MANAGEMENT OF PATIENTS WITH ATRIAL FIBRILLATION Linda Petronella Theodora Joosten
MANAGEMENT OF PATIENTS WITH ATRIAL FIBRILLATION Linda Petronella Theodora Joosten
Management of patients with atrial fibrillation PhD thesis, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, the Netherlands ISBN: 978-94-6506-221-1 DOI: https://doi.org/10.33540/2489 Cover design and layout: Jolanda Hiddink, persoonlijkproefschrift.nl Printing: Ridderprint, ridderprint.nl Copyright © 2024 Linda Petronella Theodora Joosten All rights reserved. No part of this thesis may be reproduced, stored or transmitted in any way or by any means without the prior permission of the author, or when applicable, of the publishers of the scientific papers.
MANAGEMENT OF PATIENTS WITH ATRIAL FIBRILLATION MANAGEMENT VAN PATIËNTEN MET ATRIUMFIBRILLEREN (met een samenvatting in het Nederlands) Proefschrift ter verkrijging van de graad van doctor aan de Universiteit Utrecht op gezag van de rector magnificus, prof. dr. H.R.B.M. Kummeling, ingevolge het besluit van het College voor Promoties in het openbaar te verdedigen op dinsdag 15 oktober 2024 des middags te 2.15 uur door Linda Petronella Theodora Joosten geboren op 1 november 1991 te Weert
Promotoren: Prof. dr. F.H. Rutten Prof. dr. A.W. Hoes Copromotoren: Dr. G.J. Geersing Dr. S. van Doorn Beoordelingscommissie: Prof. dr. H.J.G.M. Crijns Prof. dr. M.H. Emmelot-Vonk (voorzitter) Prof. dr. M. Meine Prof. dr. R.E.G. Schutgens Prof. dr. D.L.M. Zwart Dit proefschrift werd (mede) mogelijk gemaakt met financiële steun van de Federatie van Nederlandse Trombosediensten (FNT), de Nederlandse Hartstichting en de Stichting Beroepsopleiding Huisartsen (SBOH).
Voor mijn ouders
CONTENTS Chapter 1 General introduction: management of patients with atrial fibrillation 9 Chapter 2 Atrial fibrillation: a systemic cardiovascular disease in need for integrated cardiovascular risk management 19 Chapter 3 Sex- and age specific association of new-onset atrial fibrillation with in-hospital mortality in hospitalised COVID-19 patients 29 Chapter 4 Stroke rate variation and anticoagulation benefit in atrial fibrillation 57 Chapter 5 Atrial fibrillation: trends in prevalence and antithrombotic prescriptions in the community 63 Chapter 6 Safety of switching from a vitamin K antagonist to a non- vitamin K antagonist oral anticoagulant in frail older patients with atrial fibrillation: rationale and design of the FRAIL-AF randomised controlled trial 85 Chapter 7 Safety of switching from a vitamin K antagonist to a nonvitamin K antagonist oral anticoagulant in frail older patients with atrial fibrillation: results of the FRAIL-AF randomised controlled trial 105 Chapter 8 Clinical consequences of off-label reduced dosing of nonvitamin K antagonist oral anticoagulants in patients with atrial fibrillation: a systematic review and meta-analysis 133 Chapter 9 General discussion: from management of patients with atrial fibrillation to the ‘inverse research law’ 177 Appendices Summary 193 Samenvatting 203 Dankwoord 213 About the author 221 Publications and conference presentations 225
GENERAL INTRODUCTION: MANAGEMENT OF PATIENTS WITH ATRIAL FIBRILLATION Linda P.T. Joosten 1
10 CHAPTER 1 THE CASE OF MRS. DE JONG Mrs. de Jong is 80-years old and has been living alone since her husband died two years ago in 2018. She is frequently visited by her general practitioner (GP), most often for complaints of pain caused by coxarthrosis and shortness of breath due to heart failure; both reasons why she no longer manages to go out for grocery shopping on her own. In addition, she is known with hypertension, mitral valve insufficiency, vascular disease, diabetes mellitus, presbycusis, and mild cognitive impairment. Her medication list includes six different types of drugs. May 2020 – Her GP receives a phone call from her worried son. Mrs. de Jong has been admitted with coronavirus disease 2019 (COVID-19) and has also developed atrial fibrillation (AF) during admission. The GP had previously read an interesting paper in the journal ‘Huisarts & Wetenschap’, stating that during a respiratory tract infection patients are more prone to developing cardiovascular diseases, including AF, and that they are in an increased prothrombotic state. The GP wonders whether the pathophysiology of an increased ischaemic stroke risk in AF is actually fully understood and whether everything the GP learned about it at medical school is still valid. The son of Mrs. de Jong brings the GP back to reality; he fears that his mother will not survive the admission given these two diseases new to her and her advanced age. He asks whether her GP can tell him anything about her risk of dying. Unfortunately, the GP has to explain that it is not possible to predict mortality risk, because there is still very little known about the impact of COVID19. July 2020 – Mrs. de Jong survived the hospital admission and is back home where daily home care has been initiated by her GP. Her AF appeared to be permanent. This means, considering her CHA2DS2-VASc score of 5, that her ischaemic stroke risk would be 8.4% per year on average if left untreated.1 A vitamin K antagonist oral anticoagulant (VKA) was started during hospitalisation. According to the available evidence, a VKA will reduce her ischaemic stroke risk by 67% (from 8.4% to 2.8% per year; i.e. an absolute risk reduction of 5.6% per year) .2 Thus, although accompanied by an increase in major bleeding (from around 0.9% to 1.5% per year),2 there is no doubt that Mrs. de Jong should receive oral anticoagulation. Importantly, her GP wonders how certain the optimal threshold of the CHA2DS2-VASc score above which oral anticoagulation should be initiated (i.e. 3 for women and 2 for men) actually is. Moreover, the GP wonders why the cardiologist chose a VKA instead of a non-VKA oral anticoagulant (NOAC) given that cardiologists are increasingly prescribing NOACs instead of VKAs when initiating oral anticoagulation in AF patients. April 2023 – For several months, Mrs. de Jong complains that she suffers more frequently from nosebleeds and that she dislikes the bruises on her skin, especially on her arms. Her GP wonders whether it might be better for her to switch from her VKA to a NOAC as randomised controlled trials showed that NOACs compared to VKAs are at least as
11 GENERAL INTRODUCTION effective in preventing ischaemic stroke but cause less (major) bleeding in patients with AF. However, the GP realises that frail old patients such as Mrs. de Jong were highly underrepresented in these pivotal trials. While thinking about how to minimise both the risk of stroke and the risk of bleeding as much as possible, the GP also considers switching to a NOAC with an off-label reduced NOAC dose. Eventually, the GP decides not to switch at all, because of the lack of evidence for either option. ATRIAL FIBRILLATION Atrial fibrillation (AF) is one of the most common cardiac conditions with a lifetime risk of one in three individuals of Western ancestry.3 AF is particularly common in the ageing population with a prevalence of 0.7% in people aged 55 to 59 years, rising to 17.8% in those aged 85 years and older,4 and rising even further to 38% in the most frail population in society (i.e. nursing home residents).5 Importantly, the overall prevalence of AF is increasing due to the ageing of the population and is expected to double within half a century.6 This has a major impact on public health as AF is associated with severe morbidity and mortality. The most feared complication of AF is the occurrence of an ischaemic stroke which, without anticoagulation, occurs nearly five times more often in patients with AF compared to patients without AF.7 However, it is important to note that this evidence dates back to 1991, which makes it very well possible that this risk is different in today’s AF population that generally suffers from more comorbidities but benefits from improved healthcare. To estimate stroke risk in untreated AF patients, prediction models have been developed, of which the CHA2DS2-VASc model is the most widely used.8 However, with a concordance-statistic for ischaemic stroke of 0.67 (95% confidence interval (95% CI) 0.66-0.68), the ability to predict stroke, in particular for intermediate and high risk patients, is not very accurate.1 Nevertheless, the European Society of Cardiology recommends oral anticoagulation therapy, with the aim to prevent stroke, when the CHA2DS2-VASc score is ≥2 points in men or ≥3 points in women.9,10 ANTICOAGULANTS Without anticoagulation, stroke risk can be as high as 14.4% per year in AF patients with multimorbidity, as summarised by the CHA2DS2-VASc risk model. 1 In 1989, the AFASAK study was the first randomised controlled trial (RCT) showing effectiveness of oral anticoagulation for stroke prevention in AF.11 During the years that followed, it became apparent that treatment with oral anticoagulants reduced the risk of an ischaemic stroke by 67% (95% CI 54%-77%).2 Until 2008, the only type of oral 1
12 CHAPTER 1 anticoagulation effective in stroke prevention in patients with AF was a vitamin K antagonist (VKA), such as warfarin, acenocoumarol and phenprocoumon. From 2008 onwards, another oral anticoagulant became available, namely a non-VKA antagonist oral anticoagulant (NOAC), also known as a direct oral anticoagulant (DOAC). There are currently four different NOACs on the market: apixaban, dabigatran, edoxaban, and rivaroxaban. The four pivotal NOAC trials showed that, compared with VKAs, NOACs are at least as effective in preventing ischaemic stroke, but overall have a better safety profile, i.e. a lower risk of severe bleeding, notably intracranial bleeding (relative risk reduction ranging from 29% in patients receiving rivaroxaban to 74% in patients receiving a non-reduced dose of dabigatran).12–15. Therefore, since 2016, guidelines recommend a NOAC in newly diagnosed AF patients instead of VKA treatment, especially when there are no contraindications for a NOAC. Also according to these guidelines, in AF patients already treated with a VKA, switching to NOAC treatment may be considered if time in therapeutic range is not well controlled despite good adherence, or if patients prefer a NOAC and have no contra-indications a NOAC.9 Which NOAC is best is not known, because NOACs have never been compared headto-head to each other in an RCT. FRAILTY AND THE CONSISTENT LACK OF EVIDENCE Frailty involves a lot more than just ageing, multiple comorbidities and polypharmacy. It is a clinical syndrome defined by a high biological vulnerability and a reduced capacity to resist stressors, all leading to reduced homeostatic reserve and to dependency on others.16 In the Netherlands, it is estimated that there are currently 730,000 frail older people (i.e. more than 1 in 25 individuals).17,18 The population of frail elderly grows rapidly as, largely due to improved healthcare, there is a shift in the burden of morbidity from acute to chronic diseases (including AF) and life expectancy increases.17–19 As described above, AF is common, especially in frail older people in whom the prevalence is around 40%.5 The incidence of stroke in frail older patients with AF peaks at 12.3% per year compared to 3.9% per year in non-frail older patients with AF.5 A considerable amount of research has been conducted on AF and its treatment with oral anticoagulation, but important questions remain, especially for the frail elderly population. For example, it is uncertain whether NOACs should be preferred over VKAs in frail older AF patients and it is even more questionable whether frail elderly patients with AF who are stable on VKA treatment should be switched to a NOAC. Observational studies do not provide a proper answer to these questions because they suffer from confounding. And, surprisingly, almost no RCTs have been conducted in frail older people (neither in the field of AF nor in most other clinical fields), which is unjustified given that in this large and increasing population there is the greatest need for evidence and personalised management. Currently, results from
13 GENERAL INTRODUCTION RCTs performed in a selective population including few or no frail elderly are incorrectly generalised to frail older people. The assumption that the results from RCTs in general cannot simply be generalised to the population of frail older people is entirely valid. Frail older people have a large volatility, for example in anticoagulation status. This large volatility is due to problems with treatment adherence which is often associated with polypharmacy and some degree of cognitive impairment. Furthermore, these fluctuations are due to different pharmacokinetics and pharmacodynamics, which respectively means that the human body of frail elderly, who often suffer from multimorbidity, processes medication differently compared to non-frail elderly (i.e. they have a different absorption, distribution, metabolism and excretion of medication), and that medication itself has different effects in frail elderly compared to non-frail elderly. Therefore, the balance, in this example between coagulation and bleeding, is more fragile in frail older people. Regarding AF management, this fragile balance may influence the effects of oral anticoagulation. Perhaps VKA treatment with monitoring through international normalised ratio testing instead of NOAC treatment is safer for frail older patients because it allows early intervention by titrating the VKA dose to the most optimal range. Given the differences between frail and non-frail elderly and current speculations rather than evidence, RCTs in frail elderly patients are urgently needed, especially towards comparing VKA treatment with NOAC treatment in frail older patients with AF. THESIS OUTLINE In the management of patients it may be useful to understand the underlying pathophysiological mechanisms of the disease involved or to have an explainable model of the particular disease. Therefore, in Chapter 2 the role of a hypercoagulable or prothrombotic state as pathophysiological mechanism for increased ischaemic stroke risk in patients with AF was explored. A hypercoagulable or prothrombotic state may also at least partly explain why patients with an respiratory tract infection, such as coronavirus disease 2019 (COVID-19), are more prone to developing AF and other (cardiovascular) morbidities. In Chapter 3, the sex- and age specific association of new-onset AF with in-hospital mortality was assessed in hospitalised COVID-19 patients mainly during the first COVID-19 wave. Chapters four to eight consist of studies on oral anticoagulant treatment of AF. Chapter 4 is a response letter to a published article about stroke rate variation and anticoagulation benefit in patients with AF. Notably, the balance between the risk of ischaemic stroke and bleeding in those with a low CHA2DS2-VASc score was discussed. Chapter 5 provides an overview of the trends in prevalence of AF and antithrombotic 1
14 CHAPTER 1 prescriptions in the community from 2008 to 2017. In Chapter 6 and 7, in-depth exploration was conducted through an RCT: the FRAIL-AF trial which aimed to evaluate the safety of switching from a VKA to a NOAC compared to continuing with a VKA in frail older patients with AF. In Chapter 6, the rationale and design of the FRAIL-AF trial were described and in Chapter 7 the results of this RCT were presented. Important in treatment with oral anticoagulation is determining the correct dose. Postmarketing observational studies show that some patients are treated with a reduced NOAC dose without a clear indication for dose reduction. In Chapter 8 a systematic review and meta-analysis on the clinical consequences of this so-called off-label reduced dosing of NOACs was described in patients with AF. In Chapter 9, the main findings of this thesis and their practical implications were described in relation to the case of Mrs. de Jong, unanswered questions in relation to the FRAIL-AF trial were provided and, most important, one of the main messages of this thesis was extensively discussed.
15 GENERAL INTRODUCTION REFERENCES 1. Friberg L, Rosenqvist M, Lip GYH. Evaluation of risk stratification schemes for ischaemic stroke and bleeding in 182 678 patients with atrial fibrillation: The Swedish atrial fibrillation cohort study. European Heart Journal. 2012;33:1431–3. 2. Hart RG, Pearce LA, Aguilar MI. Meta-analysis: Antithrombotic therapy to prevent stroke in patients who have nonvalvular atrial fibrillation. Ann Intern Med. 2007;146(12):857–67. 3. Staerk L, Wang B, Preis SR, Larson MG, Lubitz SA, Ellinor PT, et al. Lifetime risk of atrial fibrillation according to optimal, borderline, or elevated levels of risk factors: Cohort study based on longitudinal data from the Framingham Heart Study. BMJ. 2018;361. 4. Heeringa J, van der Kuip DA, Hofman A, Kors JA, van Herpen G, Stricker BHC, et al. Prevalence, incidence and lifetime risk of atrial fibrillation: The Rotterdam study. Eur Heart J. 2006;27(8):949–53. 5. Wilkinson C, Todd O, Clegg A, Gale CP, Hall M. Management of atrial fibrillation for older people with frailty: A systematic review and meta-analysis. Age and Ageing. 2019;48:196– 204. 6. Krijthe BP, Kunst A, Benjamin EJ, Lip GYH, Franco OH, Hofman A, et al. Projections on the number of individuals with atrial fibrillation in the European Union, from 2000 to 2060. Eur Heart J. 2013;34(35):2746–51. 7. Wolf PA, Abbott RD, Kannel WB. Atrial fibrillation as an independent risk factor for stroke: The Framingham Study. Stroke. 1991;22(8):983–8. 8. Lip GYH, Nieuwlaat R, Pisters R, Lane DA, Crijns HJGM, Andresen D, 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(2):263–72. 9. Kirchhof P, Benussi S, Kotecha D, Ahlsson A, Atar D, Casadei B, et al. 2016 ESC Guidelines for the management of atrial fibrillation developed in collaboration with EACTS. Eur Heart J. 2016;37(38):2893–962. 10. Hindricks G, Potpara T, Dagres N, Arbelo E, Bax JJ, Blomström-Lundqvist C, et al. 2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS). Eur Heart J. 2021;42(5):373–498. 11. Petersen P, Godtfredsen J, Boysen G, Andersen Bjø ED, Andersen RN. Placebocontrolled, randomised trial of warfarin and aspirin for prevention of thromboembolic complications in chronic atrial fibrillation: The Copenhagen AFASAK study. Lancet. 1989;28(1):178–9. 12. Connolly SJ, Ezekowitz MD, Yusuf S, Eikelboom J, Oldgren J, Parekh A, et al. Dabigatran versus warfarin in patients with atrial fibrillation. N Eng J Med. 2009;361(12):1139–51. 13. Patel MR, Mahaffey KW, Garg J, Pan G, Singer DE, Hacke W, et al. Rivaroxaban versus warfarin in nonvalvular atrial fibrillation. N Eng J Med. 2011;365(10):883–91. 14. Granger CB, Alexander JH, McMurray JJ, Lopes RD, Hylek EM, Hanna M, et al. Apixaban versus Warfarin in Patients with Atrial Fibrillation. N Eng J Med. 2011;365(11):981–92. 15. Giugliano RP, Ruff CT, Braunwald E, Murphy SA, Wiviott SD, Halperin JL, et al. Edoxaban versus warfarin in patients with atrial fibrillation. N Eng J Med. 2013;369(22):2093–104. 16. Savelieva I, Fumagalli S, Kenny RA, Anker S, Benetos A, Boriani G, et al. EHRA expert consensus document on the management of arrhythmias in frailty syndrome, endorsed by the Heart Rhythm Society (HRS), Asia Pacific Heart Rhythm Society (APHRS), Latin America Heart Rhythm Society (LAHRS), and Cardiac Arrhythmia Society of Southern Africa (CASSA). Europace. 2023;25(4):1249–76. 1
16 CHAPTER 1 17. Centraal Bureau voor de Statistiek. Bevolkingspiramide. [Internet]. 2024 [cited 2024 Jan 30]. Available from: https://www.cbs.nl/nl-nl/visualisaties/dashboard-bevolking/ bevolkingspiramide 18. Buddeke J, Valstar GB, Van Dis I, Visseren FLJ, Rutten FH, Den Ruijter HM, et al. Mortality after hospital admission for heart failure: Improvement over time, equally strong in women as in men. BMC Public Health. 2020;20(1):1–10. 19. Koopman C, Bots ML, van Dis I, Vaartjes I. Shifts in the age distribution and from acute to chronic coronary heart disease hospitalizations. Eur J Prev Cardiol. 2016;23(2):170–7.
17 GENERAL INTRODUCTION 1
ATRIAL FIBRILLATION: A SYSTEMIC CARDIOVASCULAR DISEASE IN NEED FOR INTEGRATED CARDIOVASCULAR RISK MANAGEMENT 2 Linda P.T. Joosten Sander van Doorn Arno W. Hoes Frans H. Rutten Geert-Jan Geersing Submitted
20 CHAPTER 2 INTRODUCTION Atrial fibrillation (AF) is one of the most common cardiac conditions with a prevalence of around 1-2% in the general population, and with higher rates among those with advancing age. The prevalence of AF is expected to double in the next few decades, mainly due to the ageing of the population.1 The latest ESC guidelines on AF recommend integrated care across all healthcare levels and among different specialties for all AF patients according to the ‘Atrial Fibrillation Better Care (ABC) holistic pathway’. In this acronym, the A represents ‘anticoagulation/ avoid stroke’, the B ‘better symptom management’, and the C ‘cardiovascular and comorbidity optimisation’.2 Currently, with the publications of the landmark EASTAFNET randomised controlled trials reporting positive effects of (systematic) early ablation on improving patient outcomes, scientific focus is on ‘better symptom management’.3,4 Avoiding stroke and optimising the cardiovascular risk-factor burden and comorbidities are, however, at least equally important. By reaching back to the pathophysiology of increased stroke risk in patients with AF, we want to further explain the rationale behind the ABC strategy and provide suggestions on how to achieve optimal AF care. THE CLASSIC PARADIGM IN PATHOPHYSIOLOGY In the famous Framingham Heart cohort in which patients are followed for many years to study risk factors for cardiovascular disease, stroke risk in AF patients was found to be up to five times higher compared to patients without AF.5 It is important to note, however, that this evidence originates from 1991. Therefore, it is very well possible that this risk is slightly different in today’s AF population, which experiences more comorbidities but also benefits from advancements in healthcare. More importantly, why is it that stroke risk is so much higher in AF patients? Post mortem studies reported on cerebral emboli in a significant amount of AF patients,6,7 which led to the theoretical concept that in fibrillating atria cardiac thrombi may develop because of blood stasis, most commonly in the left atrial appendage. When these thrombi migrate, they can cause ischaemic stroke further upstream. However, it is not likely that this is the only causal mechanism for ischaemic stroke in patients with AF for a variety of reasons. First, there is often a temporal dissociation between ischaemic stroke and AF, in which ischaemic stroke precedes a period of AF or in which ischaemic stroke occurs after having had AF for a long period of time.8,9 Second, many studies have shown that there is a persistently increased stroke risk in AF patients, even after sinus rhythm is restored, thus after the period of fibrillating atria and blood stasis in the left atrial appendage.10 Third, there is clear bidirectionality between AF and venous thromboembolism, where AF is associated with an increased risk not only of pulmonary embolism but also of
21 PATHOPHYSIOLOGY OF INCREASED ISCHAEMIC STROKE RISK IN AF deep vein thrombosis, and vice versa, underpinning that ischaemic stroke risk in AF is also (at least partly) related to a hypercoagulable or prothrombotic state.11 ATRIAL FIBRILLATION: A SYSTEMIC CARDIOVASCULAR DISEASE As is commonly known, haemostatic response starts with platelet adhesion, wherein damaged endothelial cells and collagen attract platelets to the site of injury according to Virchow’s triad. Following adhesion, platelets undergo activation, transitioning to an active state and responding to various stimuli such as thrombin. This platelet activation leads to further adhesion and the formation of a platelet plug at the injured site. Ultimately platelet aggregation occurs, wherein activated platelets adhere to each other, forming a blood clot. The view that AF is a complex systemic cardiovascular disease that, together with comorbidities, maintains a systemic hypercoagulable or prothrombotic state, thereby contributing to AF related complications such as ischaemic stroke, can be clarified using Virchow’s triad for thrombogenesis. Below, we explain that, apart from abnormal decreased blood flow (i.e. stasis of the blood), also abnormal changes in the walls of blood vessels and atria and abnormal changes in blood constituents complete this triad for thrombogenesis in patients with AF.12,13 First of all, studies have shown abnormal changes in the walls of blood vessels and atria in patients with AF compared to patients without AF, a finding currently described as atrial cardiomyopathy. For example, a post mortem study in patients with ischaemic stroke described a ‘rough’ endocardium with a wrinkled appearance (due to oedema and fibrinous transformation), areas of denudation of the endothelium and aggregation of thrombi in those with AF compared to those without AF.14 In addition, Weijs et al. showed that, over a period of five years, patients diagnosed with AF compared to those without AF, develop cardiovascular disease (such as ischaemic stroke, myocardial infarction and heart failure) more often (49% versus 20%, P=0.006), at a younger age (59 versus 64 years, P=0.027), and with a more severe disease profile.15 Moreover, the presence of a complex plaque (i.e. a plaque with a thickness greater than 4 millimetre, or containing ulceration, pedunculation, or mobile elements) in the aorta of AF patients is a risk factor for ischaemic stroke.16 These findings mean that AF patients, especially those with atherosclerosis or associated vascular risk factors (e.g. hypertension, hypercholesterolaemia, diabetes mellitus, obesity, long-lasting stress, smoking, family history for vascular disease), are more prone to developing ischaemic stroke. Monitoring the left atrial volume index as a biomarker of vascular remodelling may thus be useful to predict the risk of ischaemic stroke.17 2
22 CHAPTER 2 In addition, it is known that main elements of the coagulation cascade (i.e. platelets and specific proteins) in patients with AF differ from those without AF. For example, specific coagulation proteins (e.g. von Willebrand factor and fibrinogen) and D-dimer are increased in AF.18,19 Therefore, it is assumed that there is an increased activation of the coagulation cascade in patients with AF, leading to an increased risk of ischaemic stroke.12,13 This increased activation is further amplified by pre-existing comorbidities. For example, a study showed that diabetes mellitus was strongly associated with increased platelet activation due to increased p-selectin (i.e. CD62p) expression in patients with AF compared to patients without AF.20 MANAGEMENT OF ATRIAL FIBRILLATION Following the above, AF can be considered as a complex systemic cardiovascular disease that involves multiple pathophysiological mechanisms, and that is associated with increased stroke risk and other adverse outcomes, amplified by pre-existing comorbidities. Therefore, the latest ESC guidelines on the management of AF recommend a holistic approach with integrated management for all AF patients, including patient involvement, multidisciplinary teams consisting of physicians and other healthcare professionals working together across all healthcare levels, technology tools, and access to different treatment options.2 Based on pathophysiology, it is important that within this integrated holistic AF care, stroke risk management in AF is determined by the specific stroke risk factors present in a given patient with AF, exemplified e.g. by the CHA2DS2-VASc risk tool. 21 Studies showed that regular controls and attention paid to these risk factors reduce cardiovascular hospitalisation and allcause mortality in AF patients, both in hospital and in primary care.22,23 For example, Hendriks et al. showed that integrated chronic care versus routine clinical care in AF patients led to a 35% reduction in cardiovascular hospitalisation and cardiovascular mortality. Furthermore, the ALL-IN trial showed that integrated AF care compared with AF care as usual let to a 45% reduction in all-cause mortality.23 Therefore, an integrated strategy seems more effective than solely pharmacological or invasive attempts to control heart rhythm or heart rate, and underlines the importance of considering AF as a systemic cardiovascular disease in need for integrated holistic cardiovascular risk management and care. Since primary care currently plays a pivotal role in cardiovascular risk management, it seems efficient to integrate this holistic AF care into the already existing cardiovascular risk management programmes in the primary care setting.
23 PATHOPHYSIOLOGY OF INCREASED ISCHAEMIC STROKE RISK IN AF DIRECTIONS FOR FUTURE PRACTICE AND RESEARCH As described above, it may be useful in the management of patients with AF to understand the underlying pathophysiological mechanisms or to have an explanatory model of the disease. Research on the pathophysiological mechanisms of AF with experimental in vitro studies, studies in clinical practice and the use of big data analytics can provide better insight in coagulation mechanisms that are related to the occurrence of AF itself and the subsequent association with ischaemic stroke. Such insight could serve as a starting point for future AF management. Figure 1 shows an overview of past achievements and predicted future developments in the management of patients with AF. CONCLUSION In patients with AF the pathophysiology of ischaemic stroke is multifactorial, which makes AF a complex systemic cardiovascular disease in need for integrated holistic cardiovascular risk management and care. A better understanding of the pathophysiology of AF could be valuable in the management of patients with AF. 2
24 CHAPTER 2 FIGURE 1: PAST ACHIEVEMENTS AND PROPOSED FUTURE DEVELOPMENTS IN THE MANAGEMENT OF AF PATIENTS. AF: atrial fibrillation; ECG: electrocardiogram; IPD: individual patient data; NOAC: non-vitamin K antagonist oral anticoagulant; RCT: randomised controlled trial.
25 PATHOPHYSIOLOGY OF INCREASED ISCHAEMIC STROKE RISK IN AF FUNDING This study did not receive funding. GJG is supported by a VENI and VIDI grant from the Netherlands Organisation for Health Research and Development (ZonMw numbers 016.166.030 and 016.196.304). POTENTIAL CONFLICTS OF INTEREST FR and GJG report unrestricted institutional grants for performing research in the field of atrial fibrillation from Boehringer Ingelheim, Bayer Healthcare, Bristol-Myers Squibb/Pfizer Alliance and Daiichi Sankyo. The other authors declare that they have no conflicts of interest. CONTRIBUTORS All authors conceived and initiated the study. LJ and SvD wrote the first version of the manuscript. All authors critically reviewed and revised the manuscript. ACKNOWLEDGEMENT We express our gratitude to Prof. dr. H.J.G.M. Crijns (cardiologist) for his valuable input in earlier drafts of this paper. 2
26 CHAPTER 2 REFERENCES 1. Lane DA, Skjøth F, Lip GYH, Larsen TB, Kotecha D. Temporal trends in incidence, prevalence, and mortality of atrial fibrillation in primary care. J Am Heart Assoc. 2017;6(5). 2. Hindricks G, Potpara T, Dagres N, Arbelo E, Bax JJ, Blomström-Lundqvist C, et al. 2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS). Eur Heart J. 2021;42(5):373–498. 3. Kirchhof P, Camm AJ, Goette A, Brandes A, Eckardt L, Elvan A, et al. Early rhythm control therapy in patients with atrial fibrillation. New England Journal of Medicine. 2020;383(14):1305–16. 4. Willems S, Borof K, Brandes A, Breithardt G, Camm AJ, Crijns HJGM, et al. Systematic, early rhythm control strategy for atrial fibrillation in patients with or without symptoms: The EAST-AFNET 4 trial. Eur Heart J. 2022;43(12):1219–30. 5. Wolf PA, Abbott RD, Kannel WB. Atrial fibrillation as an independent risk factor for stroke: The Framingham Study. Stroke. 1991;22(8):983–8. 6. Hurst JW, Paulk EA, Proctor HD, Schlant RC. Management of patients with atrial fibrillation. American Journal of Medicine. 1964;37:728–41. 7. Wolf PA, Dawber TR, Thomas HE, Kannel WB. Epidemiologic assessment of chronic atrial fibrillation and risk of stroke: The Framingham Study. Neurology. 1978;28:973–7. 8. Brambatti M, Connolly SJ, Gold MR, Morillo CA, Capucci A, Muto C, et al. Temporal relationship between subclinical atrial fibrillation and embolic events. Circulation. 2014;129(21):2094–9. 9. Camen S, Ojeda FM, Niiranen T, Gianfagna F, Vishram-Nielsen JK, Costanzo S, et al. Temporal relations between atrial fibrillation and ischaemic stroke and their prognostic impact on mortality. Europace. 2020;22(4):522–9. 10. Van Gelder IC, Hagens VE, Bosker HA, Kingma JH, Kamp O, Kingma T, et al. A comparison of rate rontrol and rhythm control in patients with recurrent persistent atrial fibrillation. N Engl J Med. 2002;347(23):1834–40. 11. Lutsey PL, Norby FL, Alonso A, Cushman M, Chen LY, Michos ED, et al. Atrial fibrillation and venous thromboembolism: evidence of bidirectionality in the atherosclerosis risk in communities study. Journal of Thrombosis and Haemostasis. 2018;16(4):670–9. 12. Watson T, Shantsila E, Lip GY. Mechanisms of thrombogenesis in atrial fibrillation: Virchow’s triad revisited. The Lancet. 2009;373:155–66. 13. Ding WY, Gupta D, Lip GYH. Atrial fibrillation and the prothrombotic state: Revisiting Virchow’s triad in 2020. Heart. 2020;106(19):1463–8. 14. Masawa N, Yoshida Y, Yamada T, Joshita T, Ooneda G. Diagnosis of cardiac thrombosis in patients with atrial fibrillation in the absence of macroscopically visible thrombi. Virchows Arch A Pathol Anat Histopathol. 1993;422(1):67–71. 15. Weijs B, De Vos CB, Tieleman RG, Peeters FECM, Limantoro I, Kroon AA, et al. The occurrence of cardiovascular disease during 5-year follow-up in patients with idiopathic atrial fibrillation. Europace. 2013;15(1):18–23. 16. The stroke prevention in atrial fibrillation investigators committee on echocardiography. Transesophageal echocardiographic correlates of thromboembolism in high-risk patients with nonvalvular atrial fibrillation. Ann Intern Med. 1998;128:639–47. 17. Osranek M, Bursi F, Bailey KR, Grossardt BR, Brown RD, Kopecky SL, et al. Left atrial volume predicts cardiovascular events in patients originally diagnosed with lone atrial fibrillation: three-decade follow-up. European Heart Journal. 2005;26:2487–9.
27 PATHOPHYSIOLOGY OF INCREASED ISCHAEMIC STROKE RISK IN AF 18. Gustafsson C, Blomback M, Britton M, Hamsten A, Svensson J. Coagulation factors and the increased risk of stroke in nonvalvular atrial fibrillation. Stroke. 1990;21(1):47–51. 19. Marín F, Roldán V, Climent VE, Ibáñez A, García A, Marco P, et al. Plasma von Willebrand factor, soluble thrombomodulin, and fibrin D-dimer concentrations in acute onset nonrheumatic atrial fibrillation. Heart. 2004;90(10):1162–6. 20. Yip HK, Chang LT, Sun CK, Yang CH, Hung WC, Hang CL, et al. Platelet activation in patients with chronic nonvalvular atrial fibrillation. Internal Heart Journal. 2006;47(3):371–9. 21. Lip GYH, Nieuwlaat R, Pisters R, Lane DA, Crijns HJGM, Andresen D, 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(2):263–72. 22. Hendriks JML, De Wit R, Crijns HJGM, Vrijhoef HJM, Prins MH, Pisters R, et al. Nurseled care vs. usual care for patients with atrial fibrillation: Results of a randomized trial of integrated chronic care vs. routine clinical care in ambulatory patients with atrial fibrillation. Eur Heart J. 2012;33(21):2692–9. 23. van den Dries CJ, van Doorn S, Rutten FH, Oudega R, van de Leur SJCM, Elvan A, et al. Integrated management of atrial fibrillation in primary care: Results of the ALL-IN cluster randomized trial. Eur Heart J. 2020;41(30):2836–44. 2
SEX- AND AGE SPECIFIC ASSOCIATION OF NEW-ONSET ATRIAL FIBRILLATION WITH IN-HOSPITAL MORTALITY IN HOSPITALISED COVID-19 PATIENTS 3 Linda P.T. Joosten* Joost A. Offerhaus* Maarten van Smeden Marijke Linschoten Hidde Bleijendaal Robert Tieleman Arthur A.M. Wilde Frans H. Rutten Geert-Jan Geersing^ Carol Ann Remme^ *Shared first authorship ^Shared last authorship International Journal of Cardiology - Heart & Vasculature. 2022;39:100970
30 CHAPTER 3 ABSTRACT Introduction: Coronavirus disease 2019 (COVID-19) is a systemic disease with cardiovascular involvement, including cardiac arrhythmias. Notably, new-onset atrial fibrillation (AF) and atrial flutter (AFL) during hospitalisation in COVID-19 patients has been associated with increased mortality. However, how this risk is impacted by age and sex is still poorly understood. Methods: For this multicentre cohort study, we extracted demographics, medical history, occurrence of electrical disorders and in-hospital mortality from the large international patient registry CAPACITY-COVID. For each electrical disorder, prevalence during hospitalisation was calculated. Subsequently, we analysed the incremental prognostic effect of developing AF/AFL on in-hospital mortality, using multivariable logistic regression analyses, stratified for sex and age. Results: In total, 5,782 patients (64% male; median age 67) were included. Of all patients 11.0% (95% CI 10.2–11.8) experienced AF and 1.6% (95% CI 1.3–1.9) experienced AFL during hospitalisation. Ventricular arrhythmias were rare (<0.8% (95% CI 0.6-1.0)) and a conduction disorder was observed in 6.3% (95% CI 5.7-7.0). An event of AF/AFL appeared to occur more often in patients with pre-existing heart failure. After multivariable adjustment for age and sex, new-onset AF/AFL was significantly associated with a poorer prognosis, exemplified by a two- to three-fold increased risk of in-hospital mortality in males aged 60–72 years, whereas this effect was largely attenuated in older male patients and not observed in female patients. Conclusion: In this large COVID-19 cohort, new-onset AF/AFL was associated with increased in-hospital mortality, yet this increased risk was restricted to males aged 60–72 years.
31 SEX- AND AGE SPECIFIC ASSOCIATION OF AF WITH MORTALITY IN COVID-19 INTRODUCTION Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) has infected more than 400 million people worldwide, including more than 160 million Europeans, with almost 5.8 million deaths attributed globally to the virus as of February 11th, 2022.1 With multiple vaccines available as well as the recent increase in immunisation from the omicron variant, which is possibly associated with an overall lower risk of clinical deterioration, some are optimistic that the end of the coronavirus disease 2019 (COVID-19) pandemic is in sight and that SARS-CoV-2 will become a yearly recurring more endemic virus. However, subsequent waves of new infections with new variants are to be expected in the upcoming years, given the 1) low global vaccination rate of 36%,2 and global shortage of vaccines, 2) high threshold needed for herd immunity,3 3) uncertainties regarding the duration of the immunological effect of the vaccines,4 4) high number of intermediate hosts for SARS-CoV-2,5 and in part due to this, 5) the continuous threat of (more contagious) variants reducing vaccine efficacy.6 Therefore, research into COVID-19 remains crucial. Since the start of the pandemic, cardiovascular complications have been increasingly recognised in patients suffering from COVID-19, ranging from vascular damage and cardiac injury to arrhythmias.7 Arrhythmias in COVID-19 patients may impact significantly on disease progression and outcome. As such, various population-based studies have reported a positive association between atrial fibrillation (AF)/atrial flutter (AFL) and mortality.8–10 However, these studies did not look at sex-specific influences, nor at the incremental effect of age (on a continuous scale), despite the fact that these parameters are known to influence AF/AFL outcomes in the general population.11,12 Therefore, in the large international CAPACITY-COVID dataset (NCT04325412) of 5,782 hospitalised COVID-19 patients, using the latest methodology, we explored the relation of AF and AFL to in-hospital mortality, with specific attention for sex- and age-related differences. METHODS Study design and study population For the current multicentre cohort study, pseudo-anonymous data generated during routine clinical care retrieved from the international patient registry CAPACITY-COVID (www.capacity-covid.eu) were used.13 The data within CAPACITY-COVID have been collected by 72 hospitals in 8 European (Belgium, France, Italy, the Netherlands, Portugal, Spain, Switzerland, United Kingdom) and 5 non-European (Egypt, Iran, Israel, Russia, Saudi-Arabia) countries. For this study, patients aged 18 years or older, admitted to any of the participating hospital centres before October 25th, 2020, 3
32 CHAPTER 3 with a laboratory confirmed SARS-CoV-2 infection during hospitalisation, were included. Readmission(s) from a single patient were evaluated as a single continuous presentation. Due to only few exclusion criteria, the database gives a reliable reflection of hospitalised COVID-19 patients during the first months of the pandemic, thus before availability of vaccine-induced immunity, and our analyses should therefore be interpreted as generalisable to patients with (largely) naïve immunity against SARSCoV-2. Local ethics approval was obtained in all participating hospitals. Assessment of informed consent was site specific, depending on national regulations, and has been described previously.13 Any researcher can request the data by submitting a proposal as outlined on https://capacity-covid.eu/for-professionals. Data extraction For this study the following variables were extracted: sex, age, medical history (including history of cardiac electrical disorders), body mass index (BMI), medication, physical examination findings, biomarkers, and follow-up data on the development of electrical disorders, cerebrovascular accident (CVA), pulmonary embolism, and mortality during hospitalisation. Electrical disorders were detected either through continuous rhythm monitoring or with (an) electrocardiogram(s) and were diagnosed according to the American College of Cardiology (ACC)/American Heart Association (AHA)/Heart Rhythm Society (HRS) 2006 key data elements and definitions for electrophysiological studies and procedures.14 Types of electrical disorders included AF, AFL, atrial tachycardia, atrioventricular (AV) nodal re-entry tachycardia, non-sustained ventricular tachycardia (nsVT), sustained ventricular tachycardia (sVT), ventricular fibrillation (VF), first degree AV block, second degree AV block, third degree AV block, complete left bundle branch block (LBBB), and complete right bundle branch block (RBBB). Statistical analyses Baseline characteristics of patients with COVID-19 disease are reported for the date of hospital admission. Categorical variables are presented as counts and percentages and numerical variables as means with standard deviations or medians with interquartile ranges (IQR), depending on the distribution. The prevalence of the development of each arrhythmic and conduction disorder during hospitalisation was calculated for the entire follow-up time (i.e. the time from hospital admission to discharge, death or loss to follow-up) and divided into patients without and with a history of that specific arrhythmic or conduction disorder (i.e. new-onset and recurrent, respectively). Only for patients with AF and for patients with AFL, newonset versus recurrent AF and new-onset versus recurrent AFL were defined as having no history of both AF and AFL versus a history of AF and/or AFL.
33 SEX- AND AGE SPECIFIC ASSOCIATION OF AF WITH MORTALITY IN COVID-19 To explore the association between all predefined patient characteristics and the development of the most prevalent new-onset arrhythmic disorder (i.e. AF and/or AFL), univariable logistic regression analyses were performed to estimate crude odds ratios (OR) and corresponding 95% confidence intervals (95% CI). Next, the association between development of new-onset AF and/or AFL during hospitalisation and in-hospital mortality in COVID-19 patients was first examined using univariable logistic regression analysis. Second, multivariable logistic regression analysis was performed with sex, a cubic spline function for age, the development of new-onset AF and/or AFL during hospitalisation, and the interaction between the latter two variables. The results of this analysis were depicted in plots for males and females separately. To explore whether other concomitant comorbidities and/or other known risk factors may have contributed to the observed results, we performed a sensitivity analysis where we additionally adjusted for CHA2DS2-VASc score. For all analyses, the different AF subtypes (paroxysmal, persistent, and permanent) were merged. All statistical analyses were performed using R version 4.0.2 with the bias reduction in binomial-response generalised linear models (brglm) function in the package ‘brglm’ version 0.7.1, which implements Firth correction reducing finite sample bias in the regression coefficients compared to default maximum likelihood regression.15 Non-linear relations are graphically displayed using the package ‘rms’ version 6.6.1 and the package ‘ggplot2’ version 3.3.2. In all univariable analyses with age and in all multivariable analyses, a cubic spline function for age (and in the univariable analyses for the association between BMI and new-onset AF and/or AFL also a cubic spline function for BMI) with four knots on recommended locations (on the percentiles 0.05, 0.35, 0.65, and 0.95) was used.16 Missing data for each variable were reported as percentages in the text or as counts in the corresponding tables. Since missing data was overall limited (e.g. maximum n=24 in mortality analyses), we proceeded with analyses of complete cases. Associations with two-sided p-values <0.05 were considered statistically significant. RESULTS A total of 5,782 patients were included in this study. The majority of them were hospitalised in European countries (89.9%). The median duration of hospital admission was 8 (IQR 4–17) days, and 28.8% (n=1664) of all subjects were admitted to the intensive care unit (ICU). Of the total study population, 63.8% was male and the median age was 67 (IQR 56–76) years. 12.5% (n=725) had been diagnosed with an arrhythmic event in the past, of which 93.2% (n=676) consisted of at least one episode of supraventricular arrhythmia and 7.7% (n=56) at least one episode of ventricular arrhythmia. Of all patients, 1.7% (n=96) had been diagnosed with at least one conduction disorder 3
34 CHAPTER 3 in the past. The most prevalent comorbidity registered was hypertension (47.6%), followed by diabetes mellitus (26.1%), chronic obstructive pulmonary disease (11.1%), renal impairment (10.7%), and prior myocardial infarction (9.2%). A complete list of all baseline characteristics, stratified by new-onset AF/AFL during hospitalisation and history of AF/AFL is presented in Table 1. Baseline characteristics stratified by other arrhythmias and conduction disorders are presented in Supplementary File S1. All variables had <3% missing, except for peripheral arterial disease (21.6%), BMI (24.7%), temperature (17.8%), C-reactive protein (12.2%), and white blood cell count (11.4%). Prevalence of AF/AFL The prevalence of AF and/or AFL in comparison to other arrhythmias and conduction disorders (recurrent and new-onset) during hospitalisation is summarised in Figure 1. Of all patients, 12.8% (95% CI 11.9–13.6) (n=737) experienced an arrhythmic event during hospitalisation, the vast majority being supraventricular (95.9%). AF and AFL were most common, occurring in 12.0% (95% CI 11.2–12.8) (n=692) of all patients, of which 86.7% (95% CI 84.0–89.1) (n=600) experienced only AF, 8.5% (95% CI 6.6–10.8) (n=59) experienced only AFL, and 4.8% (95% CI 3.4–6.6) (n=33) experienced both AF and AFL. In 60.7% (95% CI 57.0–64.3) (n=420) of patients the development of AF and/ or AFL was new-onset, whereas in the remaining 39.3% (95% CI 35.7–43.0) (n=272) AF and/or AFL had been present before hospital admission. Ventricular arrhythmias were rare (0.8% (95% CI 0.6–1.0)) and 50% of them were sVT or VF (n=23). A conduction disorder during hospitalisation was observed in 6.3% (95% CI 5.7–7.0) (n=365) of all patients. Association between patient characteristics and development of new-onset AF and/or AFL In univariable logistic regression analyses, sex, age, heart failure, hypertension, peripheral arterial disease, prior myocardial infarction, renal impairment, certain drugs, white blood cell count, duration of hospitalisation, and development of pulmonary embolism, showed an increased statistically significant association with the development of AF and/or AFL. Of medical history, heart failure seemed to be most strongly associated with a higher likelihood of developing AF and/or AFL compared to patients without heart failure: OR 1.72 (95% CI 1.05–2.64) (Supplementary File S2). Prognostic impact of new-onset AF and/or AFL on in-hospital mortality In absolute terms, there were only few patients aged <50 years and >90 years in our dataset who developed new-onset AF and/or AFL (n=7 and n=10, respectively). Because these small numbers could affect the reliability and precision of the point estimates of the outcomes to a high extent, only patients aged ≥50 and ≤90 years for new-onset AF and/or AFL were included in the mortality analyses.
35 SEX- AND AGE SPECIFIC ASSOCIATION OF AF WITH MORTALITY IN COVID-19 TABLE 1: BASELINE CHARACTERISTICS OF HOSPITALISED COVID-19 PATIENTS STRATIFIED BY THE AF/AFL EVENT DURING HOSPITALISATION AND HISTORY OF AF/AFL. Total (n=5,782) No AF/AFL (n=4,712) New-onset or recurrent AF/AFL (n=692) New-onset AF/AFL (n=420) Recurrent AF/AFL (n=271) Demographics Male sex n (%) 3,686 (63.8) 2,955 (62.7) 482 (69.7) 294 (70.0) 188 (69.4) Age in years median (IQR) 67 (56-76) 64 (54-74) 74 (69-81) 73 (66-79) 78 (73-83) History of supraventricular tachycardia AF n (%) 616 (10.7) 0 (0.0) 257 (37.2) 0 (0.0) 257 (94.8) AFL n (%) 52 (0.9) 0 (0.0) 23 (3.3) 0 (0.0) 23 (8.5) Atrial tachycardia n (%) 21 (0.4) 12 (0.3) 3 (0.4) 3 (0.7) 0 (0.0) AV nodal re-entry tachycardia n (%) 22 (0.4) 15 (0.3) 4 (0.6) 1 (0.2) 3 (1.1) History of ventricular tachycardia Non-sustained ventri- cular tachycardia n (%) 21 (0.4) 12 (0.3) 7 (1.0) 4 (1.0) 3 (1.1) Sustained ventricular tachycardia n (%) 15 (0.3) 14 (0.3) 0 (0.0) 0 (0.0) 0 (0.0) Ventricular fibrillation n (%) 24 (0.4) 17 (0.4) 6 (0.9) 6 (1.4) 0 (0.0) History of conduction disorders 1st AV block n (%) 19 (0.3) 13 (0.3) 2 (0.3) 1 (0.2) 1 (0.4) 2nd AV block n (%) 13 (0.2) 8 (0.2) 2 (0.3) 1 (0.2) 1 (0.4) 3rd AV block n (%) 26 (0.4) 16 (0.3) 2 (0.3) 1 (0.2) 1 (0.4) Left bundle branch block n (%) 24 (0.4) 14 (0.3) 5 (0.7) 4 (1.0) 1 (0.4) Right bundle branch block n (%) 18 (0.3) 12 (0.3) 4 (0.6) 2 (0.5) 2 (0.7) Other medical history Heart failure n (%) 315 (5.5) 156 (3.3) 88 (12.7) 23 (5.5) 64 (23.6) Hypertension n (%) 2,692 (47.6) 2,031 (44.0) 407 (60.2) 227 (55.4) 179 (67.5) Diabetes mellitus (type I or II) n (%) 1,494 (26.1) 1,195 (25.6) 188 (27.6) 100 (24.2) 87 (32.6) Peripheral arterial disease n (%) 271 (6.0) 181 (4.9) 54 (9.8) 26 (8.0) 28 (12.6) 3
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