acute Cardioversion Versus Wait and See (RACE 7 ACWAS trial), two patients had cerebral embolism.8 One occurred 5 days after SCV while on anticoagulation treatment since the previous ED visit, the other stroke occurred 10 days after ECV in a patient who had begun taking anticoagulation treatment during the ED visit.

Discussion This systematic review provides an overview of the frequency and determinants of SCV of AF in patients presenting at the ED. SCV rates ranged widely between 9–83% depending on the duration of the observation period, and differences in the inclusion and exclusion criteria, such as including first-detected versus all-comers or excluding patients on antiarrhythmic drugs or digoxin. Predictors of SCV also varied between studies. The most important determinants of SCV include short duration of AF (<24 or <48 hours versus longer duration at ED presentation, although that was not supported by all studies), low episode number (first-detected AF versus recurrent AF or previous supraventricular arrhythmias), normal atrial dimensions and absence of previous heart failure or other underlying heart diseases.3,5,25 Notably, variation between studies concerning predicting factors may also relate to relatively small patient numbers per study and different strategies when including specific variables in the prediction models. Many patients presenting at the ED with recent-onset AF may convert spontaneously if a sufficiently long observation period is used. The majority of SCVs occur within the first 24–48 hours of observation in patients with relatively short duration of symptoms at the time of presentation. Presumably this finding relates to the intrinsic patientspecific pattern of self-terminating symptomatic AF in patients reporting to the ED, i.e. long enough to cause symptoms and to be still present at the ED, yet self-terminating. This pattern of AF was recently reported as the ‘legato’ (rather than ‘staccato’) type of paroxysmal AF which in the majority of patients lasts hours.32 Patients with a long legato pattern of a day to a few days of AF are in the minority and responsible for non-spontaneous conversions seen in the ED

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setting.3,5,25 From the current data we cannot tell whether patients with ‘early’ SCV have a different risk factor profile or different mechanism of termination compared to patients with ‘late’ SCV.32 More studies with continuous or intense longitudinal rhythm monitoring are needed to investigate whether those subtypes of recent-onset AF indeed exist and differ in pathophysiology, underlying risk factors, mechanism of termination or even prognosis. The duration until SCV was assessed variably, some studies taking the symptom onset into account whereas others started measuring from the beginning of the observation period (often from presentation at the ED), all until the time-point of documented SR. This may have contributed to the observed variance in SCV rates. For instance, Mattioli et al. reported a SCV rate of 77% within 48 hours and included only patients with first-onset AF and a symptom onset <6 hours. This stringent selection of patients could explain the higher conversion rate compared to the 52.6% reported by Dixon et al. and 54% reported by Lindberg et al.5,26 The latter studies included patients with first-onset AF regardless of the duration of AF with the inherent chance to also include a significant subset of patients with longer lasting episodes, in turn responsible for non-conversion even after long observation times up until 48 hours. Whether a more exact documentation of the actual AF duration (e.g. by continuous rhythm monitoring or using the onset of symptoms as a surrogate of AF onset) would reveal a more detailed classification of the AF subtype, and whether this will explain the variance in SCV rates warrants further study. None of the studies provided data on patient-reported self-termination or on a previously recognised pattern of SCV in those who had experienced SCVs of symptomatic AF in the past. Many patients with recent-onset AF are likely to have experienced previous selftermination and will experience self-termination in the future. Knowing that the pattern may be quite constant, such information could quite robustly guide the choice between early cardioversion and a wait-and-see approach. The majority of the included studies evaluated SCV during a hospitalised observation period and did not report safety concerns. Only three studies evaluated a wait-and-see approach which included sending patients home while still in AF.4,8,29 Although those studies

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Clinical Arrhythmias were not powered to assess safety, complications were infrequent and similar when compared to active cardioversion.8 Regardless of the choice of rate or rhythm control for the acute management, early diagnostics and treatment of cardiovascular and non-cardiovascular risk factors is an important component of AF management and can help to maintain sinus rhythm and reduce AF burden. A wait-and-see approach may enhance systematic identification of risk factors and concomitant conditions, since it shifts the focus away from acute rhythm control strategies. A better refinement of determinants of SCV and a categorical classification of patients in different subtypes of recent-onset AF will be crucial to allow a personalised guidance of a wait-and-see approach, which may be a good alternative to acute cardioversion in the management of recent-onset AF. This wait-and-see approach consisting of reassurance and pharmacological rate control at home, reduces the heart rate and complaints of AF, which may improve haemodynamics and enhance atrial electrophysiology and, in turn, enhance conversion to sinus rhythm. Note that in patients with AF >48 hours and considered for an elective cardioversion, SCV can still occur, which can improve characterisation of patients concerning their AF being (non-)selfterminating.33 This improved patient characterisation can guide personalised future long-term rhythm control therapies such as pill-inthe-pocket therapy or ablation therapy. Besides this, a better identification of patients with (early) SCV can reduce future visits to the ED. Patients can experience that their arrhythmia terminates spontaneously which can improve self-management in case of recurrent episode of AF, and it also reduces overtreatment. During a short-term follow-up of 4 weeks in patients with recent-onset AF, no difference was seen between early cardioversion and a wait-and-see approach in terms of recurrent episodes of AF, time to first recurrence

Kirchhof P, Benussi S, Kotecha D, et al. 2016 ESC guidelines for the management of atrial fibrillation developed in collaboration with EACTS. Eur Heart J 2016;37:2893–962. https://doi.org/10.1093/eurheartj/ehw210; PMID: 27567408. 2. January CT, Wann LS, Alpert JS, et al. 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillatio. J Am Coll Cardiol 2014;64:e1–76. https://doi.org/10.1016/j. jacc.2014.03.022; PMID: 24685669. 3. Danias P, Caulfield T, Weigner M, Silverman DWM. Likelihood of spontaneous conversion of atrial fibrillation to sinus rhythm. J Am Coll Cardiol 1998;31:588–92. https://doi.org/10.1016/S07351097(97)00534-2; PMID: 9502640. 4. Doyle B, Reeves M. “Wait and see” approach to the emergency department cardioversion of acute atrial fibrillation. Emerg Med Int 2011;2011:545023. https://doi.org/10.1155/2011/545023; PMID: 22145078. 5. Lindberg S, Hansen S, Nielsen T. Spontaneous conversion of first onset atrial fibrillation. Intern Med J 2012;42:1195–9. https://doi.org/10.1111/j.1445-5994.2011.02600.x; PMID: 21981314. 6. Geleris P, Stavrati A, Afthonidis H, et al. Spontaneous conversion to sinus rhythm of recent (within 24 hours) atrial fibrillation. J Cardiol 2001;37:103–7. PMID: 11255692. 7. Cotter G, Blatt A, Kaluski E, et al. Conversion of recent onset paroxysmal atrial fibrillation to normal sinus rhythm: the effect of no treatment and high-dose amiodarone. A randomized, placebo-controlled study. Eur Heart J 1999;20:1833–42. https:// doi.org/10.1053/euhj.1999.1747; PMID: 10581142. 8. Pluymaekers NAHA, Dudink EAMP, Luermans JGLM, et al. Early or delayed cardioversion in recent-onset atrial fibrillation. New Engl J Med 2019;380:1499–508. https://doi.org/10.1056/ NEJMoa1900353; PMID: 30883054. 9. Higgins J, Green S. Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0. Glasgow: The Cochrane Collaboration, 2011. 10. Sterne JA, Hernán MA, Reeves BC, et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ 2016;355:i4919. https://doi.org/10.1136/bmj. i4919; PMID: 27733354. 11. Scheuermeyer FX, Grafstein E, Stenstrom R, et al. Thirty-day and 1-year outcomes of emergency department patients with atrial fibrillation and no acute underlying medical cause. Ann Emerg Med 2012;60:755–65.e2. https://doi.org/10.1016/j.

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and quality of life. No data is available on the long-term effects and the progression of atrial substrate.

Conclusion There is a large variation in SCV rate, duration until SCV and determinants of SCV reported in the literature mainly due to differences in duration of the observation period, differences in inclusion and exclusion criteria and different variables used in the prediction models. Future studies are needed to investigate the optimal waiting period in a wait-and-see approach, to define different subtypes of recent-onset AF and to assess the long-term consequences of a wait-and-see approach on the progression of atrial remodelling.

Clinical Perspective • Many patients presenting at the emergency department with recent-onset AF convert spontaneously to sinus rhythm. • Spontaneous conversion (SCV) rates range widely between 9–83%, with higher reported rates with short fibrillation duration, low episode number, normal atrial size, and absence of underlying cardiovascular disease on admission, as well as a longer waiting time until active cardioversion. • Appropriate selection of patients with a high likelihood of early SCV is key to a wait-and-see approach and may help to avoid acute intervention and therefore lower healthcare costs. • Future studies should investigate the optimal waiting time in a wait-and-see approach, evaluate the usefulness of an algorithm for prediction of early conversion incorporating categorical subtypes of recent-onset AF, and assess consequences of a wait-and-see approach for progression of atrial remodelling.

annemergmed.2012.05.007; PMID: 22738681. 12. Perrea DN, Ekmektzoglou KA, Vlachos IS, et al. A formula for the stratified selection of patients with paroxysmal atrial fibrillation in the emergency setting: a retrospective pilot study. J Emerg Med 2011;40:374–9. https://doi.org/10.1016/j. jemermed.2008.02.062; PMID: 18829204. 13. Vinson DR, Hoehn T, Graber DJ, Williams TM. Managing emergency department patients with recent-onset atrial fibrillation. J Emerg Med 2012;42:139–48. https://doi. org/10.1016/j.jemermed.2010.05.017; PMID: 20634022. 14. Hohnloser SH, Dorian P, Straub M, et al. Safety and efficacy of intravenously administered tedisamil for rapid conversion of recent-onset atrial fibrillation or atrial flutter. J Am Coll Cardiol 2004;44:99–104. https://doi.org/10.1016/j.jacc.2004.03.047; PMID: 15234416. 15. Capucci A, Boriani G, Botto GL, et al. Conversion of recentonset atrial fibrillation by a single oral loading dose of propafenone or flecainide. Am J Cardiol 1994;74:503–5. https:// doi.org/10.1016/0002-9149(94)90915-6; PMID: 8059737. 16. Boriani G, Biffi M, Capucci A, et al. Oral propafenone to convert recent-onset atrial fibrillation in patients with and without underlying heart disease. A randomized, controlled trial. Ann Intern Med 1997;126:621–5. https://doi. org/10.7326/0003-4819-126-8-199704150-00006; PMID: 9103129. 17. Capucci A, Lenzi T, Boriani G, et al. Effectiveness of loading oral flecainide for converting recent-onset atrial fibrillation to sinus rhythm in patients without organic heart disease or with only systemic hypertension. Am J Cardiol 1992;70:69–72. https://doi.org/10.1016/0002-9149(92)91392-H; PMID: 1615873. 18. Intravenous digoxin in acute atrial fibrillation. Results of a randomized, placebo-controlled multicentre trial in 239 patients. The Digitalis in Acute Atrial Fibrillation (DAAF) Trial Group. Eur Heart J 1997;18:649–54. https://doi.org/10.1093/ oxfordjournals.eurheartj.a015311; PMID: 9129897. 19. Choudhary MB, Holmqvist F, Carlson J, et al. Low atrial fibrillatory rate is associated with spontaneous conversion of recent-onset atrial fibrillation. Europace 2013;15:1445–52. https://doi.org/10.1093/europace/eut057; PMID: 23515337. 20. Bellandi F, Dabizzi RP, Cantini F, et al. Intravenous propafenone: efficacy and safety in the conversion to sinus rhythm of recent onset atrial fibrillation – a single-blind placebocontrolled study. Cardiovasc Drugs Ther 1996;10:153–7. https://

doi.org/10.1007/BF00823593; PMID: 8842507. 21. Galve E, Rius T, Ballester R, et al. Intravenous amiodarone in treatment of recent-onset atrial fibrillation: results of a randomized, controlled study. J Am Coll Cardiol 1996;27:1079– 82. https://doi.org/10.1016/0735-1097(95)00595-1; PMID: 8609324. 22. Azpitarte J, Alvarez M, Baun O, et al. Value of single oral loading dose of propafenone in converting recent-onset atrial fibrillation. Results of a randomized, double-blind, controlled study. Eur Heart J 1997;18:1649–54. https://doi.org/10.1093/ oxfordjournals.eurheartj.a015146; PMID: 9347277. 23. Hassan S, Slim AM, Kamalakannan D, et al. Conversion of atrial fibrillation to sinus rhythm during treatment with intravenous esmolol or diltiazem: a prospective, randomized comparison. J Cardiovasc Pharmacol Ther 2007;12:227–31. https://doi. org/10.1177/1074248407303792; PMID: 17875950. 24. Falk RH, Knowlton AA, Bernard SA, et al. Digoxin for converting recent-onset atrial fibrillation to sinus rhythm. A randomized, double-blinded trial. Ann Intern Med 1987;106:503–6. https:// doi.org/10.7326/0003-4819-106-4-503; PMID: 3548521. 25. Dell’Orfano JT, Patel H, Wolbrette DL, et al. Acute treatment of atrial fibrillation: spontaneous conversion rates and cost of care. Am J Cardiol 1999;83:788–90. https://doi.org/10.1016/ S0002-9149(98)00993-X; PMID: 10080441. 26. Dixon BJ, Bracha Y, Loecke SW, et al. Principal atrial fibrillation discharges by the new ACC/AHA/ESC classification. Arch Intern Med 2005;165:1877–81. https://doi.org/10.1001/ archinte.165.16.1877; PMID: 16157832. 27. Mattioli AV, Bonatti S, Zennaro M, Mattioli G. The relationship between personality, socio-economic factors, acute life stress and the development, spontaneous conversion and recurrences of acute lone atrial fibrillation. Europace 2005;7:211–20. https://doi.org/10.1016/j.eupc.2004.02.006; PMID: 15878557. 28. Mattioli AV, Vivoli D, Borella P, Mattioli G. Clinical, echocardiographic, and hormonal factors influencing spontaneous conversion of recent-onset atrial fibrillation to sinus rhythm. Am J Cardiol 2000;86:351–2. https://doi. org/10.1016/S0002-9149(00)00933-4; PMID: 10922452. 29. Abadie BQ, Hansen B, Walker J, et al. Likelihood of spontaneous cardioversion of atrial fibrillation using a conservative management strategy among patients presenting to the emergency department. Am J Cardiol 2019;124:1534–9.

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Spontaneous Conversion to Sinus Rhythm of Recent-onset AF https://doi.org/10.1016/j.amjcard.2019.08.017; PMID: 31522772. 30. Lip GY, Nieuwlaat R, Pisters R, et al. Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: the euro heart survey on atrial fibrillation. Chest 2010;137:263–72. https://doi.org/10.1378/chest.09-1584; PMID: 19762550. 31. Gage BF, Walraven Cv, Pearce L, et al. Selecting patients with

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atrial fibrillation for anticoagulation. Circulation 2004;110:2287– 92. https://doi.org/10.1161/01.CIR.0000145172.55640.93; PMID: 15477396. 32. Wineinger NE, Barrett PM, Zhang Y, et al. Identification of paroxysmal atrial fibrillation subtypes in over 13,000 individuals. Heart Rhythm 2019;16:26–30. https://doi. org/10.1016/j.hrthm.2018.08.012; PMID: 30118885. 33. Klein AL, Grimm RA, Murray RD, et al. Use of transesophageal

echocardiography to guide cardioversion in patients with atrial fibrillation. N Engl J Med 2001;344:1411–20. https://doi. org/10.1056/NEJM200105103441901; PMID: 11346805. 34. Boriani G, Biffi M, Capucci A, et al. Oral loading with propafenone: a placebo-controlled study in elderly and nonelderly patients with recent onset atrial fibrillation. Pacing Clin Electrophysiol 1998;21:2465–9. https://doi. org/10.1111/j.1540-8159.1998.tb01202.x; PMID: 9825368.

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Electrophysiology & Ablation

Anisotropic Cardiac Conduction Irum Kotadia,1,2 John Whitaker,1,2 Caroline Roney,1 Steven Niederer,1 Mark O’Neill,1,2 Martin Bishop1 and Matthew Wright1,2 1. School of Biomedical Engineering and Imaging Sciences, King’s College, London, UK; 2. Guy’s and St Thomas’ NHS Foundation Trust, London, UK

Abstract Anisotropy is the property of directional dependence. In cardiac tissue, conduction velocity is anisotropic and its orientation is determined by myocyte direction. Cell shape and size, excitability, myocardial fibrosis, gap junction distribution and function are all considered to contribute to anisotropic conduction. In disease states, anisotropic conduction may be enhanced, and is implicated, in the genesis of pathological arrhythmias. The principal mechanism responsible for enhanced anisotropy in disease remains uncertain. Possible contributors include changes in cellular excitability, changes in gap junction distribution or function and cellular uncoupling through interstitial fibrosis. It has recently been demonstrated that myocyte orientation may be identified using diffusion tensor magnetic resonance imaging in explanted hearts, and multisite pacing protocols have been proposed to estimate myocyte orientation and anisotropic conduction in vivo. These tools have the potential to contribute to the understanding of the role of myocyte disarray and anisotropic conduction in arrhythmic states.

Keywords Anisotropy, anisotropic conduction, arrhythmias, pacing, conduction velocity Disclosure: The research was supported by the National Institute for Health Research (NIHR) Clinical Research Facility at Guy’s and St Thomas’ NHS Foundation Trust and NIHR Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. The views expressed are those of the authors, and not necessarily those of the NHS, the NIHR or the Department of Health. JW is supported by a Medical Research Council UK Clinical Research Training Fellowship (grant code: MR/N001877/1). The authors have no other conflicts of interest to disclose. Received: 15 February 2020 Accepted: 9 October 2020 Citation: Arrhythmia & Electrophysiology Review 2020;9(4):202–10. DOI: https://doi.org/10.15420/aer.2020.04 Correspondence: John Whitaker, School of Biomedical Engineering and Imaging Sciences, King’s College London, Strand, London WC2R 2LS, UK. E: john.whitaker@kcl.ac.uk Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for noncommercial purposes, provided the original work is cited correctly.

Anisotropy is the property of directional dependence. In cardiac tissue, conduction velocity (CV) is anisotropic, that is, the magnitude of CV depends on the direction of a wave of activation. Anisotropic conduction facilitates prompt and synchronised cardiac chamber activation. In disease states, anisotropic conduction is implicated in the genesis of pathological arrhythmias. It can determine unidirectional conduction block (UCB), which is a prerequisite for re-entry, the likelihood of propagation of ectopic foci of activation and the motion and stability of re-entrant activation patterns. The response of cardiac tissue to treatment, such as pacing, and the ability of a high-voltage stimuli to terminate fibrillation through the generation of virtual electrodes are dependent on the anisotropic properties of the myocardium.1,2 Therefore, anisotropic conduction is an important property of cardiac tissue, disease and response to treatment of arrhythmias. In the present study, we discuss the mechanisms determining anisotropic conduction within cardiac tissue, the contribution of anisotropic conduction to the mechanisms underlying pathological re-entrant arrhythmias and the reported options for assessing anisotropy.

speed of conduction perpendicular to the myocytes (transverse CV).3,4 A further layer of complexity arises when conductivity is considered in three dimensions. At a cellular level, myocytes are transversally isotropic, that is, CV is equal in any direction in the plane perpendicular to the principal axis of the myocyte; however, this does not hold true when conduction is considered at the tissue scale, where the laminar structure of the tissue results in orthotropic conduction, that is, variation in conductivity in each of the three dimensions.5,6 Much of the literature pertaining to anisotropic conduction makes the assumption, often implicitly, of transverse isotropy of conduction, which must be considered a limitation in light of these data regarding orthotropy. However, having acknowledged this limitation, the consideration of anisotropy in two dimensions yields important data. The ratio between the maximum and minimum CV observed is known as the ‘anisotropy ratio’ (ARCV) and indicates the magnitude of CV anisotropy within that tissue. Other characteristics of cardiac tissue also demonstrate anisotropy, including the conductivity of tissue (a parameter that is frequently considered in cardiac modelling studies) and the physical structure of the tissue.7,8

Factors Responsible for Anisotropic Conduction CV varies in different locations within the heart. The magnitude of CV within cardiac tissue demonstrates directional dependence, that is, anisotropy, with the maximum speed of conduction being observed parallel to the direction of myocytes (longitudinal CV) and the slowest

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Several factors have been identified that contribute to CV anisotropy. These include cell size, cell shape and gap junction distribution. Various experimental setups have been established to attempt to separately measure longitudinal and transverse CV.9 One of the challenges in

Anisotropic Cardiac Conduction doing so has been to separate the impact of intrinsic tissue anisotropy from the impact of wavefront curvature, which has a profound effect on CV and is influenced by anisotropy.10 The impact of wavefront curvature presents significant challenges for the assessment of ARCV in vivo.9 Along with the complex 3D alignment of myocytes within the human heart, these challenges have prevented routine assessment of ARCV within intact cardiac chambers.11

Figure 1: Resistor Network Demonstrating a 2D Bidomain Model

Extracellular

Cell Shape and Size Cardiac myocytes are elongated cells with a cylindrical shape. They are oriented in bundles of parallel cells that then form into laminar sheets, rendering the microstructural architecture of human cardiac tissue anisotropic.12 Early experimental observations on the anisotropic nature of cardiac conduction noted myocyte orientation as the principal determinant of the direction of the maximal CV observed.13 In addition to experimentally demonstrating anisotropic conduction of the myocardium, Clerc also highlighted the presence of unequal resistivity anisotropy ratios in the intra- and extra-cellular domains, which was confirmed in subsequent studies.13,14 This key observation prompted further experimental and theoretical work in the coming years with significant implications for understanding complex propagation and polarisation patterns in 2D and 3D cardiac tissue, and was instrumental in the development of the bidomain model of cardiac electrophysiology (Figure 1).15–19 As demonstrated in Figure 2, a wave of conduction travelling perpendicular to the principal axis of a myocyte (transverse direction) will meet a greater number of cellular interfaces per unit length than will be encountered in the direction parallel to myocyte direction (longitudinal direction). Cytoplasmic conduction along the length of the myocyte is rapid with low resistance, whereas low-velocity, high-resistance conduction occurs across the gap junctions that electrically couple adjacent cells. This distinction is an important determinant of CV anisotropy. When isolated single chains of myocytes are considered, conduction slowing at cellular junctions results in discontinuous or saltatory conduction, and >50% of conduction time may occur at the small distance across gap junctions, with the remainder of conduction time being due to cytoplasmic conduction.20,21 However, Figure 2 further demonstrates the reduction of this effect in 2D laminar tissue due to lateral cell connections that permit divergence of the local excitatory current around the junction, effectively speeding up conduction across the cellular interface.21 Considering propagation in the longitudinal direction, it is also evident that a depolarising wave travelling in a longer cell will encounter a lower frequency of cellular interfaces than a wave travelling in a shorter cell, with a consequent increase in longitudinal CV in longer cells, and therefore, anisotropy. Experimental and modelling studies indicate that pathological changes in cell shape and size affecting the length–width ratio will have a consequent impact on anisotropy of conduction.22 Computational simulation of the activation of representative blocks of tissue confirms maximum propagation speed along the axis of myocytes, but also reveals additional levels of complexity to propagation patterns in 3D.5,6

Myocardial Fibrosis Myocardial fibrosis is a common consequence of many human cardiac pathologies, and may be classified as reactive fibrosis, which is the result of increased collagen deposition, or replacement fibrosis (‘scar’), in which collagen replaces injured myocytes.23,24 Collagen deposition may be in the form of discrete regions of dense collagen without any viable myocytes (‘compact’ fibrosis), an increase in the

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Membrane =

+ Intracellular y x

The x and y planes are represented by the intracellular and extracellular spaces (bi-domains) in the form of a 2D resistor network. These planes are coupled vertically by resistors and capacitors that represent the membrane and together form a model for a single layer of cells. However, resistors in the x and y directions may be unequal. Anisotropic ratio in the extracellular domain is estimated at 2, compared with the intracellular domain that is estimated at 10. Source: Roth et al. 1992.19 Reproduced with permission from Springer Nature.

extracellular matrix (‘interstitial’ fibrosis) or due to an intermingling of myocytes and stretches of collagen fibres.24 Different patterns of fibrosis appear to affect conduction and conduction anisotropy differently. Interstitial fibrosis, predominantly separating the longitudinal cellular bundles, results in the most pronounced decrease in transverse CV in the human heart, and an increase in ARCV.25 In this situation, enhanced microstructural discontinuities (observed in an animal model under experimental conditions) result in dissociated conduction with longer conduction times and a zigzag pattern, as well as promoting non-uniform action potential properties.26–28 These characteristics of transverse conduction are due to the tortuous route that a propagating wave must traverse, in addition to electrical uncoupling in the transverse direction, due to increased interstitial resistance to current flow.29 These changes amplify the ARCV of tissue, which favours the initiation of re-entry and will be discussed later.4

Gap Junctions Gap junctions electrically couple adjacent cells by behaving as selectively permeable ion channels. The conductivity of gap junctions (a factor of the density of gap junctions and their individual behaviour) is a major determinant of intercellular resistivity. This in part determines CV, affecting the extent of delay encountered at the intercellular junction. Gap junctions cluster at the longitudinal end of myocytes, but are also found along the length of cells, electrically coupling cells in the transverse direction.30 Pathologically, the redistribution of gap junctions can result in a decrease in density of gap junctions at the longitudinal cell ends, and an increase along the shaft of the cells, known as ‘lateralisation’.30 Furthermore, an overall reduction in the expression of gap junctions can be seen in ventricular tissue. These findings have been observed in a range of pathological processes associated with arrhythmia, including dilated cardiomyopathy and ischaemic cardiomyopathy.31,32 When the gap junction protein Cx43 was reduced by 95% in a murine experimental model, ventricular tissue demonstrated decreased CV and increased ARCV, which resulted in greater susceptibility to ventricular arrhythmias.33 Full-thickness gap junction distribution disturbance was seen in an early post-infarct canine myocardium in which ventricular tachycardia (VT) was inducible and co-localised with the central common isthmus of these VT circuits,

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Electrophysiology & Ablation Figure 2: Cellular Features that Contribute to Conduction Velocity Anisotropy in Myocardial Tissue with Long, Cylindrical Cells Longitudinal CV

Cytoplasmic conduction - Low resistance - High velocity

Longitudinal conduction: low frequency of intercellular connections

Transverse conduction: high frequency of intercellular connections Gap junctions clustered at end of cells

Divergence of excitatory current around extracellular junction

Transverse CV

Intercellular conduction - High resistance - Low velocity

Fast longitudinal conduction results from rapid, low-resistance cytoplasmic conduction interrupted by infrequent high-resistance, low-velocity intercellular conduction, which is facilitated by clustering of gap junctions at cell ends. Reduced conduction slowing at intercellular junctions results from divergence of local excitatory current around intercellular connections. Slow transverse conduction results from a high frequency of high resistance, low-velocity intercellular junctions with fewer gap junctions. CV = conduction velocity.

while only partial-thickness distribution abnormalities were observed in non-inducible hearts. In atrial tissue, genetically determined reduction in Cx40 and Cx43 function has been identified in patients with AF in the absence of any predisposing conditions. Furthermore, experimentally promoting Cx43 expression in a porcine model of AF restored CV, with a resultant decrease in susceptibility to AF.34–37 While these observations suggest that pathological changes in gap junction behaviour would be an important determinant of changes in CV and CV anisotropy in disease, other experimental evidence suggests that it has a relatively modest impact on changes in CV anisotropy.22 This may reflect an excess of gap junctions, providing a buffer that minimises the impact of redistribution and differences in function (conductivity) of the redistributed gap junctions in the pathological state. The surrogates used to identify the distribution of gap junctions (usually done through immunohistochemical analysis of the localisation of Connexin proteins) may also not accurately identify the location of the functional gap junction components.30,38 Resolving the discrepancy between the observation of remodelled gap junctions in clinical conditions associated with arrhythmia against experimental evidence suggesting a modest impact on CV with the observed changes in gap junction distribution has remained challenging. A further possible explanation may be the potentiation of changes in gap junction effects by increases in interstitial volume. In an experimental model of increased interstitial volume (which is observed in a broad range of cardiovascular pathologies), gap junction blockade resulted in slowed conduction and increased ARCV, which was associated with an increased susceptibility to arrhythmia that was not seen in controls.39,40 Outstanding issues remain surrounding the magnitude of the effect in gap junction remodelling and other conditions required to unmask the arrhythmogenic effects. However, current data suggest that the consequence of changes in gap junction function in disease predispose to arrhythmia in a range of conditions.

Functional Determinants of Anisotropy In addition to structural determinants of CV and ARCV, there are important functional contributors to these characteristics. The high density of sodium channels found at the intercalated discs between myocytes represents an important modifier of conduction at the intercalated discs, and thus, conduction along the axis of the myocyte.41,42 Activation of the

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sympathetic nervous system increases longitudinal CV, but not transverse CV, therefore increasing ARCV in a porcine ventricular myocardium. This effect was shown to be abolished by gap junction blockade, demonstrating the importance of the functional modulation of anisotropic conduction.43 The clinical significance of alterations in sodium channel function is demonstrated through the loss of function mutations of the sodium channel protein type 5 subunit alpha (SCN5A) gene, resulting in reduced CV, as is seen in Brugada and Lev–Lenègre syndromes. Prior in vivo studies have demonstrated that reduced CV in the context of normal heterogeneities within the right ventricle predisposes to vulnerabilities of re-entrant tachycardias that may precipitate ventricular fibrillation, and consequently, sudden cardiac death.44 More recently, a reduction in the number of cardiac sodium channels was shown using immunocytochemistry of cardiac tissue from patients with a diagnosis of arrhythmogenic right ventricular cardiomyopathy (ARVC).45 The same study also demonstrated reduced signal of the gap junction protein Cx43, previously discussed as an important determinant of changes in CV and CV anisotropy in disease. These observations likely contribute to the increase in arrhythmia vulnerability seen in ARVC.

Variations in Anisotropic Ratio and Conduction Velocity in the Heart Atrium Specific regions of preferential conduction within the atria appear to be optimised for conducting a wave of depolarisation to facilitate an orderly sequence of activation in the atria. These regions include the crista terminalis, running from the sinus node to the eustachian valve and giving off trabeculations that facilitate right atrial activation and left atrial activation via Bachmann’s bundle.46 These regions demonstrate both faster CV and increased ARCV (in some cases transverse conduction is absent) than in surrounding atrial tissue.47,48 ARCV of up to 10 has been recorded in these regions.49 In the crista terminalis, pronounced anisotropy fulfils the functional requirement of permitting appropriate timing of atrial activation. ARCV in atrial body tissue has been less commonly reported, but in preclinical and clinical experiments where it has been quantified, it is lower than that recorded in either the crista terminalis or Bachmann’s bundle.50,51

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Anisotropic Cardiac Conduction Figure 3: Activation Maps of the Epicardial Surface of The Anterior Left Ventricle Following a Premature Extra-stimulus from the Base of the Left Ventricle A

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Grey line indicates a line of unidirectional block that has occurred at the infarct border zone. A: Activation map demonstrates bifurcation of the wavefront of depolarisation around the line of unidirectional block, which pivots around the line of unidirectional block to activate it from the opposite direction. B: Depolarisation of the adjacent tissue that has now had time to repolarise, and which completes the first cycle of re-entry. C: Resulting ventricular tachycardia that ensues. Source: Ciaccio et al. 2015.64 Reproduced from Elsevier under a Creative Commons (CC BY) licence.

Myocytes in the heart demonstrate patterns of organisation that may be seen when tissue is examined macroscopically.

Ventricular Tissue The highest speeds of conduction found within the heart are in HisPurkinje tissue.52 These insulated cells are optimised for rapid longitudinal conduction of a depolarising wave exiting the atrioventricular node to a large mass of ventricular tissue.53 The rapid dispersion of a wave of activation permits synchronized ventricular contraction, obviating the need for rapid conduction between ventricular myocytes, and therefore, overcoming the relatively slow conduction between adjacent ventricular myocytes. The insulation of these tracts by a fibrous sheath prevents dispersion of current in a transverse direction (beyond the strand enclosed in a fibrous sheath).54 In contrast, CV in ventricular tissue is among the slowest within the heart and demonstrates a correspondingly low anisotropy ratio (ARCV). Under experimental conditions, mammalian ventricular tissue has a maximum longitudinal CV around 0.5–0.6 ms–1, whereas transverse CV is estimated between 0.15 and 0.2 ms–1, and thus the anisotropy ratio is between 2.5 and 4.13,55 In ventricular tissue, myocyte orientation seems to be optimised for mechanical efficiency, rather than for rapid dispersion of a wave of activation, which is instead facilitated by the cardiac conduction system tissue that rapidly disperses the wave of depolarisation, resulting in synchronised ventricular contraction.56

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Anisotropic Conduction as a Substrate for Arrhythmia Re-entry is a key mechanism underlying the majority of clinically important arrhythmias responsible for affecting patient prognosis or symptom burden. This may take the form of a stable and mappable reentrant circuit, such as those seen in post-infarct VT, or may be a complex interaction of one or more unmappable re-entrant circuits, such as those seen in AF, the exact nature of which remains to be definitively established. Despite ongoing uncertainty surrounding the activation patterns in AF, it is acknowledged that re-entrant activation of the atria plays a key role.

Variations in Anisotropic Ratio and Conduction Velocity in the Pathological Heart Examples of enhanced ARCV in pathological conditions have been reported, including during right atrial assessment in patients with chronically stretched atria secondary to mitral stenosis, who demonstrated increased ARCV at the crista terminalis compared to controls. This represents an example of pathological substrate remodelling in patients with a condition associated with a high incidence of AF.57 A similar increase in CV anisotropy has been observed in atrial tissue from patients undergoing surgical AF ablation.58 Optical mapping has demonstrated heterogeneously decreased CV and increased ARCV within left ventricular tissue from end-stage heart failure patients, as well

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Electrophysiology & Ablation Figure 4: Immunohistochemical Analysis Demonstrating Pathological Remodelling in Arrhythmogenic Right Ventricular Dysplasia

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time or space.62 While UCB may occur in homogeneous media due to the intrinsic asymmetry of the action potential (termed ‘functional heterogeneity’), the width of the vulnerable window may be significantly expanded by heterogeneity of the electrical properties of tissue, including the availability of Na+ channels (excitability), cell-to-cell coupling (connectivity) and the behaviour of K+ channels (repolarisation).63 Furthermore, structurally determined source–sink mismatch at the transition from a small to a large mass of excitable tissue may also give rise to UCB, as propagation fails in the direction of a rapidly expanding volume of excitable tissue.64 The anisotropic behaviour of tissue has been demonstrated to promote UCB. In post-infarct VT, re-entrant circuits may be established by the appearance of an arc of conduction block, with subsequent activation of tissue distal to the initial arc sufficiently late that it has recovered excitability and depolarisation can occur (Figure 3).65,66 If an arc of conduction block occurs in the longitudinal direction relative to myocyte orientation, that is, in the direction of maximal CV, slower conduction occurs in the transverse direction (a function of the intrinsic difference between transverse CV and longitudinal CV due to tissue anisotropy, as well as wavefront curvature introduced by the arc of block). This allows additional time for recovery of excitability of tissue distal to the arc, such that re-entry is more likely to be established than if the initial arc of conduction block was in the transverse direction.55 Similar reentrant patterns have been demonstrated in atrial tissue, identifying anisotropy of conduction as a key mechanism promoting re-entry.67 Recently, Anter et al. used high-resolution mapping of re-entrant VT circuits to show that a key substrate in the sustenance of the arrhythmia was conduction slowing at the entrance/exit of the VT isthmus.60 An important component of this was the highly curved nature of the wavefront propagation in these regions, transitioning from parallel to the faster fibre orientation (along the isthmus direction) to propagate transverse to it in order to loop back around and re-enter.60

Robustness of Conduction Merge

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Immunohistochemical analysis was performed on post-mortem biopsies from five control patients and five patients with a history of arrhythmogenic right ventricular dysplasia (ARVC). Further biopsies were taken from the right ventricular septum in 15 ARVC patients. A: Control patients. (B) Patients with ARVC. Panels show a reduction in immunoreactive signal intensity of Cx43 (left), NaV1.5 (middle), and PKG (right) at the intercalated discs in ARVC patients compared with control patients. N-cadherin (NCad) is a cell-adhesion molecule that has no known human mutations and resides at the intercalated discs. Samples were double stained. Double-labelling was performed with NCad to validate the results. Source: Noorman et al. 2013.45 Reproduced with permission from Elsevier.

as the increased incidence of transverse conduction block, reflecting substrate changes that may contribute to the increased incidence of reentrant arrhythmia in this group.59 High-resolution activation mapping of post-infarct VT circuits in a porcine model suggest that extreme slowing of conduction perpendicular to the isthmus is present, with relatively normal CV within the isthmus, in a pronounced example of anisotropic conduction during a sustained arrhythmia.60

Unidirectional Conduction Block UCB is a prerequisite for the development of re-entry.61 A variety of mechanisms may give rise to UCB, including functional asymmetry of the cardiac action potential, local heterogeneity of tissue excitability and discontinuities in tissue structure. Simulation studies demonstrate that local excitation within a homogeneous excitable media may interact with the tail of a preceding wave of depolarisation and result in UCB. In order to do so, the local excitation must be critically timed to fall within a vulnerable window, which may be defined in terms of membrane voltage,

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The effect of pathological remodelling on the robustness of conduction, quantified as ‘safety factor’, and indicating under what circumstances conduction will fail, remains uncertain, although alterations in mechanical and electrical coupling of cells at the intercalated discs have been postulated as potential mechanisms. Figure 4 demonstrates disturbance in the immunoreactive signals of connexin 43 and sodium channels following pathological remodelling of the right ventricle in patients ARVC. These changes have previously been found to be associated with reduced CV, and have an increased susceptibility to the initiation and perpetuation of arrhythmias.45 Theoretical studies and experimental data suggest that uncoupling cells in the transverse direction may result in extremely slow yet robust conduction, an effect which would promote the development of re-entry.49,68 Other investigators have demonstrated more robust conduction in the longitudinal direction under experimental conditions as a result of cellular uncoupling.69 In fibrotic human left ventricular tissue, transverse conduction block was seen more frequently than longitudinal block.59 Differences in methodology may explain some of the discrepancies in the results, and it is possible that different mechanisms of remodelling have different effects on transverse conduction safety. At present, the existence of a consistent effect of pathological remodelling on the differences in robustness of conduction in the longitudinal versus the transverse direction remains uncertain.

Anisotropic Re-entry In addition to UCB, re-entrant circuits characteristically require a region of inexcitability for the re-entrant wave to circumnavigate. This may take the form of a fixed anatomic obstacle to conduction, such as a valve or blood

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Anisotropic Cardiac Conduction vessel, or if occurring in the absence of such an obstacle, can be termed ‘functional re-entry’. Functional re-entrant circuits have been observed experimentally.70 Originally, this was explained by the ‘leading circle’ concept, whereby the central region of the re-entry circuit is activated by multiple wavelets branching from the main re-entry circuit (Figure 5). Experimental data indicate that this functional re-entry may arise due to heterogeneity in the refractory properties of the tissue, but may also arise in the absence of marked differences in refractoriness, exclusively due to anisotropic tissue properties of conduction.28,71 Modelling studies have suggested that functional re-entry within the pulmonary veins may underlie rapid activation that results in paroxysms of AF, which in the present study was dependent on heterogeneous and anisotropic conduction within the pulmonary veins.72,73 CV anisotropy therefore represents a distinct mechanism underlying sustained functional reentry. In an experimental setting, the re-entrant path of these anisotropic re-entrant circuits is closely related to myocyte orientation.74

Figure 5: Functional Re-entry Circuit Demonstrating the Leading Circle Concept

Spiral Wavebreak Junctions in myocyte orientation are observed at typical places in the atria (an example of myocardial arrangement is shown in Figure 6), and represent locations where the propagation of a spreading wavefront is subject to changes in CV and anisotropy.75 In 3D tissue, spiral waves manifest as a scroll wave or vortex. The break-up of a scroll wave is a potential mechanism underpinning a transition from a tachycardia to fibrillation. The centre of the scroll or filament forms a line through the centre of the scroll analogous to the phase singularity in 2D spiral waves. The relationship between CV anisotropy and filaments has predominantly been investigated using mathematical models. Mathematical formulations and simulation studies have shown that the motion of scroll wave filaments is determined by local anisotropy.76 Simulations have predicted that tissue anisotropy promotes filament motion towards the apex in the ventricles.77 In addition, simulations have shown that spatially varying anisotropy promotes both bending of the filament and slow wave speed due to curvature, which can contribute to wavebreak.78 The stability and location of scroll waves in cardiac tissue are highly dependent on tissue CV anisotropy. Spiral waves (in 2D) or scroll waves (in 3D) are examples of functional re-entrant circuits that are thought to be involved in the mechanisms underlying AF and VF, and have been observed more frequently in ventricular locations at abrupt junctions of myocyte orientations.79–82 Furthermore, junctions where myocytes meet in different directions are regions that favour the development of UCB, as well as promoting wavebreak, which is observed in fibrillation and may be a mechanism by which fibrillation is sustained.83,84 These considerations illustrate the importance of myocyte orientation and anisotropic conduction properties in the development and maintenance of functional myocardial re-entrant circuits, and suggest mechanisms that may promote fibrillation.

Ectopic Foci In addition to promoting re-entry, anisotropy of conduction has been implicated in arrhythmia initiation through the propagation of wavefronts from ectopic foci of depolarisation. In simulation studies, a critical degree of cellular uncoupling related anisotropy, for example, that which may be seen with myocardial fibrosis, will permit propagation of an ectopic wavefront, which would otherwise extinguish.85 Ectopic foci are well known to play a crucial role in the initiation of clinical arrhythmias, including AF.73

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Black arrows represent the re-entry circuit, and blue lines represent centripetal wavelets activating the central region of the circuit. Wavelets are extinguished prior to passing the centre point, and are therefore, unable to shortcut the circuit.

Outstanding Questions CV anisotropy is a characteristic of myocardial tissue. The speed of conduction is reliably greatest in the direction parallel to the longitudinal orientation of myocytes. As such, there is an intimate duality between conduction anisotropy and myocyte orientation. Both CV and ARCV change following pathological tissue remodelling and are associated with pro-arrhythmic states. Uncertainty remains regarding the magnitude of the change, which is likely to depend on the location and pathological process considered. There are compelling explanations and experimental evidence demonstrating mechanisms by which changes in anisotropy may promote re-entry. Some of the discrepancies in the available evidence relate to the experimental models used. Most data have been collected in experimental models due to the difficulty of assessing both myocyte orientation and anisotropy in vivo, and as such, there is residual uncertainty as to the translatability of specific experimental results to human physiology. Recently, an estimation of human atrial myocyte orientation in ex vivo hearts has been made, establishing that through the use of diffusion-tensor MRI (DT-MRI), myocyte orientation of both epicardial and endocardial atrial tissue layers may be estimated, which was previously only possible through direct tissue examination.86 Furthermore, recent reports have successfully demonstrated that DT-MRI may be reproducibly applied in vivo. It has been used to demonstrate myocyte disarray in hypertrophic cardiomyopathy patients and has been correlated with the incidence of ventricular arrhythmias.87,88 In this case, decreased structural anisotropy (when averaged over the imaged voxel volume), representing myocyte disarray, was associated with an increased incidence of ventricular arrhythmias. Importantly, the identification of decreased averaged structural anisotropy must be distinguished from the conduction characteristics of myocardium in hypertrophic cardiomyopathy, which remains highly anisotropic in fibrotic areas.25 It is hoped that DT-MRI application to other pathologies associated with myocyte disarray and arrhythmias will follow and further define the

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Electrophysiology & Ablation Figure 6: Atrial Fibre Atlas and Activation Pattern A

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A: Atrial fibre atlas constructed from a high-resolution diffusion tensor MRI dataset from which myocyte orientation (grey lines) was derived. In an electrophysiological simulation, wavefronts are seen propagating up and down the posterior wall. Roof of the atrium, which contains myocytes oriented in parallel, demonstrates rapid wavefront progression. Lower posterior wall, in which there is myocyte disarray, demonstrates slower and less uniform progression of the wavefront. B: Same model as A is shown. In this simulation, the model was paced at a cycle length of 155 ms for five beats from the right superior pulmonary vein rim during sinus rhythm to represent a train of ectopics. The figure shows the activation map of the fifth ectopic beat, which leads to spiral wave re-entry. Planar wavebreak leading to re-entry at the junction of the left atrium and right superior pulmonary vein is seen.

structural characteristics of the myocardium in pathological conditions. An alternative approach to in vivo imaging has been proposed to establish both myocyte orientation and ARCV in the human atrium using activation patterns during pacing from multiple sites in a process designed to overcome the challenges of wavefront curvature and propagation of wavefronts non-parallel or perpendicular to myocyte orientation (Figure 6).89 If validated, such a tool may facilitate the establishment of endocardial atrial myocyte orientation variability, as well as the key functional aspect of change in ARCV under different pathological conditions. Further data regarding typical myocyte orientation and ARCV with different pathological states, either through structural imaging or a functional assessment, may contribute to a greater understanding of arrhythmia mechanisms responsible for re-entrant arrhythmias, including AF. Furthermore, such information may be helpful to predict, and possibly guide, the effect of specific anti-arrhythmic medication in the context of defined changes in substrate behaviour. Such an assessment may also allow the identification of regions, for example, those with markedly increased anisotropic conduction, that could be targeted for ablative therapy. Accurate information regarding myocyte orientation and CV anisotropy in an individual atrium would allow a more thorough assessment of the relationship between imaging features (e.g. late-gadolinium enhancement MRI) and functional electrophysiological behaviour, which has rarely been incorporated into previous assessments.90 It would also allow the parameterisation of patient-specific computational models that may be used to guide individualised precision therapy.

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Conclusion Myocyte orientation and CV anisotropy are fundamental tissue properties that are important determinants of susceptibility to arrhythmia. Myocyte orientation determines the direction of maximal CV. The ratio between CV in the direction of maximal and minimal CV, the ARCV, represents a determinant of tissue susceptibility to re-entry through the promotion of UCB. In addition, anisotropic conduction itself represents a mechanism that may explain the existence of functional re-entry within cardiac tissue. Tools for establishing myocyte orientation and conduction anisotropy in vivo may address outstanding questions regarding the magnitude and mechanism underlying changes in conduction anisotropy in pro-arrhythmic pathologies.

Clinical Perspective • Tissue anisotropy is dependent on myocyte orientation. • Anisotropic myocardial conduction is enhanced in pathological states, which may contribute to arrhythmogenesis, through the promotion of abnormal focal activation, as well as functional reentrant arrhythmias. • If identifiable during clinical procedures, areas of enhanced anisotropic conduction may represent novel targets in which ablative therapy could be trialled if demonstrated to promote fibrillation.

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Sympathetic modulation of electrical activation in normal and infracted myocardium: implications for arrhythmogenesis. Am J Physiol Heart Circ Physiol 2017;312:H608–21. https://doi.org/10.1152/ ajpheart.00575.2016; PMID: 28087519. 44. Kelly A, Salerno S, Connolly A, et al. Normal interventricular differences in tissue architecture underlie right ventricular susceptibility to conduction abnormalities in a mouse model of Brugada syndrome. Cardiovasc Res 2018;114:724–36. https:// doi.org/10.1093/cvr/cvx244; PMID: 29267949.

45. Noorman M, Hakim S, Kessler E, et al. Remodeling of the cardiac sodium channel, connexin43, and plakoglobin at the intercalated disk in patients with arrhythmogenic cardiomyopathy. Heart Rhythm 2013;10:412–9. https://doi. org/10.1016/j.hrthm.2012.11.018; PMID: 23178689. 46. James TN. The internodal pathways of the human heart. Prog Cardiovasc Dis 2001;43:495–535. https://doi.org/10.1053/ pcad.2001.24598; PMID: 11431803. 47. Wagner ML, Lazzara R, Weiss RM, et al. Specialized conducting fibers in the interatrial band. Circ Res 1966;18:502–18. https:// doi.org/10.1161/01.RES.18.5.502; PMID: 5937541. 48. Li-jun J, Xue-yin L, Cong-xin H, et al. Electrophysiologic characteristics of the crista terminalis and implications on atrial tachycardia in rabbits. Cell Biochem Biophys 2012;62:267– 71. https://doi.org/10.1007/s12013-011-9290-5; PMID: 21938558. 49. Spach MS, Miller WT, Geselowitz DB, et al. The discontinuous nature of propagation in normal canine cardiac muscle. Evidence for recurrent discontinuities of intracellular resistance that affect the membrane currents. Circ Res 1981;48:39–54. https://doi.org/10.1161/01.RES.48.1.39; PMID: 7438345. 50. Maesen B, Zeemering S, Afonso C, et al. Rearrangement of atrial bundle architecture and consequent changes in anisotropy of conduction constitute the 3-dimensional substrate for atrial fibrillation. Circ Arrhythm Electrophysiol 2013;6:967–75. https://doi.org/10.1161/CIRCEP.113.000050; PMID: 23969531. 51. Morton JB, Sanders P, Vohra JK, et al. Effect of chronic right atrial stretch on atrial electrical remodeling in patients with an atrial septal defect. Circulation 2003;107:1775–82. https://doi. org/10.1161/01.CIR.0000058164.68127.F2; PMID: 12665497. 52. Kupersmith J, Krongrad E, Waldo AL. Conduction intervals and conduction velocity in the human cardiac conduction system. Studies during open-heart surgery. Circulation 1973;47:776–85. https://doi.org/10.1161/01.CIR.47.4.776; PMID: 4696799. 53. Boyden PA. Purkinje physiology and pathophysiology. J Interv Card Electrophysiol 2018;52:255–62. https://doi.org/10.1007/ s10840-018-0414-3; PMID: 30056516. 54. Ono N, Yamaguchi T, Ishikawa H, et al. Morphological varieties of the Purkinje fiber network in mammalian hearts, as revealed by light and electron microscopy. Arch Histol Cytol 2009;72:139–49. https://doi.org/10.1679/aohc.72.139; PMID: 20513977. 55. Schalij MJ, Lammers WJEP, Rensma PL, et al. Anisotropic conduction and reentry in perfused epicardium of rabbit left ventricle. Am J Physiol Heart Circ Physiol 1992;263:H1466–78. https://doi.org/10.1152/ajpheart.1992.263.5.H1466; PMID: 1279990. 56. Rijcken J, Bovendeerd PHM, Schoofs AJG, et al. Optimization of cardiac fiber orientation for homogeneous fiber strain at beginning of ejection. J Biomech 1997;30:1041–9. https://doi. org/10.1016/S0021-9290(97)00064-X; PMID: 9391871. 57. Wong CX, John B, Brooks AG, et al. Direction-dependent conduction abnormalities in the chronically stretched atria. Europace 2012;14:954–61. https://doi.org/10.1093/europace/ eur428; PMID: 22308090. 58. Krul SPJ, Berger WR, Smit NW, et al. Atrial fibrosis and conduction slowing in the left atrial appendage of patients undergoing thoracoscopic surgical pulmonary vein isolation for atrial fibrillation. Circ Arrhythm Electrophysiol 2015;8:288–95. https://doi.org/10.1161/CIRCEP.114.001752; PMID: 25673630. 59. Glukhov AV, Fedorov VV, Kalish PW, et al. Conduction remodeling in human end-stage nonischemic left ventricular cardiomyopathy. Circulation 2012;125:1835–47. https://doi. org/10.1161/CIRCULATIONAHA.111.047274; PMID: 22412072. 60. Anter E, Tschabrunn CM, Buxton AE, et al. High-resolution mapping of postinfarction reentrant ventricular tachycardia: electrophysiological characterization of the circuit. Circulation 2016;134:314–27. https://doi.org/10.1161/ CIRCULATIONAHA.116.021955; PMID: 27440005. 61. Mayer A. Rhythmic pulsation in scyphomedusæ. Washington DC, US: Carnegie Institute of Washington; 1906:1–62. 62. Rudy Y. Reentry: insights from theoretical simulations in a fixed pathway. J Cardiovasc Electrophysiol 1995;6:294–312. https://doi.org/10.1111/j.1540-8167.1995.tb00402.x; PMID: 7544193. 63. Quan W, Rudy Y. Unidirectional block and reentry of cardiac excitation: a model study. Circ Res 1990;66:367–82. https://doi. org/10.1161/01.RES.66.2.367; PMID: 2297808. 64. Ciaccio EJ, Coromilas J, Ashikaga H, et al. Model of unidirectional block formation leading to reentrant ventricular tachycardia in the infarct border zone of postinfarction canine hearts. Comput Biol Med 2015;62:254– 63. https://doi.org/10.1016/j.compbiomed.2015.04.032; PMID: 25966920. 65. Mehra R, Zeiler RH, Gough WB, et al. Reentrant ventricular arrhythmias in the late myocardial infarction period. 9. Electrophysiologic-anatomic correlation of reentrant circuits. Circulation 1983;67:11–24. https://doi.org/10.1161/01. CIR.67.1.11; PMID: 6183020. 66. Wit AL, Allessie MA, Bonke FIM, et al. Electrophysiologic mapping to determine the mechanism of experimental ventricular tachycardia initiated by premature impulses. Experimental approach and initial results demonstrating

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ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

Electrophysiology & Ablation

Decrement Evoked Potential Mapping to Guide Ventricular Tachycardia Ablation: Elucidating the Functional Substrate Abhishek Bhaskaran,1 John Fitzgerald,2 Nicholas Jackson,3 Sigfus Gizurarson,4 Kumaraswamy Nanthakumar1 and Andreu Porta-Sánchez5 1. University Health Network, University of Toronto, Ontario, Canada; 2. University of Adelaide, Australia; 3. John Hunter Hospital, Newcastle, Australia; 4. Landspitali, Reykjavik, Iceland; 5. Hospital Universitario Quirónsalud Madrid, Molecular Cardiology Laboratory, Centro Nacional de Investigaciones Cardiovasculares, Spain

Abstract Empirical approaches to targeting the ventricular tachycardia (VT) substrate include mapping of late potentials, local abnormal electrogram, pace-mapping and homogenisation of the abnormal signals. These approaches do not try to differentiate between the passive or active role of local signals as the critical components of the VT circuit. By not considering the functional components, these approaches often view the substrate as a fixed anatomical barrier. Strategies to improve the success of VT ablation need to include the identification of critical functional substrate. Decrement-evoked potential (DeEP) mapping has been developed to elucidate this using an extra-stimulus added to a pacing drive train. With knowledge translation in mind, the authors detail the evolution of the DeEP concept by way of a study of simultaneous panoramic endocardial mapping in VT ablation; an in silico modelling study to demonstrate the factors influencing DeEPs; a multicentre VT ablation validation study; a practical approach to DeEP mapping; the potential utility of DeEPs to identify arrhythmogenic atrial substrate; and, finally, other functional mapping strategies.

Keywords Ventricular tachycardia, substrate mapping, EGM, catheter ablation, cardiac mapping Disclosure: KN declares US Patent Application No. 14/891,843, United States and European Patent Application No. 14798103.9. as potential conflicts of interest. APS has received speaker honoraria from Medtronic, is a consultant for Abbott Laboratories and has received travel grants from Biosense Webster. All other authors have no conflicts of interest to declare. Received: 10 June 2020 Accepted: 12 October 2020 Citation: Arrhythmia & Electrophysiology Review 2020;9(4):211–8. DOI: https://doi.org/10.15420/aer.2020.25 Correspondence: Andreu Porta-Sánchez, Arrhythmia Unit, Hospital Universitario Quirónsalud Madrid, Molecular Cardiology Laboratory, Centro Nacional de Investigaciones Cardiovasculares, Diego de Velázquez, 28223, Pozuelo de Alarcón, Madrid, Spain. E: andreuportasanchez@gmail.com Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for noncommercial purposes, provided the original work is cited correctly.

Despite advances in mapping and ablation, the long-term success of ventricular tachycardia (VT) ablation is moderate at best.1 The high recurrence rate could be attributed to either the evolving scar or inadequate ablation of pre-existing potential scar channels. Substratebased ablation strategies have been shown to be as equally effective as activation mapping, which is often limited by haemodynamic instability and non-inducibility.2

multielectrode catheters offer a new perspective on detailing the activation maps during sinus or paced rhythm to identify regions of slow conduction. Isochronal late activation mapping (ILAM) is one such novel method to identify areas of slow conduction during sinus rhythm.4 However, exact relationship of the areas of slow conduction to critical zones of re-entry and their ability to define ablation targets has not been clarified with a multicentre validation study.

Substrate ablation is often based on late potentials (LPs) and local abnormal ventricular activities (LAVAs). However, the conducting channels critical to VT induction/maintenance need not be active during sinus rhythm mapping. Decrement-evoked potential (DeEP) mapping is a method to unmask these critical channels and to identify those with the potential for unidirectional block to initiate tachycardia. The latest consensus document on VT ablation recommends DeEP mapping for substrate-based ablation.3

The functional substrate mapping technique of ILAM also assumes that the slow conduction zones in sinus rhythm correspond to the critical isthmus in VT. This does not take into account the pivotal role of the initiating premature ventricular contractions (PVCs) and functional substrate in the induction of VT. Furthermore, the areas with slower conduction have an activation site dependency.5

In the current era of high-resolution mapping, detailed mapping of activation wavefronts in the arrhythmia circuit is feasible. The new

A strategy that increases the specificity of signals to better identify functional substrate that interacts with potential triggers (with or without an activation map) would be of inherent value. This technique would need to identify sites that initiate the re-entry and

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Electrophysiology & Ablation Figure 1: Mechanistic Basis of Decrement Evoked Potential Mapping A

atrium where there is a significant need over and above pulmonary vein isolation (PVI) to decrease AF burden.

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The concept of DeEP mapping was born from the understanding that the initiation of a re-entrant VT circuit is dependent upon delayed or decremental conduction through a critical zone of tissue.6 If this slow conduction occurs adjacent to a site of unidirectional block, then a reentrant circuit may develop.7 The concept of linking EGMs that identify regions displaying decremental conduction to the initiation and maintenance of VT is shown in Figure 1.

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The principles of the DeEP mapping strategy were initially examined using these simultaneous panoramic endocardial maps from intraoperative VT cases. These cases showed global activation of the left ventricular endocardium during a pacing train from the right ventricular apex, an extra-stimulus and VT.

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This figure corresponds to an intraoperative panoramic mapping case of ventricular tachycardia (VT) induction using a 112 bipole endocardial balloon. A: EGMs A–K correspond with the bipoles labelled A–K in panel C. The end of a drivetrain (S1) is followed by three extra-stimuli (S2–S4) and the initiation of a re-entrant VT. The near-field EGMs progressively decrement with each extra-stimulus until unidirectional block occurs between bipoles I and J, allowing for the initiation of the re-entrant circuit. Most of the near-field EGMs in panel A (that occur along the length of the diastolic isthmus in VT) display decrement with the first extra-stimulus, hence these would all be considered DeEPs and would all be excellent targets for the ablation of this particular VT. B: An enlarged image of bipole H from panel A. C: Bull’s-eye map of the left ventricular endocardium showing all 112 bipoles of the balloon array with the apical electrodes in the centre and the basal electrodes at the periphery. The voltage has been adjusted on this map to show regions of fixed scar in red, and healthy voltage in dark blue. The diastolic pathway of the VT circuit is shown as a red arrow in this panel. †Shows the polarity of the local component during S1. ‡Indicates the polarity change when the VT starts. Source: Jackson et al. 2015.6 Reproduced with permission from Wolters Kluwer Health.

the critical components of the VT circuit. This is the role and strength of DeEP. DeEP mapping identifies the components of diseased myocardium that are more likely to be critical to initiating or maintaining the VT circuit. This is achieved by delivering an extra stimulus and comparing the local activation delay during steady-state conditions (S1) and after the extra stimuli (S2). A decrement of more than 10 ms in the local electrogram (EGM) component has been proven to be highly specific for the detection of the critical sites of the VT circuit and thus provides a mechanistic target for substrate-based ablation. In this review, we focus on the birth of this concept from seminal panoramic intra-operative mapping of VT circuits, then take the concept back to the basic laboratory in silico model to understand the mechanism, followed by a prospective validation in a multicentre VT ablation trial. We also review other works that share similarities to this concept. Importantly, we discuss the potential of DeEP mapping in the

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Validation of Decrement-evoked Potential Mapping

Jackson et al. examined six hearts (nine VTs) that had undergone simultaneous panoramic mapping for VT induction.6 In each case, a substrate (or voltage) map was created to identify regions of fixed conduction block during right ventricular pacing, an activation map of the VT circuit was created to identify the critical isthmus, an LP map was created by highlighting any regions with local activation occurring beyond the end of the QRS and a DeEP map was created to highlight any regions of the myocardium where components of the local EGM displayed decrement following a single extra-stimulus. These maps were then compared to determine the sensitivity and specificity of DeEPs to the critical isthmus of the VT circuit (Figure 2). In this study, the mean sensitivity for identifying the critical isthmus in VT was 50 ± 23% for DeEPs and 36 ± 32% for LPs (p=0.31). The mean specificity was 43 ± 23% versus 20 ± 8% for DeEP and LP mapping respectively (p=0.031). Further to this, the EGMs that displayed the greatest decrement in each case had a sensitivity and specificity for the VT isthmus of 29 ± 10% and 95 ± 1%, respectively.6 This study showed DeEPs had better specificity than LPs for identifying the VT isthmus.6 Additionally, in silico simulations showed that conduction velocity restitution magnified by zig-zag conduction in diseased areas of myocardium could be the underlying mechanism for DeEPs. In this way, the authors were able to show that a mechanistic strategy that looked at functional aspects of the substrate with a single extra-stimulus was able to refine the conventional targets of VT ablation (LAVAs) to a more focused strategy. Based on data from high-resolution mapping of swine VT circuits, areas with the slowest conduction where decrement is likely to occur may correspond to wavefront curvature or changes in myocardial fibre orientation.8,9

In Silico Modelling of Decrement-evoked Potential The physiological variables that could affect the presence and extent of decrement had to be defined. The objective of this back-to-bench strategy was to understand the effect of multiple pacing parameters on the degree of decrement, i.e. the proximity of pacing to the conducting channels in the unexcitable scar, the number of conducting channels in the scar, the size of scar, the effect of multiple extrasystoles and the direction of engagement of the channels. Validation with an animal or human model of such a number of variables is not feasible so a computer model was used in the study by Beheshti et al.10,11

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

DeEP Mapping: Elucidating the Functional VT Substrate

Current evidence points to the crucial role of decrement in local potentials for the induction and maintenance of scar related-VT.11 The clinical implications of these findings are: isolated right ventricle (RV) pacing for VT induction might be insufficient to produce decremental potentials; and different sites of programmed ventricular stimulation (such as the RV apex, the right ventricular outflow tract and multiple left ventricular sites) could be used to allow the wavefront to engage the scar from different directions and so alter the decrement in the local tissue. This may be useful in patients with left ventricular leads for cardiac resynchronisation, as this lead could be used as an alternate site that may be more effective for inducing VT depending on the location of the patient’s scar and critical isthmus. Anter et al. also found that areas of slow conduction with isochronal crowding can dramatically change with different pacing sites and this is consistent with our modelling studies.5

Figure 2: Mapping Comparisons Voltage map

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Many substrate-based ablation strategies have been described and used in the past to render patients VT free. Those strategies consisted initially of intraoperatively peeling the whole endocardium responsible for the VT circuit.12 This was followed by the development of catheterbased strategies that were initially focusing on activation mapping that allowed the VT isthmus to be identified and targeted in patients with haemodynamically stable, mappable VT. The fact that many patients were experiencing breakthrough arrhythmia episodes during follow-up led to widespread use of substrate-based strategies, some of them targeting LAVA, and others encircling the substrate to try to electrically isolate the scar or else the use of more aggressive endo-epicardial scar homogenisation strategies.13–15 Those strategies, albeit with clinically proven benefit, have lacked the ability of focus the ablation in areas that are truly responsible for the initiation or maintenance of the VT circuit. As such, they lead to ablation of areas of still functional myocardium that could be playing a completely passive role. In contrast with the tendency to ablate large areas of myocardium with abnormal signals, the finding of the higher sensitivity and specificity of the DeEP areas in identifying the critical VT substrate led us to design a focused strategy in a multicentre setting where areas with DeEP properties would be targeted first with radiofrequency (RF) then reinducibility of VT would be tested. The objectives of the study were twofold: to establish whether the methodology for DeEP mapping with an extra-stimulus is feasible with current electro-anatomical mapping tools; and describe the mid-term

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

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We simulated a ventricular myocardial slab of 40 mm × 20 mm × 10 mm with an unexcitable core with a conductivity of 0.1 S/m. The ‘scar’ extended from epicardium to endocardium with a thin rim of conduction tissue outside (Figure 3) and it contained five conducting channels running towards a central isthmus. These channels could be opened or closed as desired. The pacing sequence of S1–S2 was simulated. The main findings were: pacing in close proximity to the scar maximised the amount of decrement (Figure 3A); pacing close to the opening of the channels induced less decrement (Figure 3A); the larger the size of the scar the larger the decrement (Figure 3B); a fewer open conducting channels led to higher decrement (Figure 3C); and the addition of S3 did not cause increased decrement.

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1-Specificity Comparison of voltage mapping, LP mapping, diastolic path of ventricular tachycardia (VT) and decrement evoked potential mapping. Example of left ventricle endocardial maps obtained during intraoperative mapping from the same patient. A shows the apex at the centre, anterior wall on top, inferior wall on the bottom and basal segments at the periphery. The voltage map highlights an area in the anterolateral wall with low voltage corresponding to scar. The diastolic channel of activation is located in a region (highlighted with white arrows and seen in the activation map) of borderline decreased voltages between two areas of dense scar. The LP map (where annotation of local activation time is in the late near-field component) highlights an area near the apex and border zone of the low-voltage area, far from the actual VT circuit. In contrast, the (DeEP) map corresponds to early and late isthmus sites in keeping with a higher specificity for identifying ablation targets for this VT. B illustrates the true-positive results against false-positive results to generate likelihood ratios for LPs and DeEPs, LPs within scar channels and points with the largest decrement or maximum DeEPs to identify the diastolic isthmus during VT. Mean likelihood radios of all VTs are given above with the 95% CIs. DeEP = decrement evoked potential; LP = late potential. Source: Jackson et al. 2015.6 Reproduced with permission from Wolters Kluwer Health.

results of a DeEP-guided ablation strategy in terms of VT burden. The study included 20 consecutive patients in three institutions.16 Substrate maps were created during RV pacing or sinus rhythm. Late potentials were identified via a multi-electrode mapping catheter (16 patients) or a 3.5 mm tip catheter, and were defined as potentials with complex high frequency or multicomponents after or at the QRS offset. For all the points showing LPs, a systematic assessment for local decrement was performed with a drive train (S1) from the RV at 600 ms with a single S2 (coupled at 20 ms above the ventricular effective refractory period [VERP]). Those areas were tagged in the mapping system and, in 13 VTs, the activation map of the tachycardia was carefully constructed with high density maps (Figure 4). With that information, we were able to identify which proportion of DeEPs were co-located with the isthmus of VT. The main difference with other studies was that only areas with DeEPs were targeted with RF ablation. Reinduction of VT was performed after DeEPs were eliminated. If VT was still inducible, other targets were ablated.

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Electrophysiology & Ablation Figure 3: In Silico Simulations of Decremental Response

Position 1

(a) Effect of conduction barrier and site of pacing

Close to channel: mid DeEP

Position 3

Far from scar: minimal DeEP

Close to scar: maximum DeEP

B3 DeEP delay (ms)

Position 2

(b) Effect of scar size

7.5 5.0

S2–S1 S3–S1

2.5 0.0

2/3

4/3

DeEP delay S2–S1 (ms)

3 4 5 6 7 Inexcitable core ID

Factors influencing the extent of decrement in a simplified VT substrate demonstrated in an in silico model. A: Different pacing sites cause different degrees of DeEP. Conduction barriers placed between the pacing site and unexcitable scar led to a reduction in decrement (minimal DeEP, position 2). Pacing from other side of channel and near to the scar. When paced from proximity the extent of decrement was much higher (maximum DeEP, position 3). Pacing from the near end produced less decrement (mid DeEP, position 1). B: The third set of experiments included altering the size of central scar. See the reference scar size (B1). The bigger the scar (B2), the more the decrement (B3). C: Fewer open channels lead to maximal decrement. Pacing from close to unprotected channels with multiple side branches showed smaller decrement compared to a protected channel with no side branches. DeEP = decrement evoked potential. Source: Beheshti et al. 2018.11 Reproduced with permission from Elsevier.

Patient characteristics were typical for a VT ablation cohort: the mean age was 65 ± 17 years, the left ventricular ejection fraction was 33.4 ± 11%, 95% were men, 90% had a New York Heart Association classification of I–II, 40% were on two antiarrhythmic drugs and six were in VT storm (30%). Mapping showed that conventional LPs accounted for 17% of the myocardium mapped (IQR 8.9%–75%) and DeEPs accounted for 4.8% (IQR 2.2%–26%); p<0.001). Most patients (80%) became non-inducible by targeting the DeEP areas only and further RF in those still inducible did not change the inducibility rate. RF time was low, with a mean of 31 minutes ± 21 minutes. The median (IQR) VT episode burden 6 months after the procedure was 0 (IQR 0–2) and it was 11 (IQR 5–25) 6 months before it. When the locations of LPs and DeEPs with respect to the critical VT regions were assessed, it was found that the area under the ROC curve for DeEPs (0.86; 95% CI [0.82–0.88]) was significantly higher than that of LPs (0.79; 95% CI [0.75–0.82]). These findings indicate that DeEPs have a higher specificity than LPs for the detection of critical VT sites during stable rhythm than LPs and also encompass a smaller region of the myocardium. The main messages of this study were: DeEP mapping was a safe and effective strategy to differentiate the critical regions of the VT circuit during stable rhythm with current electro-anatomical mapping technology; a limited and focused RF ablation strategy yielded the majority of patients non-inducible and showed mid-term results comparable with other contemporary ablation strategies; DeEPs provide higher specificity than conventional LPs obtained during stable rhythms. These findings are of significant importance to enhance the

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capacity of the electrophysiologist to differentiate critical areas of the VT substrate from passive ones.

Workflow Considerations Manual construction of DeEP maps using multi-electrode catheters is time consuming. Therefore, current efforts are directed at automating this process. Recent advances in technology such as the ‘replay’ algorithm of CARTO (Biosense Webster), the ‘turbomap’ feature of NavX Ensite (Abbott) and the customised mapping window of the Rhythmia HDx (Boston Scientific) mapping system could aid in the creation of DeEP maps.

Window of Interest and Annotation Criteria DeEP mapping might appear cumbersome initially. The key technique is to localise the areas of LPs initially and then to follow that up with an S1–S2 sequence. To identify LPs and DeEPs, the window of interest needs to be set at the terminal portion of the QRS to ensure that only the local EGM is annotated and the far-field activation is not tracked by the automated algorithm. If permitted by the system, annotation of the latest deflection of the local EGM is preferable (as this is easiest for an automated system to do consistently). Manual review of the automated annotations is often required to ensure precision.

Creation of S1 and S2 Maps All mapping systems allow additional mapping on previously acquired signals. A practical method to compare the activation pattern of both maps would be to create the S2 map initially and then move the window of interest to the preceding S1, which is the final stimulus of the drive train to annotate the LPs.17 Automatic repetition of the pacing sequence

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

DeEP Mapping: Elucidating the Functional VT Substrate Figure 4: Mapping in Ischaemic Cardiomyopathy

B II

aVR

Voltage map

Late potential map

Duo 1,2

Duo 3,4 125 ms

151 ms

Duo 5,6

Duo 7,8 DeEP map

Activation map Duo 9,10

RVa d

P1 ART Stim 3 ILAM map

S1/S2 from RVA (600/320 ms)

A: Case example of a post-MI scar-related ventricular tachycardia showing right anterior oblique views of the electroanatomical maps. The voltage map shows a large area of low voltage at the anterolateral wall. The late potential map shows an extensive area of late activation into the low voltage region. In contrast, the DeEP map shows that the area of interest is much more circumscribed to the anteroseptal region of the left ventricle. This corresponds to the ventricular tachycardia isthmus of the tachycardia. ILAM mapping shows several areas with isochronal crowding, making it difficult to select the best ablation strategy. B: An example of a DeEP mapped with a decapolar catheter. DeEP = decrement evoked potential; ILAM = isochronal late activation mapping. Source: Porta-Sánchez et al. 2018.16 Reproduced with permission from Elsevier.

of the drive train followed by an extra stimulus while the substrate map is being performed would be the most time-efficient method.

Comparison of S1 and S2 Maps The areas of DeEPs are usually a smaller subset of the areas with late potentials. This provides an opportunity to narrow the area of interest to the critical components of the VT circuit.

Manual Annotation of Late Potentials and Decrement-evoked Potentials It goes without saying that, despite using automated algorithms, one has to verify the accuracy of the annotations during the S1 and S2 mapping to confirm the presence or absence of DeEPs. Another option is to manually annotate the local EGMs, which is less susceptible to errors and could provide accurate maps; however, this is time consuming.

Possible Application of Decrement-evoked Potential to Atrial Substrates Haïssaguerre et al. showed pulmonary vein triggers to be frequent initiators of AF and this has led to the ablation strategy of pulmonary vein isolation.18 Although this had moved from ostial to antral lesion sets, it has remained the primary strategy for AF ablation up to the

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

present time. Indeed, there is randomised data showing no additional benefit of ablation strategies with roof and mitral isthmus lines, or complex fractionated atrial EGM targeting in addition to pulmonary vein isolation in reducing the rate of recurrence of AF.19,20 The search for strategies to identify additional targets for AF ablation continues. Atrial myocardial thickness is less than one-third that of ventricular myocardium, at approximately 1–4 mm on average.21 Surprisingly in this thin-walled tissue, there is evidence for electrical dissociation between layers of the atrial endo- and epicardium, as well as heterogeneity in conduction in different regions.22 Atrial arrhythmia is promoted by early functional and then structural changes in this tissue. Probably, the first known description of decrement preceding atrial re-entry was described by Lammers in 1992.7 This has been overlooked and needs further developmental work for application in the atrium using the DeEP protocol. The application of DeEP mapping to atrial tissue shows promise. Indeed, there are published cases of successful intra-atrial re-entrant tachycardia (IART) ablation using DeEP mapping to locate involved tissue that corresponded with earliest activation but did not correspond with LPs mapped without the use of extra-stimulus pacing. The circuit

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Electrophysiology & Ablation Table 1: Studies Assessing the Functional Component of the Ventricular Tachycardia Substrate: Extrastimulus Techniques for the Ventricular Tachycardia Substrate Mapping Type of Decremental Mapping

Aetiology

DeEP16

20 patients with ICM

HSC29

EDP28

Extra-Stimulus

Location of Decremental Potentials

Ablation Target

One extrastimulus VERP + 20ms

In 50% of DeEP areas co-localised with diastolic isthmus

Only DeEP

37 patients with ICM, ARVC and DCM

2–3 extrastimuli VERP + 60 ms, VERP + 40–20 ms and VERP + 10–20 ms

62 patients with ICM

1–4 extrastimuli

Outcome Acute

Follow-Up

High noninducibility (80%)

6 months: mean VT burden reduced to 0 from 11 pre-procedure

Majority in border zone Both LP and HSC, and areas, 32% in non-scar compared to historical areas cohort of LP only

Low inducibility (28.6% versus 52.9%)

2 years: less VT recurrence (75% versus 58%)

50% in dense scar, 30% Only EDP in border zone, 20% in non-scar area (hidden substrate)

High noninducibility (90%)

16 months: low recurrence (22%)

ARVC = arrhythmogenic right ventricular dysplasia; DCM = dilated cardiomyopathy; DeEP = pecrement-evoked potential; EDP = evoked delayed potential; HSC = hidden slow conduction; LP = late potential; VERP = ventricular effective refractory period; VT = ventricular tachycardia.

in IART may share characteristics with that in ventricular tachycardia given there are areas of fixed scar and routes for conduction within or around this.23 The lack of easily mappable, targetable, low-voltage areas in many cases of AF make functional mapping of the atrial substrate an appealing approach. Regions participating in the initiation and/or perpetuation of AF outside the pulmonary veins are likely to display the properties of conduction delay, block and re-entry which can be identified by applying DeEP mapping to atrial tissue. Analogous to ventricular tissue, atrial tissue forming a critical part of the AF substrate may be identifiable with DeEP mapping.16 Recent studies have further explored the presence of endoepicardial dissociation seen in atrial tissue, which may be brought out to an even greater extent with extra-stimulus pacing.24,25 This functional change in atrial activation patterns is likely reflected in the difficulties shown mapping unstable atrial activation patterns in AF.26 DeEP mapping may play a role in unmasking the substrate that facilitates the chaotic, three-dimensional movement of wavefronts during AF.

Comparison with Other Extrastimuli Strategies and Future Perspectives Since the first published description of decremental mapping for the facilitation of VT ablation in 2015, there have been three more published clinical series.6 Our group published our initial clinical experience with DeEP mapping for VT ablation in March 2018 and, in the same month, de Riva's group published their initial patient data, followed by Acosta’s group with their initial experience and a follow-up 2 years later.16,27–29 Although these studies shared some similarities, there were important differences in methodology and ablation strategy (Table 1). The study by Acosta’s group included 37 patients, mostly post-infarction patients but one-quarter of these patients had other diagnoses, such as arrhythmogenic right ventricular dysplasia and dilated cardiomyopathy.29 They referred to the decrementing potentials as ‘hidden slow conductions’ (HSCs). An HSC was defined as the local EGM that decremented a minimum of 10 ms with double extra stimuli during programmed stimulation. They chose the ventricular effective refractory period (VERP) + 60 ms on S1 and VERP + 40–20ms on S2. If block was observed, the coupling interval was prolonged until conduction occurred and, in situations of uncertainty (when conduction was not delayed), they added a third extrastimulus. With this relatively aggressive protocol, they managed to induce sustained VT in

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only three patients, and those were terminated with antitachycardia pacing or direct current cardioversion. This protocol is quite different from ours regarding both the number of extra-stimuli and the length of the coupling interval. Acosta et al. performed pacing only when a suspected HSC was seen and, in a third of those signals, they could confirm decrement. For a quarter of the signals, a third stimulus was necessary to demonstrate decrement. They noticed HSCs in 57% of patients with a median of eight HSCs per patient. They observed more HSCs in ischaemic patients and in smaller scars with less late potentials, a feature noticed by others as well. In addition, they noted more HSCs in heterogenous scars than in large homogenous scars. Their ablation strategy was to target suspected channels using voltage mapping or as demonstrated by late potentials (LPs). In patients with HSCs, they added further ablation to these areas, which in the vast majority were outside the presumed channels and would have not been targeted by their standard ablation strategy. The patients with HSC ablation had shorter total RF times (17 minutes), presumably because of smaller scars and fewer LPs being surrogates for potential channels. More patients with HSC were rendered non-inducible after the initial ablation but, after further mapping and ablation, the results were similar at the end of the procedure as well as during follow-up. In the two other studies, a strategy that initially targeted the decrementing potentials was used, so it is difficult to tease out the potential added benefit of HSC ablation.28,29 As a complement to the electrical data, Acosta et al. also added some insight gained from MRI scans obtained before the procedure, and could demonstrate that the HSCs were located in areas in the dense scar or border zone, even though the EGM voltage was normal (>1.5 mV).29 A study on an extended cohort of patients with longer follow-up has been recently published by the same group and compared to a historical cohort; this has shown that targeting the HSC seems to be associated with less VT during follow-up.29 This is a feature noted by de Riva's group, who studied 62 postinfarction patients referred for VT ablation.28 Two patients had to be excluded because they were intolerant to the pacing protocol. They

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

DeEP Mapping: Elucidating the Functional VT Substrate mapped the infarct area with a pacing protocol of S1 = 500 ms and set S2 at VERP + 50 ms. They targeted ablation signals that showed a nearfield component that was <1.5 mV and displayed decrement or block with the pacing protocol. Late potentials that did not display these findings were not targeted for ablation. In their study, a third of all signals from the infarct area were decrementing and were termed ‘evoked delayed potentials’ (EDPs); about 20% of those were in normal voltage areas adjacent to the scar. All but four (7%) patients displayed EDPs. The authors had MRI data for a small subset of patients, and observed that the EDPs came from areas with relatively normal voltage and were mostly located in non-transmural scar areas. On average, they ablated only for 15 minutes with a rigorous endpoint of loss of capture at that site. Almost 70% of patients were non-inducible after EDP ablation only, and an additional 23 were non-inducible after further ablation based on conventional mapping. Our protocol and study differed significantly from other studies in several aspects: • A simple pacing (S1 = 600 ms) and extra-stimulus protocol (S2 = VERP + 20 ms) were used. • Multielectrode catheters were used in 80% of the cases. • DeEP mapping was performed only in areas with late potentials. • Mechanistic evidence of the value of DeEP mapping was provided by demonstrating that in 50% of patients (13 VTs), DeEP areas and not LPs correlated well with the diastolic pathway of the VT circuit. The abolition of this resulted in better clinical results. DeEP mapping, regardless of the protocol chosen, will be invaluable in cases where VT induction is either impossible or not feasible. Multielectrode catheters will be increasingly be used in these circumstances and this will facilitate the procedure further; this may also elucidate targets in the vicinity of the mapped area as critical areas

Tung R, Vaseghi M, Frankel DS, et al. Freedom from recurrent ventricular tachycardia after catheter ablation is associated with improved survival in patients with structural heart disease: an International VT Ablation Center Collaborative Group study. Heart Rhythm 2015;12:1997–2007. https://doi. org/10.1016/j.hrthm.2015.05.036; PMID: 26031376. Graham AJ, Orini M, Lambiase PD. Limitations and challenges in mapping ventricular tachycardia: new technologies and future directions. Arrhythm Electrophysiol Rev 2017;6:118–24. https://doi.org/10.15420/aer.2017.20.1. PMID: 29018519. Cronin EM, Bogun FM, Maury P, et al. 2019 HRS/EHRA/APHRS/ LAHRS expert consensus statement on catheter ablation of ventricular arrhythmias. Europace 2019;21:1143–4. https://doi. org/10.1093/europace/euz132; PMID: 31075787. Aziz Z, Shatz D, Raiman M, et al. Targeted ablation of ventricular tachycardia guided by wavefront discontinuities during sinus rhythm: a new functional substrate mapping strategy. Circulation 2019;140:1383–97. https://doi.org/10.1161/ CIRCULATIONAHA.119.042423; PMID: 31533463. Anter E, Neuzil P, Reddy VY, et al. Ablation of reentryvulnerable zones determined by left ventricular activation from multiple directions: a novel approach for ventricular tachycardia ablation: a multicenter study (PHYSIO-VT). Circ Arrhythm Electrophysiol 2020;13:e008625. https://doi. org/10.1161/CIRCEP.120.008625; PMID: 32372657. Jackson N, Gizurarson S, Viswanathan K, et al. Decrement evoked potential mapping: basis of a mechanistic strategy for ventricular tachycardia ablation. Circ Arrhythm Electrophysiol 2015;8:1433–42. https://doi.org/10.1161/CIRCEP.115.003083; PMID: 26480929. Lammers WJ, Kirchhof C, Bonke FI, Allessie MA. Vulnerability of rabbit atrium to reentry by hypoxia. Role of inhomogeneity in conduction and wavelength. Am J Physiol 1992;262:H47–55. https://doi.org/10.1152/ajpheart.1992.262.1.H47; PMID: 1733321. Anter E, Tschabrunn CM, Buxton AE, Josephson ME. Highresolution mapping of postinfarction reentrant ventricular

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10.

11.

12.

13.

14.

15.

for successful ablation. Attempts are under way to automate and incorporate this concept into contemporary 3D mapping technology with multi-electrode catheters.

Conclusion DeEP mapping is a substrate-based mapping strategy established on the foundation of robust mechanistic evidence and has been prospectively validated in a multi-centre human trial. This functional assessment of the VT substrate adds to the conventional mapping of local abnormal EGMs during VT ablation. Unlike local abnormal EGMs, however, DeEP sites have been proven to participate in initiation and maintenance of re-entrant arrhythmias, which obviates the need for extensive substrate ablation. The evidence for the efficacy of this strategy in VT ablation comes from a multicentre patient cohort, but further validation in larger randomised trials with automated software in 3D mapping systems will be important. The utility of DeEP mapping in atrial flutter and AF ablation is still to be elucidated and such efforts are under way.

Clinical Perspective • Decrement-evoked potential (DeEP) mapping is a strategy for VT ablation without inducing VT. • If tachycardia remains inducible after DeEP, other methods of substrate ablation can be explored. • Automated algorithm incorporation into electro-anatomical mapping systems could allow DeEP mapping to integrate into the workflow seamlessly. • In AF ablation and atypical atrial flutters, DeEPs could be targeted where they identify the tachycardia isthmus or at areas capable of local re-entry, without time-consuming extensive mapping and annotation.

tachycardia: electrophysiological characterization of the circuit. Circulation 2016;134:314–27. https://doi.org/10.1161/ CIRCULATIONAHA. 116.021955; PMID: 27440005. León DG, López-Yunta M, Alfonso-Almazán JM, et al. Three-dimensional cardiac fibre disorganization as a novel parameter for ventricular arrhythmia stratification after myocardial infarction. Europace 2019;21:822–32. https://doi.org/10.1093/europace/euy306; PMID: 30649290. ten Tusscher KHWJ, Noble D, Noble PJ, Panfilov AV. A model for human ventricular tissue. Am J Physiol Heart Circ Physiol 2004;286:H1573–89. https://doi.org/10.1152/ ajpheart.00794.2003; PMID: 14656705. Beheshti M, Nayyar S, Magtibay K, et al. Quantifying the determinants of decremental response in critical ventricular tachycardia substrate. Comput Biol Med 2018;102:260–6. https://doi.org/10.1016/j.compbiomed.2018.05.025; PMID: 29871758. Miller JM, Marchlinski FE, Harken AH, et al. Subendocardial resection for sustained ventricular tachycardia in the early period after acute myocardial infarction. Am J Cardiol 1985;55:980–4. https://doi.org/10.1016/0002-9149(85)90730-1; PMID: 3872591. Jais P, Maury P, Khairy P, et al. Elimination of local abnormal ventricular activities: a new end point for substrate modification in patients with scar-related ventricular tachycardia. Circulation 2012;125:2184–96. https://doi.org/10.1161/CIRCULATIONAHA.111.043216; PMID: 22492578. Tzou WS, Frankel DS, Hegeman T, et al. Core isolation of critical arrhythmia elements for treatment of multiple scar-based ventricular tachycardias. Circ Arrhythm Electrophysiol 2015;8:353–61. https://doi.org/10.1161/CIRCEP.114.002310; PMID: 25681389. Gökoglan Y, Mohanty S, Gianni C, et al. Scar homogenization versus limited-substrate ablation in patients with nonischemic cardiomyopathy and ventricular tachycardia. J Am Coll Cardiol

2016;68:1990–8. https://doi.org/10.1016/j.jacc.2016.08.033; PMID: 27788854. 16. Porta-Sánchez A, Jackson N, Lukac P, et al. Multicenter study of ischemic ventricular tachycardia ablation with decrementevoked potential (DEEP) mapping with extra stimulus. JACC Clin Electrophysiol 2018;4:307–15. https://doi.org/10.1016/j. jacep.2017.12.005; PMID: 30089555. 17. Voglimacci-Stephanopoli Q, Sacher F, Martin C, et al. Creation of sinus rhythm and paced maps using a single acquisition step: the ‘one acquisition-two maps’ technique – a feasibility study. J Interv Card Electrophysiol 2020. https://doi.org/10.1007/ s10840-020-00793-z; PMID: 32562193; epub ahead of press. 18. Haïssaguerre M, Jaïs P, Shah DC, et al. Spontaneous initiation of atrial fibrillation by ectopic beats originating in the pulmonary veins. N Engl J Med 1998;339:659–66. https://doi. org/10.1056/NEJM199809033391003; PMID: 9725923. 19. Verma A, Jiang CY, Betts TR, et al. Approaches to catheter ablation for persistent atrial fibrillation. N Engl J Med 2015;372:1812–22. https://doi.org/10.1056/NEJMoa1408288; PMID: 25946280. 20. Ganesan AN, Shipp NJ, Brooks AG et al. Long-term outcomes of catheter ablation of atrial fibrillation: a systematic review and meta-analysis. J Am Heart Assoc 2013;2:e004549. https://doi.org/10.1161/JAHA.112.004549; PMID: 23537812. 21. Whitaker J, Rajani R, Chubb H, et al. The role of myocardial wall thickness in atrial arrhythmogenesis. Europace 2016;18:1758–72. https://doi.org/10.1093/europace/euw014; PMID: 27247007. 22. de Groot N, van der Does L, Yaksh A, et al. Direct proof of endo-epicardial asynchrony of the atrial wall during atrial fibrillation in humans. Circ Arrhythm Electrophysiol 2016;9:e003648. https://doi.org/10.1161/CIRCEP.115.003648; PMID: 27103089. 23. Bhaskaran A, Gizurarson S, Porta-Sánchez A, et al. Atrial decremental evoked potentials accurately determine the critical isthmus of intra-atrial re-entrant tachycardia. Europace

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Electrophysiology & Ablation 2018;20:1620. https://doi.org/10.1093/europace/euy164; PMID: 30085029 24. Parameswaran R, Teuwen CP, Watts T, et al. Functional atrial endocardial-epicardial dissociation in patients with structural heart disease undergoing cardiac surgery. JACC Clin Electrophysiol 2020;6:34–44. https://doi.org/10.1016/j. jacep.2019.08.016; PMID: 31971904. 25. van der Does LJME, Kharbanda RK, Teuwen CP, et al. Atrial ectopy increases asynchronous activation of the endo- and epicardium at the right atrium. J Clin Med 2020;9:558. https://

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doi.org/10.3390/jcm9020558; PMID: 32085601. 26. Barbhayia CR, Kumar S, Michaud GF. Mapping atrial fibrillation: 2015 update. J Atr Fibrillation. 2015;8:1227. https://doi. org/10.4022/jafib.1227; PMID: 27957220. 27. Jackson N, Gizurarson S, Viswanathan K, et al. Decrement evoked potential mapping. Circ Arrhythm Electrophysiol 2015;8:1433–42. https://doi.org/10.1161/CIRCEP.115.003083; PMID: 26480929. 28. de Riva M, Naruse Y, Ebert M, et al. Targeting the hidden substrate unmasked by right ventricular extrastimulation

improves ventricular tachycardia ablation outcome after myocardial infarction. JACC Clin Electrophysiol. 2018;4:316–27. https://doi.org/10.1016/j.jacep.2018.01.013; PMID: 30089556. 29. Acosta J, Andreu D, Penela D, et al. Elucidation of hidden slow conduction by double ventricular extrastimuli: a method for further arrhythmic substrate identification in ventricular tachycardia ablation procedures. Europace 2018;20:337–46. https://doi.org/10.1093/europace/euw325; PMID: 28017938.

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References 1. Piorkowski C, et al. Early real-world adoption of mobile remote monitoring using the Confirm Rx Insertable Cardiac Monitor. Poster presented at: APHRS; 2018.

Rx Only Brief Summary: This product is intended for use by or under the direction of a Physician. Prior to using these devices, please review the Instructions for Use for a complete listing of indications, contraindications, warnings, precautions, potential adverse events and directions for use. Intended Use: The Implantable Cardioverter Defibrillator (ICD) and Cardiac Resynchronization Therapy Defibrillator (CRT-D) devices are intended to provide ventricular antitachycardia pacing and ventricular cardioversion/ defibrillation. The CRT-D devices are also intended to resynchronize the right and left ventricles. The myMerlinPulse™ mobile application is intended for use by people who have an Abbott Medical implanted heart device and access to a mobile device. The app provides remote monitoring capability of the implanted heart device by transmitting information from the patient’s implanted heart device to the patient’s healthcare provider. Indications: The ICD and CRT-D devices are indicated for automated treatment of life-threatening ventricular arrhythmias. CRT-D devices are also indicated to treat symptoms in patients who have congestive heart failure with ventricular dyssynchrony. In addition, dual chamber ICD and CRT-D devices with the AT/AF detection algorithm are indicated in patients with atrial tachyarrhythmias or those patients who are at significant risk of developing atrial tachyarrhythmias. MR Conditional ICDs and CRT-Ds are conditionally safe for use in the MRI environment when used in a complete MR Conditional system and according to instructions in the MRI-Ready Systems manual. Scanning under different conditions may result in severe patient injury, death or device malfunction. The myMerlinPulse™ mobile application is indicated for use by patients with supported Abbott Medical implanted heart devices. Contraindications: Contraindications for use of the pulse generator system include ventricular tachyarrhythmias resulting from transient or correctable factors such as drug toxicity, electrolyte imbalance, or acute myocardial infarction. The myMerlinPulse™ mobile application is contraindicated for use with any implanted medical device other than supported Abbott Medical implanted heart devices. Adverse Events: Possible adverse events associated with the implantation of the pulse generator system include the following: Arrhythmia (for example, accelerated or induced), Bradycardia, Cardiac or venous perforation, Cardiac tamponade, Cardiogenic shock, Death, Discomfort, Embolism, Endocarditis, Erosion, Exacerbation of heart failure, Excessive fibrotic tissue growth, Extracardiac stimulation (phrenic nerve, diaphragm, pectoral muscle), Extrusion, Fluid accumulation within the device pocket, Formation of hematomas, cysts, or seromas, Heart block, Hemorrhage, Hemothorax, Hypersensitivity, including local tissue reaction or allergic reaction, Infection, Keloid formation, Myocardial damage, Nerve damage, Occlusion/Thrombus, Pericardial effusion, Pericarditis, Pneumothorax, Pulmonary edema, Syncope, Thrombosis, Valve damage. Complications reported with direct subclavian venipuncture include pneumothorax, hemothorax, laceration of the subclavian artery, arteriovenous fistula, neural damage, thoracic duct injury, cannulation of other vessels, massive hemorrhage and rarely, death. Among the psychological effects of device implantation are imagined pulsing, depression, dependency, fear of premature battery depletion, device malfunction, inappropriate pulsing, shocking while conscious, or losing pulse capability. Possible adverse device effects include complications due to the following: Abnormal battery depletion, Conductor fracture, Device-programmer communication failure, Elevated or rise in defibrillation/cardioversion threshold, Inability to defibrillate or pace, Inability to interrogate or program due to programmer or device malfunction, Incomplete lead connection with pulse generator, Inhibited therapy including defibrillation and pacing, Inappropriate therapy (for example, shocks and antitachycardia pacing [ATP] where applicable, pacing), Interruption of function due to electrical or magnetic interference, Intolerance to high rate pacing (for example dyspnea or discomfort), Lead abrasion, Lead fracture, Lead insulation damage, Lead migration or lead dislodgement, Loss of device functionality due to component failure, Pulse generator migration, Rise in DFT threshold, Rise in pacing threshold and exit block, Shunting of energy from defibrillation paddles, System failure due to ionizing radiation. Additionally, potential adverse events associated with the implantation of a coronary venous lead system include the following: Allergic reaction to contrast media, Breakage or failure of implant instruments, Prolonged exposure to fluoroscopic radiation, Renal failure from contrast media used to visualize coronary veins. Refer to the User’s Manual for detailed intended use, indications, contraindications, warnings, precautions and potential adverse events. No potential adverse events have been identified with use of the myMerlinPulse™ mobile application. ™ Indicates a trademark of the Abbott group of companies. © 2020 Abbott. All Rights Reserved MAT-2007716 v1.0 | Item approved for Global use.

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