University of Groningen Characterization of Different Patient Populations with Atrial Fibrillation Kloosterman, Mariëlle

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University of Groningen

Characterization of Different Patient Populations with Atrial Fibrillation

Kloosterman, Mariëlle

DOI:

10.33612/diss.143841478

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Kloosterman, M. (2020). Characterization of Different Patient Populations with Atrial Fibrillation. University

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Mariëlle Kloosterman

Characterization of Different Patient Populations with Atrial Fibrillation

Financial support for the publication of this thesis by the following institutions and companies is gratefully acknowledged:

University of Groningen, Groningen University for Drug Exploration (GUIDE) The Dutch Heart Foundation

Abbott Medical Nederland B.V. Bayer B.V.

Biotronik Nederland B.V. Boehringer Ingelheim B.V. Olink Proteomics

All rights are reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means (electronic, mechanically, photocopying, recording or otherwise), without the permission of the author, and when appropriate the publisher holding the copyrights of the published articles.

Cover design: Robert Faber

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Proefschrift

ter verkrijging van de graad van doctor aan de Rijksuniversiteit Groningen

op gezag van de

rector magnificus prof. dr. Cisca Wijmenga en volgens besluit van het College voor Promoties.

De openbare verdediging zal plaatsvinden op maandag 23 november 2020 om 16:15 uur

door

Mariëlle Kloosterman geboren op 18 maart 1993

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Promotores

Prof. dr. Isabelle C. Van Gelder Prof. dr. Michiel Rienstra Copromotor

Dr. Alexander H. Maass Beoordelingscommissie Prof. dr. Rudolf A. De Boer Prof. dr. Frans H. Rutten Prof. dr. Karina Meijer

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Robbert Kloosterman MSc Drs. Valerie Collij

Financial support by the Dutch Heart Foundation and the Groningen Institute for Drug Exploration (GUIDE) for the publication of this thesis is gratefully acknowledged.

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Chapter 1 General introduction and outline of the thesis PART I - RIsK FACToRs AnD seX DIFFeRenCes

Chapter 2 Characteristics and outcomes of atrial fibrillation in patients with-out traditional risk factors: a RE-LY AF registry analysis

Europace. 2020

Chapter 3 Sex-related differences in risk factors, outcome, and quality of life in patients with permanent atrial fibrillation: results from the RACE II study

Europace. 2019

Chapter 4 Sex differences in catheter ablation of atrial fibrillation: results from AXAFA-AFNET 5

Europace. 2020

PART II - ConCoMITAnT HeART FAIlURe

Chapter 5 Genetic risk of atrial fibrillation in patients with heart failure European Journal of Heart Failure. 2020

Chapter 6 Comparing biomarker profiles of patients with atrial fibrillation versus sinus rhythm in heart failure with reduced and preserved ejection fraction

European Heart Journal. 2018

Chapter 7 General discussion and future perspectives

In part discussed in book chapters 74 and 90, Sex and Cardiac Electrophysiology (Elsevier. 2020) and the rising prevalence of AF in the elderly population (Europace. 2019)

Appendices I English summary

II Dutch summary | Nederlandse samenvatting III Acknowledgements | Dankwoord

IV List of publications V About the author

9 25 49 73 95 115 147 161 166 170 174 178

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1

General introduction and

outline of the thesis

Mariëlle Kloosterman

“When the pulse is irregular and tremulous and the beats occur at intervals, then the impulse of life fades.’’ - Huang Di Nei Jing Su Wen, Yellow emperor of China, third

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RIsInG PRevAlenCe oF ATRIAl FIBRIllATIon

Atrial fibrillation (AF) is the most common sustained arrhythmia and its prevalence is rising.1-5_{Due to improvements in medical treatments and interventions patients} experi-ence increased longevity. This causes the risk of age-related diseases, such as AF, to grow. Recent studies, including the European BiomarCaRE consortium and Framing-ham study, estimate that the lifetime risk of AF in individuals from European ancestry has increased from ~1 in 4 to ~1 in 3 by age 90 years.1-5_{It is estimated that by 2060 there} will be almost 18 million patients with AF in the European Union, of which more than half a million in the Netherlands.6_{This poses a tremendous burden on health care} provi-sion and expenditure, with AF costs totaling well over €550 million in the Netherlands alone.7,8

Especially the prevalence of elderly patients with AF will increase in the coming four decades (Figure 1A). This is problematic since AF is associated with increased risk of adverse diseases and events, including among others, heart failure, stroke, myocardial infarction, dementia, and death.7,9_{These adverse events frequently occur in the older} AF patient (Figure 1B). AF diminishes the survival advantage typically observed in wom-en.10,11_{The increased risk of death is even the most frequent observed adverse event in} newly diagnosed patients and linked to (worsening) risk factors.12_{Early, comprehensive,} and aggressive treatment of these underlying risk factors might offer a solution.

RIsK FACToRs

The genesis and evolution of AF is complex and involves many, still incompletely under-stood, mechanisms. We know that several modifiable and non-modifiable risk factors promote the development and maintenance of AF. In almost all cases risk factors are present, making AF without underlying risk factors extremely rare.13_{Advancing age is} the key non-modifiable risk factor for AF, others include male sex, length, and genetic factors with currently 97 genome-wide susceptibility loci for AF identified in individuals of European ancestry.14-17_{Modifiable risk factors for AF include hypertension, coronary} artery disease, heart failure, obesity, diabetes, and valvular disease, just to name a few.18,19_{Subclinical or less-established risk factors, such as borderline hypertension,} chronic kidney disease, and sleep apnea syndrome, are gaining more attention.14,20 Electrical and structural remodeling of the atria is central in the disease process and heavily influenced by the normal ageing process21_{, the abovementioned risk factors,} as well as the arrhythmia itself (‘’AF begets AF’’) (Figure 2).22-24_{All these factors play}

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a role in inducing a unique atrial substrate that is characterized by atrial enlargement and conduction heterogeneity due to molecular and cellular changes, inflammation, fibrosis, fatty infiltration and atherosclerosis, making AF the manifestation of multiple pathophysiological pathways.22,23

Figure 1. Rising prevalence and adverse outcomes in elderly patients with AF

Panel A: Expected number (millions) of elderly patients with AF in the European Union in the coming four decades. Estimates are for the age categories >65 years (red), >75 years (grey), and >80 years (blue). Panel B: Cumulative incidence (%) of events in the 5-years after diagnosis of incident AF in elderly Medi-care patients (average age 79.5±7.3 years).7_{Reprinted from Kloosterman et al.}

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Often patients have multiple risk factors, making multimorbidity a common occurrence in clinical practice.25_{Prevalence of risk factors gradually increases when age rises and} lifetime risk of AF increases with this increased risk factor burden (Figure 2).20,26_In pa-tients with an optimal risk factor profile, defined as never smoker, 14 or less units of alcohol per week for men and 7 or less for women, a body mass index (BMI) below 25, no hypertension, no diabetes, and no history of heart failure or myocardial infarction, the lifetime risk of AF is estimated to be around ~25%. Patients with the highest risk factor burden defined as current smokers with an alcohol consumption of >14 units of alcohol per week for men and >7 units for women, a BMI of ≥30, hypertension, diabetes, and a history of heart failure or myocardial infarction have a ~38% lifetime risk of AF.26

Figure 2. AF substrate

AF is a complex, multifactorial, progressive disease with a substrate that is influenced by the normal age-ing process (age-induced remodelage-ing, grey), the underlyage-ing cardiovascular (CV) risk factors (CV disease-induced remodeling, red), and the arrhythmia itself (AF-disease-induced remodeling, blue). The normal ageing process and lifetime accumulation of risk factors will decrease patients’ resilience against AF. In the case of an optimal risk factor profile*, the lifetime risk for AF is around ~25%, in case of a high risk factor bur-den* this increases to around ~38%.26

*For a definition of the risk factor profiles see paragraph ‘’risk factors’’. AF, atrial fibrillation; CV, cardiovascular.

All in all AF is a complex, multifactorial, progressive disease, with an individually unique atrial substrate that may differ depending on the genetics, risk factors, sex, and other elements.16,17,27,28

seX DIFFeRenCes

AF plagues both women and men, but not in the same manner. Women are generally underrepresented in trials, but data on sex-specific differences in AF is accumulating, and in the recent years it has come to light that sex differences exist in all facets of

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the disease: from incidence, risk factors, and clinical presentation, to treatment and outcomes (Figure 3).29

Figure 3. Women experience differences in all facets of AF

Sex differences exists in all facets of AF, from epidemiology, clinical presentation and risk factors, to treat-ment and outcomes. AF, atrial fibrillation.

Women and men have a similar cumulative lifetime risk of AF but are generally older when AF is diagnosed, resulting in a lower age-adjusted incidence and prevalence.30 Women frequently have more AF risk factors (including hypertension, valvular disease, and heart failure with preserved ejection fraction), experience a higher symptom burden than men, and have a lower quality of life.31_{Women are often treated with} a more conservative approach based on rate control, and there is a tendency that women receive more calcium channel blockers and digoxin than men.30,32_{When they} do receive antiarrhythmic drugs women have an increased risk to suffer from brady- and tachyarrythmias, especially sick sinus syndrome and Torsades de Pointes.33,34_{Part of this} increased susceptibility can be explained by electrophysiology differences in corrected QT intervals.35,36_{But sex differences in pharmacodynamics and pharmacokinetics likely} also play an important role and contribute to differences in optimal doses of cardiovas-cular medications for women and men.37

Sex hormones also play a role, but the exact mechanisms and extent of their influ-ence, remain incompletely understood.38_{Women are also less likely to be referred for} catheter ablation and are older when they do receive the procedure.39-41_{Results of the} ablation tend to be less favorable, and procedure-related complications are more often observed in women, possibly associated with the older age at the time of ablation.41-43 Crude stroke rates are higher in women than in men. But whether this is because female sex has considerable interactions with age and other risk factors, or whether female sex is truly an independent risk factor remains topic of debate, especially in younger age

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groups or in the absence of risk factors.29,44_{Furthermore, AF-related mortality in women} is higher.11

ConCoMITAnT HeART FAIlURe

Heart failure has a high prevalence in patients with AF, with reported rates ranging from ~20% to ~70%; prevalence increases as the arrhythmia becomes more permanent.45,46 Vice versa all types of heart failure: reduced- (HFrEF), mid-range- (HFmrEF), and preserved ejection fraction (HFpEF), experience an increased risk of AF and reported prevalence is increasing. In the CHARM study (Candesartan in Heart failure-Assessment of Reduction in Mortality and morbidity) prevalence of AF was 19% in HFpEF and 17% in HFrEF.47_{The Framingham Heart Study reported slightly over 20% in both HFpEF} and HFrEF.48_{Medicare claim analyses report 48% AF in HFpEF and 44% in HFrEF.}49_Two recent studies highlight the extremely high burden of AF, especially in HFpEF and older patients with prevalence rates of 39-65% in HFpEF, 29-60% in HFmrEF, and 27-53% in HFrEF.50,51

When viewed as separate entities AF and heart failure are already complex clinical syndromes, but when occurring together, especially AF and HFpEF, they pose one of the most challenging conditions to date. Both conditions share risk factors and can pre-dispose to each other, but exact pathophysiological mechanisms remain unclear and

Figure 4. AF and heart failure

AF and heart failure are inextricably linked. They share many risk factors and can predispose to each other. Depicted are some mechanistic hypotheses (dotted lines) but exact pathophysiological mechanisms are unclear and untangling cause and effect remains difficult.

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a direct cause and effect paradigm is too simplistic (Figure 4).52_{The epidemiological,} clinical and mechanistic parallelisms between AF and HFpEF support the hypothesis that both conditions may be the manifestation of similar underlying myocardial dis-ease; an atrial and ventricular cardiomyopathy triggering a systemic manifestation of inflammation, metabolic disarray, and microvascular dysfunction and fibrosis with an important role for epicardial adipose tissue.53

In clinical practice affected patients are often the elderly with a significant risk factor burden.54_{Regardless of which condition occurs first, the combination of AF and heart} failure heralds a worse prognosis than when either condition occurs alone.55,56_Generally patients with AF have an almost 5-fold increased risk of heart failure9_{, and while stroke is} historically the most feared complication of AF, heart failure causes two to three times as many deaths in patients with AF.55_{In patients with congestive heart failure who develop} AF mortality rates double, while in patients with AF the development of congestive heart failure triples mortality.56_{In the last few years there have been several conflicting} studies and meta-analyses on mortality rates in HFrEF versus HFpEF patients with AF, but overall mortality risk seems at least as high, if not higher in patients with HFpEF and AF compared to patients with HFrEF and AF.50,51,57-60

Potential role for genetics and biomarkers

While the prevalence of combined heart failure and AF is high, some patients with AF will never develop heart failure, and some patients with heart failure will never develop AF. Gene polymorphisms, genetic risk scores, and blood biomarkers may improve our understanding of how, and in whom, AF develops.61_{Genetics may point towards} devel-opmental factors and molecular mechanisms of the arrhythmia, and blood biomarkers, although often not specific to just atrial myocardial disease, may provide insight into the pathophysiological mechanisms and specific pathways involved in disease develop-ment and progression.62_{Assessing a combination of these alterations could} character-ize different AF populations, which ultimately could help to personalcharacter-ize management.

AIMs oF THe THesIs

AF encompasses so much more than just an irregular heart rhythm and is one of the major chronic conditions and challenges in modern cardiology. More insight into some key factors may provide the first steps in improving AF care for the individual patient. This requires stepping away from a single-disease framework and creating more awareness of: the multimorbidity that plagues AF patients, including subclinical and less-established risk factors; knowledge of sex differences in risk factor profiles,

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treat-ment (utilization) and outcome; and elucidation of genetic risk and biomarker profiles of AF patients with concomitant HFrEF or HFpEF as a first step towards risk stratification and potentially novel therapeutic targets by gaining more insights into the underlying pathophysiological mechanisms.

This thesis aims to better characterize these multifaceted aspects of AF and consists of sub-analyses from several large (inter)national studies. In Chapter 2 we studied prevalence, patient characteristics, and outcomes of AF patients without traditional risk factors in the RE-LY AF registry, a study that included 15400 patients with AF from emergency departments in 47 countries worldwide. In Chapter 3 we assessed sex dif-ferences in risk factors, outcome and quality of life in elderly patients with permanent AF enrolled in the Rate Control Efficacy in Permanent AF: A Comparison between Lenient versus Strict Rate Control II (RACE II) study. RACE II recruited patients from 33 centers in the Netherlands. In Chapter 4 we assessed sex differences in patients undergoing first-time catheter ablation under continuous anticoagulation in The Anticoagulation using the direct factor Xa inhibitor apixaban during Atrial Fibrillation catheter Abla-tion: comparison to vitamin K antagonist therapy (AXAFA-AFNET 5) study. The trial was conducted in 48 sites in Europe and North America. In Chapter 5 we studied the association between a genetic risk score based on 97 single nucleotide polymorphism with prevalent AF and all-cause mortality. For this we used a large sample of patients with heart failure included in The BIOlogy Study to Tailored Treatment in Chronic Heart Failure (BIOSTAT-CHF) study, consisting of an index cohort that enrolled patients from 11 European countries, as well as a validation cohort from Scotland. In Chapter 6 we studied blood biomarker profiles, consisting of 92 cardiovascular risk markers, compar-ing sinus rhythm and AF in heart failure patients from BIOSTAT-CHF with reduced and preserved ejection fraction.

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ReFeRenCes

1. Lloyd-Jones DM, Wang TJ, Leip EP, et al. Lifetime risk for development of atrial fibrillation: the Framingham Heart Study.

Circulation. 2004; 110: 1042-1046.

2. Heeringa J, van der Kuip DA, Hofman A, et al. Prevalence, incidence and lifetime risk of atrial fibrillation: the Rotterdam study. Eur

Heart J. 2006; 27: 949-953.

3. Magnussen C, Niiranen TJ, Ojeda FM, et al. Sex Differences and Similarities in Atrial Fibrillation Epidemiology, Risk Fac-tors, and Mortality in Community Cohorts: Results From the BiomarCaRE Consortium (Biomarker for Cardiovascular Risk Assess-ment in Europe). Circulation. 2017; 136: 1588-1597.

4. Weng LC, Preis SR, Hulme OL, et al. Genetic Predisposition, Clinical Risk Factor Burden, and Lifetime Risk of Atrial Fibrillation.

Cir-culation. 2018; 137: 1027-1038.

5. Mou L, Norby FL, Chen LY, et al. Lifetime Risk of Atrial Fibrillation by Race and Socio-economic Status: ARIC Study (Atheroscle-rosis Risk in Communities). Circ Arrhythm

Electrophysiol. 2018; 11: e006350.

6. Krijthe BP, Kunst A, Benjamin EJ, et al. Pro-jections on the number of individuals with atrial fibrillation in the European Union, from 2000 to 2060. Eur Heart J. 2013; 34: 2746-2751.

7. Piccini JP, Hammill BG, Sinner MF, et al. Clinical course of atrial fibrillation in older adults: the importance of cardiovascular events beyond stroke. Eur Heart J. 2014; 35: 250-256.

8. Ringborg A, Nieuwlaat R, Lindgren P, et al. Costs of atrial fibrillation in five European countries: results from the Euro Heart Sur-vey on atrial fibrillation. Europace. 2008; 10: 403-411.

9. Ruddox V, Sandven I, Munkhaugen J, Skattebu J, Edvardsen T, Otterstad JE. Atrial fibrillation and the risk for myocardial infarction, all-cause mortality and heart

fail-ure: A systematic review and meta-analysis.

Eur J Prev Cardiol. 2017; 24: 1555-1566.

10. Benjamin EJ, Wolf PA, D’Agostino RB, Silbershatz H, Kannel WB, Levy D. Impact of atrial fibrillation on the risk of death: the Framingham Heart Study. Circulation. 1998; 98: 946-952.

11. Emdin CA, Wong CX, Hsiao AJ, et al. Atrial fibrillation as risk factor for cardiovascular disease and death in women compared with men: systematic review and meta-analysis of cohort studies. BMJ. 2016; 532: h7013.

12. Bassand JP, Accetta G, Al Mahmeed W, et al. Risk factors for death, stroke, and bleed-ing in 28,628 patients from the GARFIELD-AF registry: Rationale for comprehensive management of atrial fibrillation. PLoS

One. 2018; 13: e0191592.

13. Wyse DG, Van Gelder IC, Ellinor PT, et al. Lone atrial fibrillation: does it exist? J Am

Coll Cardiol. 2014; 63: 1715-1723.

14. Kirchhof P, Lip GY, Van Gelder IC, et al. Comprehensive risk reduction in patients with atrial fibrillation: emerging diagnostic and therapeutic options--a report from the 3rd Atrial Fibrillation Competence NET-work/European Heart Rhythm Association consensus conference. Europace. 2012; 14: 8-27.

15. Roselli C, Chaffin MD, Weng LC, et al. Multi-ethnic genome-wide association study for atrial fibrillation. Nat Genet. 2018; 50: 1225-1233.

16. Andrade J, Khairy P, Dobrev D, Nattel S. The clinical profile and pathophysiology of atrial fibrillation: relationships among clinical features, epidemiology, and mecha-nisms. Circ Res. 2014; 114: 1453-1468. 17. Staerk L, Sherer JA, Ko D, Benjamin EJ,

Helm RH. Atrial Fibrillation: Epidemiology, Pathophysiology, and Clinical Outcomes.

Circ Res. 2017; 120: 1501-1517.

(20)

RB, Belanger AJ, Wolf PA. Independent risk factors for atrial fibrillation in a population-based cohort. The Framingham Heart Study. JAMA. 1994; 271: 840-844.

19. Vermond RA, Geelhoed B, Verweij N, et al. Incidence of Atrial Fibrillation and Relation-ship With Cardiovascular Events, Heart Failure, and Mortality: A Community-Based Study From the Netherlands. J Am Coll

Cardiol. 2015; 66: 1000-1007.

20. Lau DH, Nattel S, Kalman JM, Sanders P. Modifiable Risk Factors and Atrial Fibrilla-tion. CirculaFibrilla-tion. 2017; 136: 583-596. 21. Laredo M, Waldmann V, Khairy P, Nattel

S. Age as a Critical Determinant of Atrial Fibrillation: A Two-sided Relationship. Can

J Cardiol. 2018; 34: 1396-1406.

22. Shen MJ, Arora R, Jalife J. Atrial Myopathy.

JACC Basic Transl Sci. 2019; 4: 640-654.

23. Everett TH,4th, Olgin JE. Atrial fibrosis and the mechanisms of atrial fibrillation. Heart

Rhythm. 2007; 4: S24-7.

24. Nattel S, Harada M. Atrial remodeling and atrial fibrillation: recent advances and trans-lational perspectives. J Am Coll Cardiol. 2014; 63: 2335-2345.

25. Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet. 2012; 380: 37-43.

26. Staerk L, Wang B, Preis SR, et al. Lifetime risk of atrial fibrillation according to opti-mal, borderline, or elevated levels of risk factors: cohort study based on longitudinal data from the Framingham Heart Study.

BMJ. 2018; 361: k1453.

27. Nattel S, Burstein B, Dobrev D. Atrial remodeling and atrial fibrillation: mecha-nisms and implications. Circ Arrhythm

Electrophysiol. 2008; 1: 62-73.

28. Lau DH, Schotten U, Mahajan R, et al. Novel mechanisms in the pathogenesis of atrial fibrillation: practical applications. Eur Heart

J. 2016; 37: 1573-1581.

29. Linde C, Bongiorni MG, Birgersdotter-Green U, et al. Sex differences in cardiac arrhythmia: a consensus document of the European Heart Rhythm Association, endorsed by the Heart Rhythm Society and Asia Pacific Heart Rhythm Society.

Europace. 2018; .

30. Lip GY, Laroche C, Boriani G, et al. Sex-related differences in presentation, treat-ment, and outcome of patients with atrial fibrillation in Europe: a report from the Euro Observational Research Programme Pilot survey on Atrial Fibrillation. Europace. 2015; 17: 24-31.

31. Ko D, Rahman F, Schnabel RB, Yin X, Benja-min EJ, Christophersen IE. Atrial fibrillation in women: epidemiology, pathophysiology, presentation, and prognosis. Nat Rev

Car-diol. 2016; 13: 321-332.

32. Weberndorfer V, Beinart R, Ricciardi D, et al. Sex differences in rate and rhythm con-trol for atrial fibrillation. Europace. 2019; . 33. Ehdaie A, Cingolani E, Shehata M, Wang

X, Curtis AB, Chugh SS. Sex Differences in Cardiac Arrhythmias: Clinical and Research Implications. Circ Arrhythm Electrophysiol. 2018; 11: e005680.

34. Rienstra M, Van Veldhuisen DJ, Hagens VE, et al. Gender-related differences in rhythm control treatment in persistent atrial fibrillation: data of the Rate Control Versus Electrical Cardioversion (RACE) study. J Am

Coll Cardiol. 2005; 46: 1298-1306.

35. Rosano GM, Lewis B, Agewall S, et al. Gender differences in the effect of cardio-vascular drugs: a position document of the Working Group on Pharmacology and Drug Therapy of the ESC. Eur Heart J. 2015; 36: 2677-2680.

36. Tamargo J, Rosano G, Walther T, et al. Gender differences in the effects of car-diovascular drugs. Eur Heart J Cardiovasc

Pharmacother. 2017; 3: 163-182.

37. Santema BT, Ouwerkerk W, Tromp J, et al. Identifying optimal doses of heart failure medications in men compared with women:

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a prospective, observational cohort study.

Lancet. 2019; (in press).

38. Odening KE, Deiss S, Dilling-Boer D, et al. Mechanisms of sex differences in atrial fi-brillation: role of hormones and differences in electrophysiology, structure, function, and remodelling. Europace. 2019; 21: 366-376.

39. Avgil Tsadok M, Gagnon J, Joza J, et al. Temporal trends and sex differences in pulmonary vein isolation for patients with atrial fibrillation. Heart Rhythm. 2015; 12: 1979-1986.

40. Kuck KH, Brugada J, Furnkranz A, et al. Impact of Female Sex on Clinical Outcomes in the FIRE AND ICE Trial of Catheter Abla-tion for Atrial FibrillaAbla-tion. Circ Arrhythm

Electrophysiol. 2018; 11: e006204.

41. Zylla MM, Brachmann J, Lewalter T, et al. Sex-related outcome of atrial fibrillation ablation: Insights from the German Abla-tion Registry. Heart Rhythm. 2016; 13: 1837-1844.

42. Ko D, Rahman F, Martins MA, et al. Atrial fibrillation in women: treatment. Nat Rev

Cardiol. 2017; 14: 113-124.

43. Patel D, Mohanty P, Di Biase L, et al. Out-comes and complications of catheter abla-tion for atrial fibrillaabla-tion in females. Heart

Rhythm. 2010; 7: 167-172.

44. Renoux C, Coulombe J, Suissa S. Revisiting sex differences in outcomes in non-valvular atrial fibrillation: a population-based cohort study. Eur Heart J. 2017; 38: 1473-1479. 45. Ling LH, Kistler PM, Kalman JM, Schilling

RJ, Hunter RJ. Comorbidity of atrial fibril-lation and heart failure. Nat Rev Cardiol. 2016; 13: 131-147.

46. Chiang CE, Naditch-Brule L, Murin J, et al. Distribution and risk profile of paroxysmal, persistent, and permanent atrial fibrillation in routine clinical practice: insight from the real-life global survey evaluating patients with atrial fibrillation international registry.

Circ Arrhythm Electrophysiol. 2012; 5:

632-639.

47. Olsson LG, Swedberg K, Ducharme A, et al. Atrial fibrillation and risk of clinical events in chronic heart failure with and without left ventricular systolic dysfunction: results from the Candesartan in Heart failure-Assessment of Reduction in Mortality and morbidity (CHARM) program. J Am Coll

Cardiol. 2006; 47: 1997-2004.

48. Santhanakrishnan R, Wang N, Larson MG, et al. Atrial Fibrillation Begets Heart Failure and Vice Versa: Temporal Associations and Differences in Preserved Versus Reduced Ejection Fraction. Circulation. 2016; 133: 484-492.

49. Eapen ZJ, Greiner MA, Fonarow GC, et al. Associations between atrial fibrillation and early outcomes of patients with heart failure and reduced or preserved ejection fraction. Am Heart J. 2014; 167: 369-375.e2. 50. Sartipy U, Dahlstrom U, Fu M, Lund LH.

Atrial Fibrillation in Heart Failure With Pre-served, Mid-Range, and Reduced Ejection Fraction. JACC Heart Fail. 2017; 5: 565-574. 51. Zafrir B, Lund LH, Laroche C, et al. Prog-nostic implications of atrial fibrillation in heart failure with reduced, mid-range, and preserved ejection fraction: a report from 14 964 patients in the European Society of Cardiology Heart Failure Long-Term Regis-try. Eur Heart J. 2018; 39: 4277-4284. 52. Kotecha D, Lam CS, Van Veldhuisen DJ,

Van Gelder IC, Voors AA, Rienstra M. Heart Failure With Preserved Ejection Fraction and Atrial Fibrillation: Vicious Twins. J Am

Coll Cardiol. 2016; 68: 2217-2228.

53. Packer M, Lam CSP, Lund LH, Redfield MM. Interdependence of Atrial Fibrillation and Heart Failure With a Preserved Ejection Fraction Reflects a Common Underlying Atrial and Ventricular Myopathy.

Circula-tion. 2020; 141: 4-6.

54. Kotecha D, Piccini JP. Atrial fibrillation in heart failure: what should we do? Eur Heart

J. 2015; 36: 3250-3257.

55. Marijon E, Le Heuzey JY, Connolly S, et al. Causes of death and influencing factors in

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patients with atrial fibrillation: a competing-risk analysis from the randomized evalu-ation of long-term anticoagulant therapy study. Circulation. 2013; 128: 2192-2201. 56. Wang TJ, Larson MG, Levy D, et al.

Tempo-ral relations of atrial fibrillation and conges-tive heart failure and their joint influence on mortality: the Framingham Heart Study.

Circulation. 2003; 107: 2920-2925.

57. Kotecha D, Chudasama R, Lane DA, Kirch-hof P, Lip GY. Atrial fibrillation and heart failure due to reduced versus preserved ejection fraction: A systematic review and meta-analysis of death and adverse out-comes. Int J Cardiol. 2016; 203: 660-666. 58. Cheng M, Lu X, Huang J, Zhang J, Zhang S,

Gu D. The prognostic significance of atrial fibrillation in heart failure with a preserved and reduced left ventricular function: insights from a meta-analysis. Eur J Heart

Fail. 2014; 16: 1317-1322.

59. McManus DD, Hsu G, Sung SH, et al. Atrial fibrillation and outcomes in heart failure with preserved versus reduced left ven-tricular ejection fraction. J Am Heart Assoc. 2013; 2: e005694.

60. Linssen GC, Rienstra M, Jaarsma T, et al. Clinical and prognostic effects of atrial fibrillation in heart failure patients with reduced and preserved left ventricular ejection fraction. Eur J Heart Fail. 2011; 13: 1111-1120.

61. Kalsto SM, Siland JE, Rienstra M, Chris-tophersen IE. Atrial Fibrillation Genetics Update: Toward Clinical Implementation.

Front Cardiovasc Med. 2019; 6: 127.

62. Hijazi Z, Oldgren J, Siegbahn A, Granger CB, Wallentin L. Biomarkers in atrial fibrilla-tion: a clinical review. Eur Heart J. 2013; 34: 1475-1480.

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Part I

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2

Characteristics and outcomes of

atrial fibrillation in patients without

traditional risk factors: a Re-lY AF

registry analysis

Mariëlle Kloosterman, Jonas Oldgren, David Conen, Jorge A. Wong, Stuart J. Connolly, Alvaro Avezum, Salim Yusuf, Michael D. Ezekowitz, Lars Wallentin, Marie Ntep-Gweth, Philip Joseph, Tyler W. Barrett, Supachai Tanosmsup, William F. McIntyre, Shun Fu Lee, Ratika Parkash, Guy Amit, Alex Grinvalds, Isabelle C. Van Gelder, Jeff S. Healey.

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26

ABsTRACT

Background: Data on patient characteristics, prevalence, and outcomes of AF patients

without traditional risk factors, often labelled “lone AF”, is sparse.

Methods: The RE-LY AF registry included 15,400 individuals who presented to

emer-gency departments with AF in 47 countries. This analysis focused on patients without traditional risk factors, including: age ≥60 years, hypertension, coronary artery disease, heart failure, left ventricular hypertrophy, congenital heart disease, pulmonary disease, valve heart disease, hyperthyroidism, and prior cardiac surgery. Patients without tradi-tional risk factors were compared to age- and region-matched controls with traditradi-tional risk factors (1:3 fashion).

Results: In 796 (5%) patients, no traditional risk factors were present. However, 98%

(779/796) had less-established or borderline risk factors, including borderline hyper-tension (130-140/80-90 mmHg; 47%), chronic kidney disease (eGFR<60 ml/min; 57%), obesity (BMI>30; 19%), diabetes (5%), excessive alcohol intake (>14 units/week; 4%), and smoking (25%). Compared to patients with traditional risk factors (N=2388), pa-tients without traditional risk factors were more often men (74% versus 59%, P<0.001), had paroxysmal AF (55% versus 37%, P<0.001) and less AF persistence after 1-year (21% versus 49%, P<0.001). Furthermore, 1-year stroke occurrence rate (0.6% versus 2.0%, P=0.013), and heart failure hospitalizations (0.9% versus 12.5%, P<0.001) were lower. However; risk of AF-related re-hospitalization was similar (18% versus 21%, P=0.09).

Conclusion: Almost all patients without traditionally-defined AF risk factors have

less-established or borderline risk factors. These patients have a favourable 1-year progno-sis, but risk of AF-related re-hospitalization remains high. Greater emphasis should be placed on recognition and management of less-established or borderline risk factors.

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InTRoDUCTIon

Sixty-five years ago atrial fibrillation (AF) in the absence of heart disease was coined ‘lone AF’.1_{However, that concept has come under scrutiny}2_{as our knowledge of risk} factors and their importance is evolving.2-4_{Over the last decade, a re-evaluation of} traditional frameworks for understanding and managing of AF occurred, and focus has shifted towards optimal treatment of underlying conditions and risk factors. This includes less-established and borderline risk factors such as obesity, diabetes, sleep ap-noea, borderline hypertension, chronic kidney disease, smoking, and excessive alcohol intake.2,5_{Furthermore, many thresholds for detecting and defining comorbid conditions} have changed, making some conditions such as hypertension more prevalent.2,4_{Due to} this improved ascertainment of underlying cardiovascular diseases and risk factors, the reported proportion of seemingly ‘’lone AF’’ decreased over the years from ~30% to ~3%.2,6,7_{Therefore it has been recommended that use of the term ‘’lone AF’’ should be} avoided.2_{Nevertheless it still remains in use today.}

Our current understanding of outcomes in AF patients previously thought to have ‘’lone AF’’ is largely confined to patients from North America and Europe.3,6,8,9_{This is a major} limitation since we know that important regional variation exists among the global population of individuals with AF.10-12_{The current analysis aimed to examine patient} characteristics, prevalence of less-established or borderline risk factors, and outcome in patients without traditional risk factors from different geographic regions using data from the Randomized Evaluation of Long-Term Anticoagulation Therapy (RE-LY) AF registry 10,11

MeTHoDs

Re-lY AF registry

The methods of the RE-LY AF registry have been described previously.10,11_{Patients from} 164 sites in 47 countries, representing all inhabited continents, who presented to an emergency department or equivalent acute-care setting with AF or atrial flutter (AFL), were included in this prospective registry. The atrial rhythm disturbance could be either the primary reason for their visit or a secondary diagnosis. Although patients were not consecutive, study sites were encouraged to enrol patients as rapidly as possible to minimize bias. All patients gave written informed consent for study participation.

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28

study population

Between December 24, 2007 and October 21, 2011, 15,400 patients were enrolled, of whom 97.7% had AF and the rest had AFL. The present analysis excluded all patients with traditional AF risk factors including: advancing age (≥60 years), myocardial infarc-tion, coronary artery disease, congenital heart disease, heart failure, left ventricular hypertrophy or systolic dysfunction, hypertension, rheumatic heart disease, significant valvular heart disease (defined as moderate to severe [grade 3] or severe [grade 4]), pulmonary disease including emphysema and chronic obstructive pulmonary disease, stroke or transient ischemic attack, hyperthyroidism, or recent cardiac surgery.

Figure 1. Traditional risk factors

The columns show the traditional risk factors used in the Framingham, Olmsted and RE-LY cohorts.3,6,9

* Secondary precipitants for AF were excluded, including acute coronary syndrome or arrest, pericarditis or pericardial effusion (in our cohort mainly caused by tuberculosis and HIV), myocarditis, pulmonary oedema, cerebrovascular vascular accident, aortic dissection, ICD shock or heart failure.

† Patients with AF related to surgery, trauma, or acute medical illness were excluded. ‡ Insulin dependent diabetes mellitus.

AF denotes atrial fibrillation; BMI, body mass index; eGFR, estimated glomerular filtration rate; TIA, transient ischemic attack.

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These “traditional” risk factors are the ones used in the Olmsted Country and Framing-ham cohorts (Figure 1), 3,9_{whose absence used to define “lone AF”. The non-traditional} risk factors, and the terminology ‘’ less-established and borderline’’ are in line with the 2014 ‘’Lone AF does it exist’’ paper by Wyse et al. 2

Patients with missing variables (N=10) or patients with secondary precipitants for AF including acute coronary syndrome, acute pericardial disease, heart failure, infection, or other acute cerebral-, pulmonary- or rheumatic disease, were excluded from the current analysis (Figure 2 and Supplementary Table 1).

Figure 2. Flowchart

* No myocardial infarction, coronary artery disease, congenital heart disease, heart failure, left ventricular hypertrophy or systolic dysfunction, hypertension, rheumatic heart disease or significant valvular disease. † Defined as emphysema or chronic obstructive pulmonary disease.

AF denotes atrial fibrillation; CVA, cerebrovascular accident; ED, emergency department; TIA, transient ischemic attack.

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30

We studied the following less-established or borderline risk factors: borderline hyper-tension (RR 130-140/80-90 mmHg), chronic kidney disease (eGFR<60 ml/min), obesity (body mass index (BMI) >30), diabetes (oral glucose-lowering drugs and/or insulin), excessive alcohol intake (>14 units/week), smoking, and sleep apnoea (Figure 1).2_Our aim was to examine patient characteristics, study prevalence of less-established or borderline risk factors, and assess outcome. We compared patients without traditional risk factors to age- and region-matched controls with traditional risk factors (1:3 fashion) from the RE-LY AF Registry.10,11_{Additionally, regional comparisons were performed to} provide a global overview of region-specific differences.

Follow-up

Patients were assessed one year after attending the emergency department. The visit occurred either in-person or consisted of a telephone call. The validated questionnaire for the verification of stroke-free status was administered to all patients. Additional required information was collected from medical records and contact with treating physicians. Clinical data were collected on the endpoints death, stroke, major bleeding and systemic embolism, as well as admission to hospital for heart failure, myocardial infarction, AF or AFL. Data were collected on treatment of AF during follow-up includ-ing cardioversion, ablation, and rate and rhythm control therapy.

statistical analysis

Baseline characteristics of patients without traditional risk factors and 1:3 matched subset of patients with traditional risk factors are shown for both groups overall and for the different regions. Patients from North America, Western Europe, and Austra-lia were used as the reference population for comparison with patients from South America, Eastern Europe, the Middle East and Mediterranean crescent (including North Africa and Turkey), Sub-Saharan Africa, India, China, and Southeast Asia (participating countries by region were previously published).10_{Data are presented as mean (SD)} and median (IQR) for continuous variables and frequency (percentage) for categorical variables. Differences between patients were evaluated by the Student t test and the Mann-Whitney U test, depending on normality of the data. Chi-square and Fisher’s exact test were used for comparison of categorical variables. Comparisons between the regions, with North America, Western Europe and Australia as the reference group, were performed using an ANOVA or Kruskal-Wallis test for continuous variables and using Pearson’s χ2_{test or Fisher’s exact test for categorical variables. Outcomes were} compared using logistic regression models with relative risk (RR) and 95% confidence interval (CI) reported. Models were subsequently adjusted for: sex, chronic kidney disease, diabetes mellitus, and anticoagulation/antiplatelet therapy, including warfarin, vitamin K antagonist or aspirin. The two-sided significance level was set at 0.005 to

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adjust for multiple comparisons. All statistical analyses were performed using SAS 9.4 for UNIX (SAS Institute Inc., Cary, North Carolina).

ResUlTs

Patient characteristics

Of the 15,400 patients enrolled in the RE-LY AF registry, 796 (5%) did not have traditionally-defined risk factors (Figure 2). Prevalence differed between the regions: ranging from 2% in Eastern Europe to 15% in the Middle East. Baseline characteristics are summarized in Table 1 for patients without and with traditional risk factors. Aver-age Aver-age of patients without traditional risk factors was 45.7±10.1 years, and 74% were men. Compared to patients with traditional risk factors, patients without traditional risk factors were taller, weighed more, were more likely to be men, and had slightly better kidney function (Table 1).

The most common less-established or borderline risk factors were borderline hyper-tension (130-140/80-90 mmHg; 47%), chronic kidney disease (eGFR<60 ml/min; 57%), obesity (BMI >30 kg/m2_{; 19%), and smoking (25%). (Table 1) In total 779 of 796 (98%)} patients had one or more less-established or borderline risk factors. Less-established or borderline risk factors were present in a comparable or lower number in patients with traditional risk factors (Table 1).

Among patients without traditional risk factors, the prevalence of specific less-estab-lished or borderline risk factors differed between regions (Table 1). In North America and Western Europe obesity was common (30%), and in the Middle East, both obesity (25%) and diabetes mellitus (11%) were frequent. In Eastern Europe borderline hyper-tension (65%), excessive alcohol intake (8%), and smoking (38%) were often found. In South America (83%) and India (94%), high percentages of chronic kidney disease were observed, and in Africa 22% of patients used large amounts of alcohol.

Type and treatment of atrial fibrillation

Patients without traditional risk factors more often had paroxysmal AF (55% versus 37%, P<0.001), and were more likely to undergo cardioversion in the emergency department, ei-ther spontaneously or through electrical or chemical cardioversion (P<0.001) (Supplemen-tary Table 2.1). Fewer patients without traditional risk factors left the emergency department in AF compared to patients with traditional risk factors (54% versus 77%, P<0.001). Patients without traditional risk factors received less medications, including anticoagulation, anti-arrhythmic drugs, beta-blockade, and diuretics (all P<0.001) (Supplementary Table 2.1).

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32 33

Chapter 2

Table 1. Baseline characteristics in patients without and with traditional risk factors

o verall n orth America, W ester n e ur ope, and Australia south _America e aster n e ur ope Middle e ast Africa India China southeast Asia P-value†

AF without traditional risk factors - %

5.2% 7.5% 4.6% 1.5% 14.9% 3.2% 3.2% 4.5% 6.2%

Number (matched 1:3) without traditional risk factors

796 286 52 37 132 36 80 90 83

with traditional risk factors

2388 648 150 127 280 234 466 279 204

Demographics Age - years (SD) without traditional risk factors

45.7±10.1 47.6±9.4 45.4±9.6 48.1±9.5 41.2±10.3* 43.3±11.8 45.5±9.6 45.3±10.8 47.2±9.5 <0.001

46.4±11.9 54.3±7.3 49.2±8.7* 48.2±8.3* 46.5±9.3* 32.4±14.5 38.2±11.4 48.1±7.7 50.7±6.9 <0.001

Male (%) without traditional risk factors

588 (73.9) § 227 (79.4) 38 (73.1) 30 (81.1) 106 (80.3) 24 (66.7) 46 (57.5)* 59 (65.6) 58 (69.9) 0.001

1410 (59.0) 484 (74.7) 97 (64.7) 94 (74.0) 177 (63.2) 96 (41.0) 203 (43.6) 136 (48.7) 123 (60.3) < 0.001

Height - cm (SD) without traditional risk factors

172.4±10.2 § 178.0±9.4 172.5±10.1* 177.5±9.1 171.2±7.9* 168.7±7.7* 162.9±8.7* 169.2±7.8* 166.8±9.0* <0.001

167.9±11.5 176.0±10.0 167.4±10.5* 175.7±8.9 166.1±9.2* 160.9±13.0* 161.7± 9.1* 165.6±8.7* 165.4±9.5* <0.001 W

eight - kg (SD) without traditional risk factors

79.6±18.7 § 90.4±18.3 78.8±12.5* 84.6±14.8 80.1±17.8* 76.0±19.4* 64.6±12.9* 70.7±11.8* 65.8±12.3* <0.001

75.8±25.5 98.2±26.3 78.6±18.1* 91.1±20.3* 76.9±19.2* 59.2±20.0* 57.0±13.2* 65.2±14.4* 69.0±15.8* <0.001

Body mass index - kg/m

2 (SD)

without traditional risk factors

26.7±5.3 28.6±6.0 26.5±3.9* 26.7±3.2* 27.2±5.3 26.7±7.2 24.3±4.0* 24.6±3.5* 23.5±3.3* <0.001

26.6±7.4 31.7±8.4 28.0±5.7* 29.5±6.0* 27.9±6.4* 22.5±6.1* 21.7±4.4* 23.6±4.1* 25.4±5.2 <0.001

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Table 1. Baseline characteristics in patients without and with traditional risk factors (continued) o verall n orth America, W ester n e ur ope, and Australia south _America e aster n e ur ope Middle e ast Africa India China southeast Asia P-value† eGFR - ml/min*1.73m 2 (SD)

87.9±27.0 § 87.9±25.4 66.2±20.0* 83.1±20.8 87.0±22.7 86.4±29.2 62.1±24.9 88.9±25.7 100.8±32.8 <0.001

80.0±55.5 80.7±54.2 66.7±22.2 83.7±24.3 750±32.3 86.8±54.0 61.5±21.3* 79.4±29.6 81.0±37.8 0.230 Blood pr essur e - mmHg (SD) ▪ Systolic

125±20 130±21 120±18* 122±15 123±20* 115±16* 119±17* 122±21* 125±18 <0.001

126±23 133±23 128±25 133±22 129±26 115±21* 119±19* 121±22* 129±21 <0.001 ▪ Diastolic

79±14 84±15 77±13* 77±8* 77±14* 73±12* 77±11* 77±13* 76±12* <0.001

80±15 84±17 81±16 84±12 81±17 75±16* 77±11* 78±15* 78±16* <0.001

Prior diagnosis of AF (%) without traditional risk factors

375 (47.1) § 159 (55.6) 25 (48.1) 28 (75.7) 35 (26.5)* 6 (16.7)* 25 (31.3)* 57 (63.3) 40 (48.2) <0.001

1428 (59.8) 435 (67.1) 101 (67.3) 90 (70.9) 152 (54.3)* 103 (44.0)* 195 (41.8* 220 (78.9)* 132 (64.7) <0.001 AF type (%) ▪ Par oxysmal

440 (55.3) § 175 (61.2) 18 (34.6)* 13 (35.1)* 70 (53.0) 18 (50.0) 43 (53.8) 44 (48.9) 59 (71.1) <0.001

887 (37.2) 331 (51.2) 26 (17.3)* 48 (37.8) 68 (24.3)* 26 (11.1)* 202 (43.3) 89 (31.9)* 97 (47.5) <0.001 ▪ Persistent

268 (33.7) § 99 (34.6) 26 (50.0) 20 (54.1) 42 (31.8) 8 (22.2) 28 (35.0) 33 (36.7) 12 (14.5)* <0.001

636 (26.6) 205 (31.7) 59 (39.3) 44 (34.6) 48 (17.1)* 42 (17.9)* 124 (26.6) 66 (23.7) 48 (23.5) <0.001 ▪ Permanent

88 (11.1) § 12 (4.2) 8 (15.4) 4 (10.8) 20 (15.2)* 10 (27.8)* 9 (11.3) 13 (14.4)* 12 (14.5)* <0.001‡

864 (36.2) 111 (17.2) 65 (43.3)* 35 (27.6) 164 (58.6)* 166 (70.9)* 140 (30.0)* 124 (44.4)* 59 (28.9)* <0.001

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34 35

Chapter 2

Table 1. Baseline characteristics in patients without and with traditional risk factors (continued)

o verall n orth America, W ester n e ur ope, and Australia south _America e aster n e ur ope Middle e ast Africa India China southeast Asia P-value†

Reason for initial ED visit (%) ▪

Atrial Fibrillation

590 (74.1) § 207 (72.4) 45 (86.5) 32 (86.5) 108 (81.8) 20 (55.6) 52 (65.0) 75 (83.3) 51 (61.4) <0.001

1178 (49.3) 390 (60.2) 86 (57.3) 89 (70.1) 120 (42.9)* 63 (26.9)* 238 (51.1)* 109 (30.1)* 83 (40.7)* <0.001

less - established or bor

derline risk factors (%)

Bor

derline hypertension (130 -

140/80 - 90 mmHg) without traditional risk factors

372 (46.8) 134 (46.9) 25 (48.1) 24 (64.9) 64 (48.5) 15 (41.7) 41 (51.9) 34 (37.8) 35 (42.2) 0.194

1040 (43.7) 279 (43.1) 70 (47.0) 85 (66.9)* 94 (33.6) 77 (33.) 227 (49.1) 125 (45.0) 83 (40.7) <0.001 Chr

onic kidney disease (eGFR<60) _{without traditional risk factors}

456 (57.3) § 162 (56.6) 43 (82.7)* 29 (78.4) 48 (36.4)* 20 (55.6) 75 (93.8)* 48 (53.3) 31 (37.3)* <0.001

1563 (65.5) 355 (54.8) 115 (76.7)* 102 (80.3)* 121 (43.2)* 155 (66.2)* 449 (96.4) 192 (68.8)* 74 (36.3)* <0.001

Obesity (body mass index>30) without traditional risk factors

153 (19.2) § 85 (29.7) 9 (17.3) 4 (10.8) 33 (25.0) 8 (22.2) 6 (7.5)* 5 (5.6)* 3 (3.6)* <0.001

566 (23.7) 309 (47.4) 47 (31.3)* 50 (39.4) 81 (28.9)* 19 (8.1)* 10 (2.1)* 19 (6.8)* 31 (15.2)* <0.001

Diabetes mellitus without traditional risk factors

36 (4.5) § 8 (2.8) 0 (-) 0 (-) 14 (10.6)* 2 (5.6) 6 (7.5) 3 (3.3) 3 (3.6) 0.011‡

378 (15.8) 132 (20.4) 24 (16.0) 21 (16.5) 75 (26.8) 13 (5.6)* 33 (7.1)* 28 (10.0)* 52 (25.5) <0.001

Excessive alcohol intake (>14/ week) without traditional risk factors

31 (3.9) 18 (6.3) 0 (-) 3 (8.1) 0 (-)* 8 (22.2)* 0 (-) 2 (2.2) 0 (-) <0.001‡

62 (2.6) 43 (6.6) 2 (1.3) 5 (3.9) 1 (0.4)* 2 (0.9)* 1 (0.2)* 4 (1.4)* 4 (2.0) <0.001‡

Smoking without traditional risk factors

197 (24.7) 65 (22.7) 14 (26.9) 14 (37.8) 42 (31.8) 8 (22.2) 6 (7.5)* 20 (22.2) 28 (33.7) <0.001

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Table 1. Baseline characteristics in patients without and with traditional risk factors (continued) o verall n orth America, W ester n e ur ope, and Australia south _America e aster n e ur ope Middle e ast Africa India China southeast Asia P-value†

519 (21.7) 184 (28.4) 29 (19.3) 41 (32.3) 77 (27.5) 19 (8.1)* 29 (6.2)* 81 (29.0) 59 (28.9) <0.001

Sleep apnoea without traditional risk factors

15 (1.9) § 8 (2.8) 1 (1.9) 2 (5.4) 2 (1.5) 0 (-) 0 (-) 2 (2.2) 0 (-) 0.371‡

146 (6.1) 93 (14.4) 7 (4.7)* 11 (8.7) 9 (3.2)* 0 (-)* 4 (0.9)* 20 (7.2)* 2 (1.0)* <0..001 * Significantly dif fer ent fr om North America/W estern Eur ope, P<0.005. § Significantly dif fer

ent, P<0.01 between patients with and without traditional risk factors. †

P-value is fr

om the test of null hypothesis that ther

e is no dif

fer

ence among r

egions, using ANOV

A test for mean age, Kruskal W

allis test for median age and Chi-squar

e

test or Monte Carlo estimates of Fisher’

s exact test for categorical variables. ‡ Exact P-value was estimated by Monte Carlo simulation with 100,000 samples.

AF denotes atrial fibrillation; ED, emer

gency department; IQR, inter

quartile range; L

VH, left ventricular hypertr

ophy; SD, standar

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36

They experienced more AF recurrences (28% versus 21%, P<0.001), but AF persistence was less pronounced after 1-year (21% versus 49%, P<0.001) (Supplementary Table 3.1).

outcomes

Complete one-year follow-up was available for 793 (99.6%) patients without traditional risk factors and 2374 (99.4%) patients with traditional risk factors (Table 2). Patients without traditional risk factors suffered less strokes (5 [0.6%] versus 48 [2%]; RR 0.31 [95% CI, 0.12-0.78, P=0.013]) and had a lower all-cause mortality within 1 year of initial emergency department visit (13 patients [1.6%] versus 165 [7%]; RR 0.24 [95% CI, 0.14-0.41, P<0.001]). Reasons for death in patients without traditional risk factors included: cancer (N=5), unknown (N=4), heart failure (N=3), and sudden cardiac death (N=1). Patients with traditional risk factors were more frequently hospitalized for heart failure (13% versus 0.9%, P<0.001). Hospitalizations for AF occurred often in both groups (18% in patients without versus 21% in patients with traditional risk factors, P=0.09). The high-est rate of repeat hospital visits for AF was in North America and Whigh-estern Europe (27%) (Supplementary Table 4). Adjustments for sex, chronic kidney disease, diabetes mellitus and anticoagulation use did not affect the observation of increased death, stroke, and heart failure hospitalization risk in patients with traditional risk factors (Table 2).

Table 2. outcomes of patients without traditional risk factors compared to age and region-matched patients with traditional risk factors

overall Without traditional risk factors With traditional

risk factors Unadjusted Adjusted*

No. complete follow-up visit

3167 793 2374 RR (95% CI) P-value RR (95% CI) P-value

MACCE 235 (7.4) 18 (2.3) 217 (9.1) 0.25 (0.15-0.40) <0.001 0.26 (0.16-0.43) <0.001 ▪ Death 178 (5.6) 13 (1.6) 165 (7.0) 0.24 (0.14-0.41) <0.001 0.25 (0.14-0.44) <0.001 ▪ Stroke 53 (1.7) 5 (0.6) 48 (2.0) 0.31 (0.12-0.78) 0.013 0.35 (0.14-0.89) 0.027 ▪ Systemic embolism 12 (0.4) 0 (0.0) 12 (0.5) 0.00 (-) 1.000 0.00 (-) 1.000 ▪ Major bleeding 33 (1.0) 3 (0.4) 30 (1.3) 0.30 (0.09-0.98) 0.046 0.41 (0.12-1.39) 0.154 Hospitalization 814 (25.7) 146 (18.4) 668 (28.1) 0.66 (0.56-0.77) <0.001 0.72 (0.61-0.85) <0.001 ▪ Hospitalization

for heart failure

303 (9.6) 7 (0.9) 296 (12.5) 0.07 (0.03-0.15) <0.001 0.08 (0.04-0.17) <0.001 ▪ Hospitalization for MI 23 (0.7) 2 (0.3) 21 (0.9) 0.29 (0.07-1.22) 0.090 0.36 (0.08-1.62) 0.184 ▪ Hospitalization for AF 630 (19.9) 141(17.8) 489 (20.6) 0.87 (0.73-1.02) 0.093 0.94 (0.79-1.13) 0.529

All values are depicted as number (%) unless stated otherwise. Matching conducted 1:3 on age and region.

*Adjusted for sex, chronic kidney disease, diabetes mellitus, and anticoagulation use.

AF denotes atrial fibrillation; IQR, intra-quartile range; MACCE, major adverse cardiac and cerebrovascu-lar event; MI, myocardial infarction; SD, standard deviation.

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DIsCUssIon

This observational study shows that almost all patients presenting to the emergency department without traditionally-defined AF risk factors have less-established or borderline risk factors upon closer examination. These patients without traditional risk factors have predominantly paroxysmal episodes, less AF persistence, and a low 1-year risk of death, stroke and heart failure hospitalizations (Figure 3). Nevertheless, their risk of AF-related re-hospitalization is high; with nearly one fifth returning to the emergency department within one year. Recognition and management of these non-traditional risk could help improve patient outcomes.13

Figure 3. Take home figure

In the RE-LY AF registry, patients without traditional risk factors seemed to have less severe AF, with more paroxysmal AF (55% versus 37%, P<0.001) and less AF persistence (21% versus 49%, P<0.001) compared to matched controls with traditional risk factors. Additionally, their risk of heart failure hospitalizations (0.9% versus 12.5%) and major adverse cardiac or cerebrovascular events (MACCE) during 1-year follow up (2.3% versus 9.1%) was low. However, risk of AF-related re-hospitalization was high, almost 18%, similar to patients with traditional risk factors.

The term ‘’lone AF’’ was first used in 1954 to describe patients in whom ‘’subsequent investigation shows that heart disease is absent’’.1_{In the last few decades our} under-standing of AF pathophysiology and the multitude of systemic aetiologies and risk factors for AF has increased exponentially. We now know that AF without any risk factor is rare.2_{Weijs et al. have shown that in clinical practice almost half of the patients} origi-nally diagnosed with idiopathic AF developed cardiovascular diseases within 5 years.14

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38

Other long-term follow-up studies corroborate these findings and show that almost all patients develop evident cardiovascular risk factors over time.14,15_{In the Olmsted} study all patients who had a cerebrovascular event during long-term follow-up had developed at least one overt risk factor for thromboembolism.3,9_{The high presence} of less-established or borderline risk factors in the RELY-AF registry (98% had one or more less- established or borderline risk factors) underscores the rarity of ‘’lone AF’.2 In the current population, different profiles of less-established or borderline risk factors existed across the world, with obesity being common in North America and Western Europe; borderline hypertension in the Middle East and Eastern Europe; and chronic kidney disease in South America and India.

AF in the absence of traditional risk factors is often considered a benign disease.2_We confirm that our large, global AF population without traditional risk factors has a low short-term risk of morbidity and mortality.7,8,14_{This can be explained not only by the} lack of cardiovascular conditions in these patients, but also by their young age and low rate of AF persistence,16,17_{as both morbidity and mortality are increased in patients} with AF progression.18_{Incident heart failure is common among patients with AF, and} many traditional AF risk factors are also independent clinical predictors of heart failure. Additionally, prolongation of AF episodes >24 hours is associated with a higher rate of heart failure hospitalizations, and AF type and increased burden have been found to be associated with a higher risk of ischemic stroke.19

Although patients with AF without traditional risk factors had a lower risk of death and cardiovascular events, they had a substantial risk of repeat hospitalizations for AF. This highlights the importance of initial AF management during the emergency depart-ment visit, and the importance of appropriate follow-up for further optimization of AF management to prevent recurrent symptoms due to AF. Additionally, prevention of AF progression and management of new risk factors that may develop during follow-up of patients with AF could help to minimize the risk of adverse outcomes, including heart failure hospitalizations (Figure 3).16,17

Clinical implications

In all patients presenting with AF without an obvious cardiac cause, a thorough initial search for less-established or borderline risk factors, which vary between geographic regions, is recommended.4,5,20_{In some cases, no risk factors will be present as AF can} oc-cur as a primary electrical disease, however in many cases borderline or non-traditional risk factors may be found. These patients seem to have less severe AF and a lower risk of adverse events. However, also these non-traditional risk factors require treatment or

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careful follow-up since they may contribute to progression of AF and the occurrence of cardiovascular morbidity and mortality.13

Early identification of less-established or borderline risk factors with timely, holistic treatment; targeted, tailored, and adjusted over time according to the individual needs of these patients, may facilitate the maintenance of sinus rhythm and improve cardio-vascular outcomes.13_{Given the complexity of AF management and the heterogeneity} of patients’ risk factor profiles, integrated AF care by a multidisciplinary team in special-ized AF clinics is recommended.4,5,20

strengths and limitations

Selection of sites within regions was not random and might have introduced recruit-ment bias in comparing the regions, making this a convenience sample. Furthermore, our population without traditional risk factors is determined not only by definition, but also by the organization of the healthcare systems, given differences in the extent of the search for underlying factors, and the robustness of diagnostic tools used in the different world regions. It is conceivable that risk factors or other secondary precipitants have been missed. Detailed echocardiographic and ECG data were not collected in this study. Follow up was only one year, which limits the comparison of outcomes with low incidence; including stroke and death. Strengths include the relatively large, matched group of patients and the broad global representation of countries, many of which have never been included in previous registries or clinical trials of patients without traditional risk factors of AF.

ConClUsIon

Almost all patients without traditionally-defined AF risk factors have less-established or borderline risk factors. These patients have a lower burden of AF and a more favourable 1-year prognosis, but their risk of AF-related re-hospitalization remains high. Greater emphasis should be placed on the recognition and management of these AF risk fac-tors, as this could improve patient outcomes.

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ReFeRenCes

1. Evans W, Swann P. Lone auriculair fibrilla-tion. British heart journal. 1954; 16: 189-194. 2. Wyse DG, Van Gelder IC, Ellinor PT, et al.

Lone atrial fibrillation: does it exist? J Am

Coll Cardiol. 2014; 63: 1715-1723.

3. Jahangir A, Lee V, Friedman PA, et al. Long-term progression and outcomes with aging in patients with lone atrial fibrillation: a 30-year follow-up study. Circulation. 2007; 115: 3050-3056.

4. Lau DH, Nattel S, Kalman JM, Sanders P. Modifiable Risk Factors and Atrial Fibrilla-tion. CirculaFibrilla-tion. 2017; 136: 583-596. 5. 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: 2893-2962. 6. Brand FN, Abbott RD, Kannel WB, Wolf PA.

Characteristics and prognosis of lone atrial fibrillation. 30-year follow-up in the Fram-ingham Study. JAMA. 1985; 254: 3449-3453. 7. Weijs B, Pisters R, Nieuwlaat R, et al.

Idiopathic atrial fibrillation revisited in a large longitudinal clinical cohort. Europace. 2012; 14: 184-190.

8. Jouven X, Desnos M, Guerot C, Ducim-etiere P. Idiopathic atrial fibrillation as a risk factor for mortality. The Paris Prospective Study I. Eur Heart J. 1999; 20: 896-899. 9. Kopecky SL, Gersh BJ, McGoon MD, et al.

The natural history of lone atrial fibrilla-tion. A population-based study over three decades. N Engl J Med. 1987; 317: 669-674. 10. Oldgren J, Healey JS, Ezekowitz M, et al.

Variations in cause and management of atrial fibrillation in a prospective registry of 15,400 emergency department patients in 46 countries: the RE-LY Atrial Fibrillation Registry. Circulation. 2014; 129: 1568-1576. 11. Healey JS, Oldgren J, Ezekowitz M, et al.

Occurrence of death and stroke in patients in 47 countries 1 year after presenting with atrial fibrillation: a cohort study. Lancet. 2016; 388: 1161-1169.

12. Rahman F, Kwan GF, Benjamin EJ. Global epidemiology of atrial fibrillation. Nat Rev

Cardiol. 2016; 13: 501.

13. Rienstra M, Hobbelt AH, Alings M, et al. Targeted therapy of underlying conditions improves sinus rhythm maintenance in patients with persistent atrial fibrillation: results of the RACE 3 trial. Eur Heart J. 2018; .

14. Weijs B, de Vos CB, Tieleman RG, et al. The occurrence of cardiovascular disease during 5-year follow-up in patients with idiopathic atrial fibrillation. Europace. 2013; 15: 18-23.

15. Katritsis DG, Toumpoulis IK, Giazitzoglou E, et al. Latent arterial hypertension in ap-parently lone atrial fibrillation. J Interv Card

Electrophysiol. 2005; 13: 203-207.

16. Rienstra M, Van Gelder IC, Hagens VE, Veeger NJ, Van Veldhuisen DJ, Crijns HJ. Mending the rhythm does not improve prognosis in patients with persistent atrial fibrillation: a subanalysis of the RACE study.

Eur Heart J. 2006; 27: 357-364.

17. Chamberlain AM, Alonso A, Gersh BJ, et al. Multimorbidity and the risk of hospi-talization and death in atrial fibrillation: A population-based study. Am Heart J. 2017; 185: 74-84.

18. De With RR, Marcos EG, Van Gelder IC, Rienstra M. Atrial fibrillation progression and outcome in patients with young-onset atrial fibrillation. Europace. 2018; 20: 1750-1757.

19. Ganesan AN, Chew DP, Hartshorne T, et al. The impact of atrial fibrillation type on the risk of thromboembolism, mortality, and bleeding: a systematic review and meta-analysis. Eur Heart J. 2016; 37: 1591-1602. 20. Mahajan R, Pathak RK, Thiyagarajah A, et al.

Risk Factor Management and Atrial Fibrilla-tion Clinics: Saving the Best for Last? Heart

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sUPPleMenTARY MATeRIAl

supplementary Table 1. secondary precipitants for AF

secondary precipitants number

Acute coronary syndrome / arrest 13

Pericarditis / pericardial effusion* 6

Acute pulmonary oedema 2

Cerebrovascular accident 4 Aortic rupture 1 Heart failure 14 Hypertension 1 ICD shock 1 Myocarditis 1

Rheumatic heart disease 3

*HIV and tuberculosis associated pericarditis occurred in Africa.