# Impact of Cerebral Microbleeds in Stroke Patients with Atrial Fibrillation

Yannie Soo, Annaelle Zietz, Brian Yiu, Vincent C T Mok, Alexandros A Polymeris, David Seiffge, Gareth Ambler, Duncan Wilson, Thomas Wai Hong Leung, Suk Fung Tsang, et al.

► To cite this version:

Yannie Soo, Annaelle Zietz, Brian Yiu, Vincent C T Mok, Alexandros A Polymeris, et al. Impact of Cerebral Microbleeds in Stroke Patients with Atrial Fibrillation. Annals of Neurology, 2023, 94 (1), pp.61-74. 10.1002/ana.26642. inserm-04118626

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# Impact of Cerebral Microbleeds in Stroke Patients with Atrial Fibrillation

Yannie Soo, MB, ChB,¹ Annaelle Zietz, MMed,² Brian Yiu, BBA,¹

Vincent C. T. Mok, MD,¹,³ Alexandros A. Polymeris, MD, PhD,² David Seiffge, MD,⁴

Gareth Ambler, PhD,⁵ Duncan Wilson, MD, PhD,⁶ Thomas Wai Hong Leung, MD,¹

Suk Fung Tsang, MPhil,¹ Winnie Chu, MD,⁷ Jill Abrigo, MD,⁷ Cyrus Cheng, MB, ChB,¹

Keon-Joo Lee, MD,⁸ Jae-Sung Lim, MD,⁹ Masayuki Shiozawa, MD,¹⁰

Masatoshi Koga, MD, PhD,¹⁰ Hugues Chabriat, MD,¹¹ Michael Hennerici, MD,¹²

Yuen Kwun Wong, PhD,¹³ Henry Mak, MD,¹⁴ Roger Collet, MD,¹⁵ Shigeru Inamura, MD,¹⁶

Kazuhisa Yoshifuji, PhD,¹⁶ Ethem Murat Ar sava, MD,¹⁷ Solveig Horstmann, MD,¹⁸

Jan Purrucker, MD,¹⁸ Bonnie Y. K. Lam, PhD,¹,³ Adrian Wong, PhD,³ Young Dae Kim, MD,¹⁹

Tae-Jin Song, MD, PhD,²⁰ Robin Lemmens, PhD,²¹,²²,²³ Sebastian Eppinger, MD,²⁴,²⁵

Thomas Gattringer, MD,²⁴,²⁵ Ender Uysal, MD,²⁶ Derya Selçuk Demirelli, MD,²⁷

Natan M. Bornstein, MD,²⁸,²⁹ Einor Ben Assayag, PhD,²⁸,²⁹ Hen Hallevi, MD,²⁸,²⁹

Jeremy Molad, MD,²⁸,²⁹ Masashi Nishihara, MD,³⁰ Jun Tanaka, MD,³¹

Shelagh B. Coutts, MD,³² L. Jaap Kappelle, MD,³³ Rustam Al-Shahi Salman, PhD,³⁴

Rolf Jager, MD,³⁵ Gregory Y. H. Lip, MD,³⁶,³⁷ Martina B. Goeldlin, MD,⁴

Leonidas D. Panos, MD,⁴ Jean-Louis Mas, MD,³⁸ Laurence Legrand, PhD,³⁹

Chris Karayiannis, MD, PhD,⁴⁰ Thanh Phan, MD,⁴¹ Maximilian Bellut, MD,⁴²

Francesca Chappell, PhD,⁴³,⁴⁴ Stephen Makin, MBChB, PhD,⁴⁵ Derek Hayden, MD, MRCPI,⁴⁶

David Williams, PhD,⁴⁷ Dianne H. K. van Dam-Nolen, MD,⁴⁸ Paul J. Nederkoorn, MD, PhD,⁴⁹

Carmen Barbato, MD, PhD,⁵⁰ Simone Browning, BSc,⁵¹,⁵² Kim Wiegertjes, MD,⁵³

Anil Man Tuladhar, MD,⁵³ Anne-Marie Mendyk, RN,⁵⁴ Sebastian Köhler, PhD,⁵⁵

Robert van Oostenburgge, MD, PhD,⁵⁶ Ying Zhou, PhD,⁵⁷ Chao Xu, MD,⁵⁷

Saima Hilal, MPH, MD, PhD,⁵⁸ Bibek Gyanwali, MD, PhD,⁵⁹ Christopher Chen, FRCP,⁵⁹

Min Lou, MD, PhD,⁵⁷ Julie Staals, MD, PhD,⁵⁶ Regis Bordet, MD,⁵⁴

Nagaendran Kandiah, FRCP,⁶⁰ Frank-Erik de Leeuw, MD,⁵³ Robert Simister, PhD,⁵¹,⁵²

Jeroen Hendrikse, MD, PhD,⁶¹ Joanna Wardlaw, MD, FRCR,⁶²,⁶³ Peter Kelly, MD,⁶⁴

Felix Fluri, MD,⁴² Velandai Srikanth, PhD,⁶⁵ David Calvet, MD,³⁸ Simon Jung, MD,⁴

Vincent, I. H. Kwa, MD, PhD,⁶⁶ Eric E. Smith, MD, MPH, FAHA,³² Hideo Hara, MD, PhD,⁶⁷
ANNALS of Neurology

Yusuke Yakushiji, MD, PhD,⁶⁸ Dilek Necioglu Orken, MD,⁶⁹ Franz Fazekas, MD,²⁴
Vincent Thijs, MD,⁷⁰,⁷¹ Ji-Hoe Heo, MD ID,¹⁹ Roland Veltkamp, MD,¹⁸,⁷² Hakan Ay, MD,⁷³
Toshio Imaizumi, MD,¹⁶ Kui Kai Lau, DPhil,¹³,⁷⁴ Eric Jouvent, MD ID,⁷⁵,⁷⁶
Kazunori Toyoda, MD, PhD ID,¹⁰ Sohei Yoshimura, MD ID,¹⁰ Hee-Joon Bae, MD, PhD,⁷⁷
Joan Martí-Fàbregas, PhD ID,¹⁵ Luis Prats-Sánchez, MD, PhD,¹⁵ Philippe Lyrer, MD,²
Jonathan Best, MD,⁵¹,⁵² David Werring, PhD,⁵¹,⁵² Stefan T. Engelter, MD,²,⁷⁸ and
Nils Peters, MD,²,⁷⁸,⁷⁹ on behalf of the Microbleeds International Collaborative Network

View this article online at wileyonlinelibrary.com. DOI: 10.1002/ana.26642

Received Oct 7, 2022, and in revised form Mar 8, 2023. Accepted for publication Mar 14, 2023.

Address correspondence to Prof. Nils Peters, Stroke Center, Klinik Hirslanden Zürich, and Department of Neurology and Stroke Center, University Hospital
Basel, University of Basel, 4031, Switzerland. E-mail: nils.peters@unibas.ch

Yannie Soo and Annaelle Zietz are co-first authors and both have contributed equally to this work.

From the ¹Division of Neurology, Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong; ²Department of Neurology and Stroke Centre, University Hospital Basel and University of Basel, Basel, Switzerland; ³Gerald Choa Neuroscience Institute, Margaret K. L. Cheung Research Centre for Management of Parkinsonism, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Li Ka Shing Institute of Health Science, Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, The Chinese University of Hong Kong, Hong Kong SAR, Hong Kong; ⁴Department of Neurology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland; ⁵Department of Statistical Science, University College London, London, UK; ⁶Stroke Research Centre, Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK, New Zealand Brain Research Institute, Christchurch, New Zealand; ⁷Department of Imaging and Interventional Radiology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong; ⁸Department of Neurology, Korea University Guro Hospital, Seoul, Republic of Korea; ⁹Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea; ¹⁰Department of Cerebrovascular Medicine, National Cerebral and Cardiovascular Centre, Suita, Japan; ¹¹APHP, Lariboisière Hospital, Translational Neurovascular Centre, F-75475 Paris, France, FHU NeuroVasc, Université de Paris and INSERM U1141, Paris, France; ¹²Department of Neurology, University of Heidelberg/Mannheim Hospital, Mannheim, Germany; ¹³Division of Neurology, Department of Medicine, The University of Hong Kong, Hong Kong, Hong Kong; ¹⁴Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, Hong Kong; ¹⁵Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute, Barcelona, Spain; ¹⁶Department of Neurosurgery, Kushiro City General Hospital, Kushiro, Japan; ¹⁷Departments of Neurology and Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; ¹⁸Department of Neurology, Heidelberg University Hospital, Heidelberg, Germany; ¹⁹Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea; ²⁰Department of Neurology, Seoul Hospital, Ewha Womans University College of Medicine, Seoul, South Korea; ²¹Experimental Neurology, Department of Neurosciences, KU Leuven—University of Leuven, Leuven, Belgium; ²²VIB Center for Brain & Disease Research, Leuven, Belgium; ²³Department of Neurology, University Hospitals Leuven, Leuven, Belgium; ²⁴Department of Neurology, Medical University of Graz, Graz, Austria; ²⁵Division of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology, Medical University of Graz, Graz, Austria; ²⁶Antalya Teaching and Research Hospital, Department of Radiology, University of Health Sciences Turkey, Antalya, Turkey; ²⁷Sisli Hamidiye Etfal Teaching and Research Hospital, Department of Neurology, University of Health Sciences Turkey, Antalya, Turkey; ²⁸Department of Neurology, Tel-Aviv Sourasky Medical Center, Tel-Aviv, Israel; ²⁹Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel; ³⁰Department of Radiology, Saga University Faculty of Medicine, Saga, Japan; ³¹Department of Cerebrovascular Medicine, St. Mary's Hospital, Kurume, Japan; ³²Calgary Stroke Program, Department of Clinical Neurosciences, Radiology and Community Health Sciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Canada; ³³Department of Neurology and Neurosurgery, University Medical Centre Utrecht and Utrecht University, Utrecht, The Netherlands; ³⁴Centre for Clinical Brain Sciences, School of Clinical Sciences, University of Edinburgh, Edinburgh, UK; ³⁵Lysholm Department of Neuroradiology and the Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology and the National Hospital for Neurology and Neurosurgery, London, UK; ³⁶Liverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool John Moores University and Liverpool Heart & Chest Hospital, Liverpool, UK; ³⁷Department of Clinical Medicine, Aalborg University, Aalborg, Denmark; ³⁸GHU-Paris Psychiatrie et Neurosciences, Neurology Department and Stroke Unit, Sainte-Anne Hospital, and Université de Paris Cité, INSERM U1266, Institute of Psychiatry and Neuroscience of Paris, Paris, France; ³⁹GHU-Paris Psychiatrie et Neurosciences, Neuroradiology Department, Sainte-Anne Hospital, and Université Paris Cité, INSERM U1266, Institute of Psychiatry and Neuroscience of Paris, Paris, France; ⁴⁰Peninsula Clinical School, Peninsula Health, Monash University, Melbourne, Australia; ⁴¹Stroke and Ageing Research Group, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia; ⁴²Department of Neurology, University Hospital of Würzburg, Würzburg, Germany; ⁴³Centre for Clinical Brain Sciences, Edinburgh Imaging, Edinburgh, UK; ⁴⁴UK Dementia Institute at the University of Edinburgh, Edinburgh, UK; ⁴⁵Centre for Rural Health, Institute for Applied Health Sciences, University of Aberdeen, Aberdeen, UK; ⁴⁶Acute Medical Unit and Department of Age-related Healthcare, Tallaght University Hospital, Dublin, Ireland; ⁴⁷Department of Geriatric and Stroke Medicine, RCSI University of Medicine and Health Sciences Dublin, Ireland and Beaumont Hospital Dublin, Dublin, Ireland; ⁴⁸Department of Radiology and Nuclear Medicine, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands; ⁴⁹Department of Neurology, Amsterdam University Medical Centers, Amsterdam, The Netherlands; ⁵⁰Department of Neurology, University of Florence, Firenze, Italy; ⁵¹Stroke Research Centre, Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK; ⁵²Comprehensive Stroke Service, University College London Hospitals NHS Trust, London, UK; ⁵³Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Medical Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands; ⁵⁴University of Lille, Inserm, CHU de Lille. Lille Neuroscience & Cognition, Lille, France; ⁵⁵Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands; ⁵⁶Department of Neurology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Centre, Maastricht, The Netherlands; ⁵⁷Department of Neurology, The Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China; ⁵⁸Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore; ⁵⁹Memory Aging & Cognition Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore; ⁶⁰Dementia Research Centre (Singapore), Lee Kong
**Objectives:** Cerebral microbleeds are associated with the risks of ischemic stroke and intracranial hemorrhage, causing clinical dilemmas for antithrombotic treatment decisions. We aimed to evaluate the risks of intracranial hemorrhage and ischemic stroke associated with microbleeds in patients with atrial fibrillation treated with vitamin K antagonists, direct oral anticoagulants, antiplatelets, and combination therapy (i.e. concurrent oral anticoagulant and antiplatelet).

**Methods:** We included patients with documented atrial fibrillation from the pooled individual patient data analysis by the Microbleeds International Collaborative Network. Risks of subsequent intracranial hemorrhage and ischemic stroke were compared between patients with and without microbleeds, stratified by antithrombotic use.

**Results:** A total of 7,839 patients were included. The presence of microbleeds was associated with an increased relative risk of intracranial hemorrhage (adjusted hazard ratio [aHR] = 2.74, 95% confidence interval = 1.76–4.26) and ischemic stroke (aHR = 1.29, 95% confidence interval = 1.04–1.59). For the entire cohort, the absolute incidence of ischemic stroke was higher than intracranial hemorrhage regardless of microbleed burden. However, for the subgroup of patients taking combination of anticoagulant and antiplatelet therapy, the absolute risk of intracranial hemorrhage exceeded that of ischemic stroke in those with 2 to 4 microbleeds (25 vs 12 per 1,000 patient-years) and ≥ 11 microbleeds (94 vs 48 per 1,000 patient-years).

**Interpretation:** Patients with atrial fibrillation and high burden of microbleeds receiving combination therapy have a tendency of higher rate of intracranial hemorrhage than ischemic stroke, with potential for net harm. Further studies are needed to help optimize stroke preventive strategies in this high-risk group.

ANN NEUROL 2023;00:1–14

Stroke prevention with oral anticoagulants is the mainstay of treatment for patients with atrial fibrillation (AF). Treatment decisions require carefully balancing the benefit in reduction of ischemic stroke (IS) versus the potential increase in risk of intracranial hemorrhage (ICH) associated with antithrombotic drugs. As the risk of ICH remains the most serious complication of anticoagulation, a number of clinical risk scores have been developed to aid risk prediction for bleeding in patients with AF, for instance, HEMORR2AGES, ATRIA, ORBIT, and HASBLED.¹ Unfortunately, these scores have only moderate performance in predicting ICH and none could reliably discriminate patients at net risk of ICH than IS.¹⁻⁴

In recent years, cerebral microbleeds (CMBs) have evolved to be a useful radiological marker which improves risk prediction for ICH. As part of the spectrum of small vessel disease, CMBs are dot-like hypointense signals detected by heme-sensitive magnetic resonance imaging (MRI) sequences (eg, T2\*gradient-echo or susceptibility-weighted imaging [SWI]).⁵,⁶ They are perivascular hemosiderin deposits indicating previous asymptomatic leakage from bleeding-prone microangiopathy. Deep CMBs are commonly associated with hypertensive arteriopathy, whereas

pure lobar CMBs are classically associated with cerebral amyloid angiopathy (CAA), which has 4-fold increased risk of warfarin-associated ICH.⁷,⁸ Several studies have shown that the addition of this biomarker to conventional clinical risk scores could improve the predictive value of ICH.⁹⁻¹³

To help individualize antithrombotic decision among patients with CMBs, a large-scale global pooled individual patient data analysis was performed by the Microbleeds International Collaborative Network (MICON) which included 20,322 participants from 38 cohorts with previous IS or transient ischemic attack and baseline CMB evaluation.¹⁴ The burden of CMBs was found to have stronger associations with subsequent ICH than IS. However, as the absolute rate of IS was consistently higher than that of ICH irrespective of CMB burden and distribution, withholding antithrombotics routinely for all patients with CMBs is therefore not justified. In this study, the analysis was performed irrespective of stroke subtypes involved in the index event. It remains uncertain if variation in risk-to-benefit ratio may exist among patients with different stroke etiologies and antithrombotic therapies, particularly patients with AF on anticoagulants, which may have a higher risk of ICH than antiplatelets,¹⁵ but better efficacy in prevention of IS.¹⁶

Chian School of Medicine, Singapore, Singapore; ⁶¹Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, Utrecht, The Netherlands; ⁶²Division of Neuroimaging Sciences, Edinburgh Imaging, Edinburgh, UK; ⁶³UK Dementia Research Institute, University of Edinburgh and NHS Lothian, Edinburgh, UK; ⁶⁴The Neurovascular Research Unit and Health Research Board, Stroke Clinical Trials Network Ireland, University College Dublin, Dublin, Ireland; ⁶⁵Peninsula Clinical School, Peninsula Health, Monash University, Melbourne, Australia, National Centre for Healthy Ageing, Melbourne, Australia; ⁶⁶Department of Neurology, OLVG, Amsterdam, The Netherlands; ⁶⁷Division of Neurology, Department of Internal Medicine, Saga University Faculty of Medicine, Saga, Japan; ⁶⁸Department of Neurology, Kansai Medical University, Hirakata, Japan; ⁶⁹Department of Neurology, Istanbul Arel University, Istanbul, Turkey; ⁷⁰Stroke Division, Florey Institute of Neuroscience and Mental Health, University of Melbourne, Heidelberg, Australia; ⁷¹A. A. Martinos Center for Biomedical Imaging, Departments of Neurology and Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; ⁷²Department of Neurology, Austin Health, Heidelberg, Australia; ⁷³Department of Brain Sciences, Imperial College London, London, UK; ⁷⁴State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Shatin, Hong Kong; ⁷⁵Université de Paris—Assistance Publique Hôpitaux de Paris, Paris, France; ⁷⁶Département de Neurologie, Hôpital Lariboisière, FHU NeuroVasc, INSERM NeuroDiderot U1141, Paris, France; ⁷⁷Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea; ⁷⁸Neurology and Neurorehabilitation, University Department of Geriatric Medicine FELIX PLATTER, University of Basel, Basel, Switzerland; and ⁷⁹Stroke Center, Klinik Hirslanden, Zürich, Switzerland
We performed a subanalysis among patients with AF from the MICON cohort. We aimed to evaluate the risks of subsequent ICH and IS associated with CMBs among patients with AF, and stratify the stroke risks by 4 antithrombotic treatments: (1) vitamin K antagonist (VKA); (2) direct oral anticoagulants (DOACs); (3) antiplatelets (single or dual agents); and (4) combination therapy (i.e. concurrent oral anticoagulant and antiplatelet drugs).

# Methodology

## Study Design

The MICON cohort consists of patients from 18 countries in North America, Europe, the Middle East, Asia, and Australia. Inclusion criteria of the MICON collaboration were cohorts with (i) prospectively recruited adult participants with IS or transient ischemic attack, (ii) documented number and anatomical distribution of CMBs evaluated by MRI T2* or SWI, (iii) collected data on outcome events, including IS, ICH, vascular, and non-vascular death, and (iv) a follow-up period of at least 3 months.¹⁴ In this sub-analysis, we included 37 cohorts who agreed to participate. We included patients with known or newly diagnosed AF. Patients who had unknown status for AF were excluded.

The MICON project was approved by the Health Research Authority of the UK (REC reference: 8/HRA/0188). Included cohorts obtained ethical and regulatory approvals according to local requirements. As this study involved only fully anonymized data which have been published, individual consent was not required for this subanalysis. The MICON study protocol is registered on PROSPERO, CRD42016036602.

## Outcome Parameters

The primary outcomes were subsequent time to ICH alone and IS alone; and the secondary outcome was time to vascular death. All events were adjudicated according to individual cohort protocols. ICH was confirmed radiologically and included ICH, subdural, and subarachnoid hemorrhage. ICH attributed to intravenous thrombolysis or trauma were excluded. IS included acute and subacute symptoms lasting > 24 hours attributed to cerebral ischemia, diagnosed clinically, with or without radiological confirmation. Vascular death included deaths attributed to ICH, IS, systematic embolism, or myocardial infarction.

## Statistical Analysis

Baseline demographic, risk factor profiles, and radiological features were compared between patients with and without CMBs as well as patients with and without outcome events. Mann-Whitney test was used for continuous variables not normally distributed and *t* test for normally distributed variables. Categorical variables between groups

were compared with the $\chi^2$ test or Fisher's exact test when appropriate.

We calculated absolute rates of outcome events per 1,000 patient-years and constructed 95% confidence intervals for the mean of the Poisson distribution based on the number of observed events. We investigated the association between presence of CMBs, predefined CMB burden categories (0, 1, 2–4, 5–10, and ≥ 11 CMBs) and distribution of CMBs (pure deep, pure lobar, and mixed deep-lobar) in all outcome events by Cox regression adjusted for prognostic and confounding variables based on biological relevance, which included age, sex, history of hypertension, ischemic heart disease, diabetes mellitus, previous ischemic stroke, previous ICH, and type of MRI sequence used to detect CMBs (T2*-weighted Gradient Echo [GRE] or SWI). Patients with missing variables required for Cox regression analyses were excluded from the model. Interaction between presence of CMBs and ethnicity for risk of outcome parameters were investigated. Further analyses were performed to investigate the effect of probable CAA (defined by modified Boston Criteria) and white matter hyperintensities (ie, Fazekas scale ≥ 2) on risk of ICH for patients who have these variables available.

To investigate the influence of CMB burden in outcome events among patients on different antithrombotic treatments, we also performed interaction analyses by adding interaction terms between CMB burden categories and antithrombotic treatments. In addition, we repeated the adjusted multivariable Cox regression separately in patients on VKA, DOACs, antiplatelet, and combination therapy. Patients on unknown antithrombotic therapy were excluded from the model.

All analyses were done in SPSS 25 and R 3.4.5. The alpha level was set at 0.05.

# Results

Of the 38 cohorts in MICON, 37 cohorts agreed to participate, and 7,839 patients with documented AF were included in this subanalysis. The mean age was 75.7 ± 10.0 years, and 47.5% were women. Ethnicity was available in 6,386 patients, including 3,394 White patients, 2,973 Asian patients, and 19 Black patients. The median follow-up period was 23.5 months (interquartile range [IQR] = 9.9, 26.6 months), 35.6% of the patients had a follow-up period of less than 1 year.

## Characteristics of Patients with CMBs

CMBs were present in 2,142 (27.3%) patients and the exact CMB burden was available in 2,026 patients. Among patients with CMBs, the median number of CMBs was 2 (IQR = 2), including 970 patients with one
CMB, 675 patients with 2 to 4 CMBs, 210 patients with 5 to 10 CMBs, and 171 patients with ≥ 11 CMBs. Information of CMB distribution was available in 1,960 patients. Six hundred ninety-eight patients (35.6%) had pure lobar CMBs, 689 (35.1%) had pure deep CMBs, and 573 (29.3%) had mixed deep-lobar CMBs.

Compared to patients without CMBs, patients with CMBs were older, more likely to have hypertension, diabetes mellitus, ischemic heart disease, congestive heart failure, peripheral vascular disease, prior ischemic stroke, prior ICH, and previous antithrombotic use (Table 1). Furthermore, there were less patients who were scanned with MRI T2* sequence than SWI, and median Fazekas scores was higher in patients with CMBs (see Table 1).

## Intracranial Hemorrhage

Eighty-seven patients developed ICH over 13,741 patient-years of follow-up, with 50 (57.5%) ICH occurring within the first year of follow-up. There were 70 patients with ICHs, 3 subarachnoid hemorrhages, 13 subdural hemorrhages, and 1 patient with more than 1 type of ICH. Patients with ICH had a significantly higher prevalence of diabetes mellitus, peripheral vascular disease, and prior ICH (Table 2). The median CMB number was higher in patients with ICH (1 [IQR = 2]) than those without (0 [IQR = 1]), *p* < 0.001. The proportion of patients with ≥ 5 CMBs was higher in patients with ICH (15.7%) than those without (5.0%), *p* < 0.001 (see Table 2).

The incidence of ICH in patients with CMBs was 12 per 1,000 patient-years compared to 4 per 1,000 patient-years in those without CMBs, an absolute increase of 8 per 1,000 patient-years (Table S1A). The incidence rate of ICH increased with higher CMB burden but was consistently lower than that of IS in all CMB categories (Fig 1A). The presence of CMBs was associated with ICH with an adjusted hazard ratio (aHR) of 2.74 [IQR = 1.76–4.26]. Increased aHR for ICH was also observed with higher CMB burden (Fig 2A), deep CMBs (aHR = 4.39 [IQR = 2.51–7.67]) and mixed deep-lobar CMBs (aHR = 3.07 [IQR = 1.48–6.38]; see Table S1A, Fig 2A). Status of Modified Boston Criteria was available in 2,124 patients, whereas Fazekas score was available in 4,301 patients. There was no increase in risk of ICH in those with probable CAA (aHR = 1.35 [IQR = 0.17–10.48]) nor Fazekas score ≥ 2 (aHR = 0.67 [IQR = 0.32–1.41]).

## Ischemic Stroke

Four hundred twelve patients developed IS over 13,521 patient-years of follow-up, with 273 (66.3%) cases of IS occurring within the first year of follow-up. Patients with recurrent IS were significantly older and had higher

prevalence of diabetes mellitus, ischemic heart disease, peripheral artery disease, prior IS, and previous use of anticoagulants compared to patients without IS (Table 3). CMBs were more commonly present in patients with IS than those without (33.7% with IS vs 27.0% without IS, *p* = 0.003) and the proportion of patients with ≥ 5 CMBs was higher in patients with IS (7.9%) than those without (4.9%), *p* = 0.009 (see Table 3).

The incidence of IS was 33 per 1,000 patient-years in patients with CMBs compared to 24 per 1,000 patient-years in those without, an increase by 9 per 1,000 patient-years (aHR = 1.29 [IQR = 1.04–1.59]; see Table S1A). The presence of mixed deep-lobar CMBs was associated with increased aHR for IS (aHR = 1.57 [IQR = 1.11–2.22]; see Fig 2B). However, a higher burden of CMBs had no influence on incidence of IS (see Table S1A, Fig 2B). Interaction was noted between presence of CMBs with an asian population for IS (aHR = 1.61 [IQR = 1.01–2.58], *p* interaction = 0.046). No interaction was detected between CMBs and other ethnic groups for other outcome events.

## Vascular Death

Vascular death occurred in 330 patients over 13,494 patient-years follow-up. The incidence of vascular death was 26 per 1,000 patient-years in patients with CMBs compared to 22 per 1,000 patient-years in patients without CMBs, an increase by 4 per 1,000 patient-years (aHR = 0.93 [IQR = 0.73–1.19]). There was no association between presence nor burden of CMBs with risk of vascular death in patients with AF overall (see Table S1A, Fig 2C).

## Subgroup Analyses of Patients on Different Antithrombotics

After an index event of IS or transient ischemic attack, 7,379 patients received antithrombotic therapy (3,244 patients received a VKA, 1,981 patients received a DOAC, 626 patients received antiplatelet, and 1,528 patients received combination therapy). Twenty-one patients on unknown antithrombotic drugs were excluded from this subanalysis. Interaction for ICH risk was detected between CMB burden categories and VKA (*p* interaction = 0.04), anti-platelet (*p* interaction < 0.001) and combination therapy (*p* interaction < 0.001), but not DOACs. Interaction for IS risk was detected between CMB burden and antiplatelet therapy (*p* interaction < 0.001) but not with other antithrombotics. No interaction was noted between CMB burden and anti-thrombotic treatments for vascular death risk.

**Patients on VKA and DOACs.** For patients on VKA, patients with CMBs had higher incidence of ICH
<table><caption>TABLE 1. Characteristics of Patients with Atrial Fibrillation with and without Cerebral Microbleeds</caption><thead><tr><th></th><th>No. of patients with data available</th><th>With CMB (n = 2,142)</th><th>Without CMB (n = 5,697)</th><th>p</th></tr></thead><tbody><tr><td><strong>Demography</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Mean age ± SD, yr</td><td>7,821</td><td>77.1 ± 9.6</td><td>75.2 ± 10.1</td><td>&lt; 0.001</td></tr><tr><td>Female, n (%)</td><td>7,839</td><td>994 (46.4)</td><td>2730 (47.9)</td><td>0.231</td></tr><tr><td>Race, n (%)</td><td>6,386</td><td></td><td></td><td>0.317</td></tr><tr><td>Whites</td><td></td><td>940 (51.7)</td><td>2454 (53.7)</td><td>-</td></tr><tr><td>Asian</td><td></td><td>874 (48)</td><td>2,099 (46)</td><td>-</td></tr><tr><td>Black</td><td></td><td>5 (0.3)</td><td>14 (0.3)</td><td>-</td></tr><tr><td><strong>Clinical risk factors</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Current smoker, n (%)</td><td>6,812</td><td>222 (12)</td><td>623 (12.6)</td><td>0.497</td></tr><tr><td>Current drinker, n (%)</td><td>5,121</td><td>187 (13.7)</td><td>592 (15.8)</td><td>0.067</td></tr><tr><td>Hypertension, n (%)</td><td>7,813</td><td>1,735 (81.3)</td><td>4,290 (75.5)</td><td>&lt; 0.001</td></tr><tr><td>Dyslipidemia, n (%)</td><td>7,539</td><td>836 (40.8)</td><td>2180 (39.7)</td><td>0.413</td></tr><tr><td>Diabetes mellitus, n (%)</td><td>7,665</td><td>524 (25)</td><td>1247 (22.4)</td><td>0.016</td></tr><tr><td>Ischemic heart disease, n (%)</td><td>7,561</td><td>446 (21.6)</td><td>890 (16.2)</td><td>&lt; 0.001</td></tr><tr><td>Congestive heart failure, n (%)</td><td>5,599</td><td>201 (13.7)</td><td>437 (10.6)</td><td>0.001</td></tr><tr><td>Peripheral vascular disease, n (%)</td><td>4,381</td><td>284 (24.8)</td><td>558 (17.2)</td><td>&lt; 0.001</td></tr><tr><td>History of ischemic stroke, n (%)</td><td>7,809</td><td>505 (23.6)</td><td>943 (16.6)</td><td>&lt; 0.001</td></tr><tr><td>History of ICH, n (%)</td><td>7,247</td><td>64 (3.2)</td><td>56 (1.1)</td><td>&lt; 0.001</td></tr><tr><td>Previous antiplatelet, n (%)</td><td>6,334</td><td>726 (42.8)</td><td>1830 (39.4)</td><td>0.015</td></tr><tr><td>Previous anticoagulants, n (%)</td><td>6,335</td><td>356 (21.0)</td><td>734 (15.8)</td><td>&lt; 0.001</td></tr><tr><td>Medication at baseline, n (%)</td><td>7,839</td><td></td><td></td><td>0.058</td></tr><tr><td>None</td><td></td><td>304 (5.3)</td><td>135 (6.3)</td><td>-</td></tr><tr><td>VKA</td><td></td><td>2,344 (41.1)</td><td>900 (42.0)</td><td>-</td></tr><tr><td>DOAC</td><td></td><td>1,438 (25.2)</td><td>543 (25.4)</td><td>-</td></tr><tr><td>Antiplatelet</td><td></td><td>447 (7.8)</td><td>179 (8.4)</td><td>-</td></tr><tr><td>Combination therapy</td><td></td><td>1145 (20.1)</td><td>383 (17.9)</td><td>-</td></tr><tr><td>Unknown oral anticoagulant</td><td></td><td>19 (0.3)</td><td>2 (0.1)</td><td>-</td></tr><tr><td><strong>Radiological features</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>MRI T2*, n (%)</td><td>7,803</td><td>1,363 (63.6)</td><td>3,906 (69.0)</td><td>&lt; 0.001</td></tr><tr><td>Median Fazekas score (IQR)</td><td>4,301</td><td>3 (3)</td><td>2 (2)</td><td>&lt; 0.001</td></tr></tbody></table>

Abbreviations: CMB = cerebral microbleed; DOAC = direct acting oral anticoagulant; ICH = intracranial hemorrhage; IQR = interquartile range; MRI = magnetic resonance imaging; SD = standard deviation; VKA = vitamin K antagonist.

compared to patients without CMBs (12 per 1,000 patient-years with CMBs versus 6 per 1,000 patient-years without CMBs, aHR = 1.92 [IQR = 1.06–3.49]). The

association was mostly driven by patients with 5 to 10 CMBs who had significantly higher aHR for ICH (aHR = 4.04 [IQR = 1.19–13.66]; see Table S1B).
<table><caption>TABLE 2. Characteristics of Patients with Atrial Fibrillation with and without Intracranial Hemorrhage</caption><thead><tr><th></th><th>No. of patients with data available</th><th>With ICH (n = 87)</th><th>Without ICH (n = 7,752)</th><th>p</th></tr></thead><tbody><tr><td><strong>Demography</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Mean age ± SD, yr</td><td>7,821</td><td>77.1 ± 8.9</td><td>75.7 ± 10.0</td><td>0.206</td></tr><tr><td>Female, n (%)</td><td>7,839</td><td>42 (48.3)</td><td>3682 (47.5)</td><td>0.885</td></tr><tr><td>Race, n (%)</td><td>6,386</td><td></td><td></td><td>0.397</td></tr><tr><td>Whites</td><td></td><td>46 (60.5)</td><td>3,348 (53.1)</td><td>-</td></tr><tr><td>Asian</td><td></td><td>30 (39.5)</td><td>2,943 (46.6)</td><td>-</td></tr><tr><td>Black</td><td></td><td>0 (0)</td><td>19 (0.3)</td><td>-</td></tr><tr><td><strong>Clinical risk factors</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Current smoker, n (%)</td><td>6,812</td><td>7 (9.6)</td><td>838 (12.4)</td><td>0.463</td></tr><tr><td>Current drinker, n (%)</td><td>5,121</td><td>6 (9.8)</td><td>773 (15.3)</td><td>0.240</td></tr><tr><td>Hypertension, n (%)</td><td>7,813</td><td>69 (79.3)</td><td>5,956 (77.1)</td><td>0.624</td></tr><tr><td>Dyslipidemia, n (%)</td><td>7,539</td><td>36 (42.9)</td><td>2,980 (40.0)</td><td>0.592</td></tr><tr><td>Diabetes mellitus, n (%)</td><td>7,665</td><td>29 (34.1)</td><td>1,742 (23.0)</td><td>0.015</td></tr><tr><td>Ischemic heart disease, n (%)</td><td>7,561</td><td>20 (23.8)</td><td>1,316 (17.6)</td><td>0.138</td></tr><tr><td>Congestive heart failure, n (%)</td><td>5,599</td><td>8 (11.1)</td><td>630 (11.4)</td><td>0.939</td></tr><tr><td>Peripheral vascular disease, n (%)</td><td>4,381</td><td>19 (35.2)</td><td>823 (19.0)</td><td>0.003</td></tr><tr><td>History of ischemic stroke, n (%)</td><td>7,809</td><td>20 (23.3)</td><td>1,428 (18.5)</td><td>0.258</td></tr><tr><td>History of ICH, n (%)</td><td>7,247</td><td>7 (8.2)</td><td>113 (1.6)</td><td>&lt; 0.001</td></tr><tr><td>Previous antiplatelet, n (%)</td><td>6,334</td><td>35 (46.1)</td><td>2,521 (40.3)</td><td>0.308</td></tr><tr><td>Previous anticoagulants, n (%)</td><td>6,335</td><td>15 (19.5)</td><td>1,075 (17.1)</td><td>0.585</td></tr><tr><td>Medication at baseline, n (%)</td><td>7,839</td><td></td><td></td><td>0.148</td></tr><tr><td>None</td><td></td><td>2 (2.3)</td><td>437 (5.6)</td><td>-</td></tr><tr><td>VKA</td><td></td><td>48 (55.2)</td><td>3,196 (41.2)</td><td>-</td></tr><tr><td>DOAC</td><td></td><td>16 (18.4)</td><td>1,965 (25.3)</td><td>-</td></tr><tr><td>Antiplatelet</td><td></td><td>7 (8.0)</td><td>619 (8.0)</td><td>-</td></tr><tr><td>Combination therapy</td><td></td><td>14 (16.1)</td><td>1,514 (19.5)</td><td>-</td></tr><tr><td>Unknown oral anticoagulant</td><td></td><td>0 (0)</td><td>21 (0.3)</td><td>-</td></tr><tr><td><strong>Radiological features</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>MRI T2*, n (%)</td><td>7,803</td><td>31 (35.6)</td><td>2,503 (32.4)</td><td>0.527</td></tr><tr><td>CMB presence, n (%)</td><td>7,839</td><td>45 (51.7)</td><td>2,097 (27.1)</td><td>&lt; 0.001</td></tr><tr><td>Median CMB number (IQR)</td><td>7,497</td><td>1 (2)</td><td>0 (1)</td><td>&lt; 0.001</td></tr><tr><td>≥ 5 CMBs, n (%)</td><td>7,497</td><td>13 (15.7)</td><td>368 (5.0)</td><td>&lt; 0.001</td></tr><tr><td>Probable cerebral amyloid angiopathy, n (%)</td><td>2,124</td><td>1 (3.7)</td><td>64 (3.1)</td><td>0.845</td></tr><tr><td>Median Fazekas score (IQR)</td><td>4,301</td><td>2 (3)</td><td>2 (2)</td><td>0.899</td></tr></tbody></table>

Abbreviations: CMB = cerebral microbleed; DOAC = direct acting oral anticoagulant; ICH = intracranial hemorrhage; IQR = interquartile range; MRI = magnetic resonance imaging; SD = standard deviation; VKA = vitamin K antagonist.
<figure><img src="image_3.png" /><figcaption>FIGURE 1: Incidence rate of ICH, IS, and vascular death during follow-up in patients with atrial fibrillation in general (A), on VKA (B), on DOAC (C), on antiplatelet (D) and on combination therapy (E). AF = atrial fibrillation; CMB = cerebral microbleed; DOAC = direct oral anticoagulant; ICH = intracranial hemorrhage; IS = ischemic stroke; VKA = vitamin K antagonist.</figcaption></figure>
<table><caption>TABLE 3. Characteristics of Patients with Atrial Fibrillation with and without Ischemic Stroke</caption><thead><tr><th></th><th>No. of patients with data available</th><th>With IS (n = 412)</th><th>Without IS (n = 7,427)</th><th>p</th></tr></thead><tbody><tr><td><strong>Demography</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Mean age ± SD, yr</td><td>7,821</td><td>77.1 ± 91</td><td>75.7 ± 10.1</td><td>0.001</td></tr><tr><td>Female, n (%)</td><td>7,839</td><td>210 (51.0%)</td><td>3,514 (47.3%)</td><td>0.148</td></tr><tr><td>Race, n (%)</td><td>6,386</td><td></td><td></td><td>&lt; 0.001</td></tr><tr><td>Whites</td><td></td><td>131 (41.1%)</td><td>3,263 (53.8%)</td><td>-</td></tr><tr><td>Asian</td><td></td><td>184 (57.7%)</td><td>2,789 (46.0%)</td><td>-</td></tr><tr><td>Black</td><td></td><td>4 (1.3%)</td><td>15 (0.2%)</td><td>-</td></tr><tr><td><strong>Clinical risk factors</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Current smoker, n (%)</td><td>6,812</td><td>32 (9.8%)</td><td>813 (12.5%)</td><td>0.152</td></tr><tr><td>Current drinker, n (%)</td><td>5,121</td><td>38 (12.8%)</td><td>741 (15.4%)</td><td>0.223</td></tr><tr><td>Hypertension, n (%)</td><td>7,813</td><td>331 (80.3%)</td><td>5,694 (76.9%)</td><td>0.109</td></tr><tr><td>Dyslipidemia, n (%)</td><td>7,539</td><td>163 (41.8%)</td><td>2,853 (39.9%)</td><td>0.459</td></tr><tr><td>Diabetes mellitus, n (%)</td><td>7,665</td><td>120 (30.0%)</td><td>1,651 (22.7%)</td><td>0.001</td></tr><tr><td>Ischemic heart disease, n (%)</td><td>7,561</td><td>90 (22.2%)</td><td>1,246 (17.4%)</td><td>0.014</td></tr><tr><td>Congestive heart failure, n (%)</td><td>5,599</td><td>49 (14.5%)</td><td>589 (11.2%)</td><td>0.064</td></tr><tr><td>Peripheral vascular disease, n (%)</td><td>4,381</td><td>84 (29.7%)</td><td>758 (18.5%)</td><td>&lt; 0.001</td></tr><tr><td>History of ischemic stroke, n (%)</td><td>7,809</td><td>125 (30.5%)</td><td>323 (17.9%)</td><td>&lt; 0.001</td></tr><tr><td>History of ICH, n (%)</td><td>7,247</td><td>11 (2.7%)</td><td>109 (1.5%)</td><td>0.119</td></tr><tr><td>Previous antiplatelet, n (%)</td><td>6,334</td><td>147 (44.7%)</td><td>2,409 (40.1%)</td><td>0.100</td></tr><tr><td>Previous anticoagulants, n (%)</td><td>6,335</td><td>85 (25.8%)</td><td>1,005 (16.7%)</td><td>&lt; 0.001</td></tr><tr><td>Medication at baseline, n (%)</td><td>7,839</td><td></td><td></td><td>0.004</td></tr><tr><td>None</td><td></td><td>26 (6.3%)</td><td>413 (5.6%)</td><td>-</td></tr><tr><td>VKA</td><td></td><td>171 (41.5%)</td><td>3,073 (41.4%)</td><td>-</td></tr><tr><td>DOAC</td><td></td><td>92 (22.3%)</td><td>1,889 (25.4%)</td><td>-</td></tr><tr><td>Antiplatelet</td><td></td><td>53 (12.9%)</td><td>573 (7.7%)</td><td>-</td></tr><tr><td>Combination therapy</td><td></td><td>70 (17.0%)</td><td>1,458 (19.6%)</td><td>-</td></tr><tr><td>Unknown oral anticoagulant</td><td></td><td>0 (0%)</td><td>21 (0.3%)</td><td>-</td></tr><tr><td><strong>Radiological features</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>MRI sequence-T2*, n (%)</td><td>7,803</td><td>260 (63.7%)</td><td>5,009 (67.7%)</td><td>0.092</td></tr><tr><td>CMB presence, n (%)</td><td>7,839</td><td>139 (33.7%)</td><td>2,003 (27.0%)</td><td>0.003</td></tr><tr><td>Median CMB number (IQR)</td><td>7,497</td><td>0 (1)</td><td>0 (1)</td><td>&lt; 0.001</td></tr><tr><td>≥ 5 CMBs, n (%)</td><td>7,497</td><td>31 (7.9%)</td><td>350 (4.9%)</td><td>0.009</td></tr></tbody></table>

Abbreviations: CMB = cerebral microbleeds; DOAC = direct acting oral anticoagulant; ICH = intracranial hemorrhage; IQR = interquartile range; MRI = magnetic resonance imaging; SD = standard deviation; VKA = vitamin K antagonist.
<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /><figcaption>FIGURE 2: Forest plots of associations for (A) ICH, (B) IS, and (C) vascular death during follow-up. aHR = adjusted hazard ratio; CMB = cerebral microbleed; ICH = intracranial hemorrhage; IS = ischemic stroke.</figcaption></figure>

Furthermore, presence of CMBs was associated with a trend of increased incidence of IS (aHR = 1.37 [IQR = 0.99–1.89]), whereas patients with ≥ 11 CMBs had significantly higher incidence of IS compared to patients without CMBs (66 per 1,000 patient-years with ≥ 11 CMBs vs 24 per 1,000 patient-year without CMBs, aHR = 2.37 [IQR = 1.13–5]). Neither presence of CMBs nor their burden influenced risk of vascular death (see Table S1B).

For patients on DOACs, neither the presence nor burden of CMBs influenced the risk of ICH, IS and vascular death (see Table S1C).

**Patients on Antiplatelet Drugs.** Compared to patients without CMBs, presence of CMBs in patients on antiplatelet drugs was associated with a significantly higher incidence of IS (72 per 1,000 patient-years with CMBs vs 33 per 1,000 patient-years without CMBs, aHR = 2.43 [IQR = 1.34–4.43]). The association was mostly driven by patient with 5 to 10 CMBs (aHR = 7.27 [IQR = 2.76–19.15]) who also had increased incidence for vascular mortality (aHR = 6.05 [IQR = 1.44–25.45]; see Table S1D).

For patients on antiplatelet drugs, no statistically significant association between presence of CMBs and risk of ICH was observed (21 per 1,000 patient-years with CMBs vs 3 per 1,000 patient-years without CMBs, aHR = 4.93 [IQR = 0.81–30.18]). The small number of ICHs in patients on antiplatelet drugs (n = 5) precluded further multivariate analyses for CMB burden on risk of ICH.

**Patients on Combination Therapy.** For patients on combination therapy, the incidence of ICH was higher among patients with CMBs (18 per 1,000 patient-years) compared to patients without CMBs (2 per 1,000 patient-years; aHR = 7.92 [IQR = 2.43–25.82]). The association was most significant among patients with 2 to 4 CMBs (aHR = 10.23 [IQR = 2.41–43.37]) and ≥ 11 CMBs (aHR = 27.97 [IQR = 5.57–140.55]). In this treatment group, neither the presence nor burden of CMBs was associated with increased incidence of IS, whereas the presence of ≥ 11 CMBs was associated with increased risk of vascular death (aHR = 4.76 [IQR = 1.31–17.26]; see Table S1E).

Given the above findings in this treatment group, we did a more detailed post hoc analysis on patients receiving combination treatment; these patients had a higher proportion of dyslipidemia (43.4% vs 39.2%, *p* < 0.001), ischemic heart disease (22.7% vs 16.4%, *p* < 0.001), and peripheral vascular disease (23.1% vs 18.1%, *p* < 0.001) compared to patients receiving either anticoagulant or antiplatelet alone.
**Absolute Incidence of Outcome Events Stratified by Antithrombotic Use.** The number of patients in each treatment group and the incidence of outcome events among different CMB categories are shown in Table S1B–E and Figure 1B–E. The absolute incidence rate of IS was higher than ICH for the majority of the patients except for (i) patients on VKA with 5 to 10 CMBs whose rate of ICH was comparable to that of IS (25 per 1,000 patient-years for ICH vs 23 per 1,000 patient-years for IS); (ii) patients on antiplatelet with 1 CMB whose rate of ICH was comparable to IS (48 per 1,000 patient-years for ICH vs 44 per 1,000 patient-years for IS), and (iii) patients on combination therapy with 2 to 4 CMBs and ≥ 11 CMBs who had a rate of ICH almost double that of IS (25 per 1,000 patient-years for ICH vs 12 per 1,000 patient-years for IS in patients with 2 to 4 CMBs and 94 per 1,000 patient-years for ICH vs 48 per 1,000 patient-years for IS in patients with ≥ 11 CMBs; see Fig 1B–E). Among all the treatment groups, the highest rate of ICH was observed among patients on combination therapy with ≥ 11 CMBs (94 per 1,000 patient-years; see Table S1E).

Discussion

In this subanalysis of the MICON pooled individual patient data cohort among patients with AF who had a stroke, the presence of CMBs was associated with increased risk of subsequent ICH and IS but not vascular death; the burden of CMBs had a stronger association with risk of ICH than IS. The absolute rate of subsequent stroke, however, varied among different antithrombotic treatments according to CMB burden. For most patients, the absolute rate of IS was higher than that of ICH. However, for patients on combination therapy with multiple CMBs, the absolute rate of ICH exceeded that of IS, with potential for net clinical harm. Among all antithrombotic treatments, DOAC was the only one which was not associated with an increased risk of ICH, IS, or vascular death among patients with CMBs.

In recent years, the addition of CMBs to clinical scores in stroke risk stratification has been shown to improve the predictive power for ICH versus IS.⁹,¹⁰,¹³ In addition, in patients with AF on anticoagulation, high lesion load of over-all small vessel disease, including the presence of perivascular spaces, CMBs, white matter hyperintensities, and lacunes¹⁷ was found to be associated with ICH.¹⁸

Regarding the distribution of CMBs in predicting outcome events, subsequent ICH was strongly associated with presence of deep CMBs, either as pure deep CMBs or mixed deep-lobar CMBs, suggesting that deep perforator arteriopathy (arteriolosclerosis) is an important factor contributing to the development of ICH in these patients.¹⁹ In contrast to our understanding that CAA is

associated with 4-fold increased risk of anticoagulant-related ICH,²⁰ we did not find an increased risk of ICH in the subset of patients rated as probable CAA. This could be accounted by the small number of patients with probable CAA in our study, however, it might also suggest that pure lobar CMBs may be related to etiologies other than CAA in patients with AF who had a stroke.

Despite the stronger association of CMBs with ICH than IS, the absolute rate for IS was higher than ICH in the overall AF subcohort irrespective of the CMB burden (see Table S1), which is consistent with the findings in the main MICON study on patients with different stroke etiologies and antithrombotic treatments. Interestingly, the absolute rate of IS in our present study was lower compared to the main study for both patients with CMBs (33 vs 46 per 1,000 patient-years) and those without CMBs (24 vs 30 per 1,000 patient-years). The lower incidence rate of IS in the AF subcohort may be related to the high efficacy of anticoagulants for prevention of cardioembolic ischemic stroke. The rate of ICH was similar among patients with CMBs (12 per 1,000 patients-years in both studies) and those without CMBs (4 per 1,000 patients-years in both studies). Despite a higher proportion of patients on oral anticoagulant in the AF subcohort (86.1%) than in the main study (38.1%), the same absolute rate of ICH in these 2 studies suggests that factors other than antithrombotic use (eg, blood pressure variability), might also influence the risk of ICH.¹⁴

Few randomized controlled studies included MRI imaging substudies.²¹,²² In the NAVIGATE ESUS trial, the presence of CMBs was associated with recurrent IS, ICH, and death but the numbers of outcome events were too small to draw conclusions about the ICH risk depending on the antithrombotic treatment (ie, rivaroxaban vs aspirin).²² More importantly none of these trials included patients on combination therapy leading to a lack of randomized data in this high-risk group.

To the best of our knowledge, we have conducted the largest study evaluating the risk–benefit ratio of different antithrombotic treatments in patients with AF who had a stroke and CMBs. Comparing the 4 observed antithrombotic treatments for AF in a real-world setting, DOAC monotherapy appeared to be the safest antithrombotic regimen, which was not associated with IS, ICH, or vascular death across all CMB burden categories. For patients on VKA, comparable rates of ICH (25 per 1,000 patient-years) and IS (23 per 1,000 patient-years) were observed among patients with 5 to 10 CMBs but not among the other CMB categories. The net-benefit of DOACs over VKA observed in our study was in line with recent publications on dependent and elderly patients with AF with stroke, who are also at high risk of having multiple CMBs.²³,²⁴
Our analysis of stroke risks in patients on combina-
tion therapy provides additional insight to this under-
studied high-risk group. In the recently defined risk score
models derived from the MICON cohort for prediction of
ICH (MICON-ICH) and IS (MICON-IS), patients on
combination therapy were not specifically captured and
were categorized under the treatment category of anticoag-
ulants. Our analysis of the subset of patients on concur-
rent anticoagulant and antiplatelet allows us to better
delineate the relative risks of ICH and IS, which may be
different from the rest of the cohort due to the increased
risk of ICH from additional antithrombotic treatments as
well as higher risk of IS from the increased comorbidities
of these patients.²⁵ With more than 1,500 subjects on
combination therapy in our AF-cohort (19.5% among
patients with AF vs 2.6% in the MICON patients with-
out AF), this treatment seems to be of clinical relevance in
patients with AF who had a stroke. In our study, there was
a 2-fold higher absolute rate of ICH than IS in patients on
combination therapy with 2 to 4 and ≥ 11 CMBs. This
reflects the importance of including detailed antithrombotic
information when individualizing stroke risk in patients
with AF and CMBs. Our study suggests that concomitant
antiplatelet use in anticoagulated patients for AF may be an
important component for further risk stratification and
could be of added value to the established risk scores.¹³

From our post hoc analysis, patients on combination
therapy more often had ischemic heart and peripheral vas-
cular diseases. Other possible indications for combination
therapy include recent acute coronary syndrome, angio-
plasty or stenting of coronary, carotid or peripheral arter-
ies, which unfortunately were not captured in our cohort.
Nevertheless, after adjusting for relevant cardiovascular
risk factors in the Cox regression model, the presence of
2 to 4 and ≥ 11 CMBs remained independent predictors
for ICH but not IS. Further randomized controlled trials
are warranted to determine the best treatment strategy for
stroke prevention in patients with AF and multiple CMBs
with indications for combination therapy. More impor-
tantly, a pre-emptive approach is important to mitigate
the risk of ICH in these patients. General measures
include stringent blood pressure control, frequent moni-
toring of International Normalized Ratio (INR) for
patients on VKA and renal function for patients on
DOACs. Indications for combination therapy should be
verified continuously,²⁶,²⁷ whereas duration of a therapy
should be minimized according to the latest
guidelines.²⁸⁻³⁰ Moreover, agents with lower risk of ICH
.ie, DOACs instead of VKA) should be considered.

Limitations of this study include (1) the non-
randomized design using prospective collected observational
data. We aimed to minimize the risk of confounding with

comprehensive adjustment for known stroke risk factors, nev-
ertheless, multiplicity of testing as well as potential unac-
counted confounding factors may have influenced our
observations and thus our results should be interpreted with
caution; (2) limited numbers of patients with ≥ 5 CMBs
which did not allow us to detect a potentially linear increase
in ICH risk in patients on different antithrombotic agents,
particularly in patients under antiplatelets; (3) missing infor-
mation on the specific indication and duration of the combi-
nation therapy as well as possible changes of antithrombotic
treatments and patients’ compliance; (4) missing information
on the Modified Boston Criteria in over two-third of the
patients which may lead to underestimation of probable CAA
in our cohort; (5) the study population is mainly based on
European and Asian cohorts, thus lowering the generalizability
to other ethnic groups; (6) data regarding the etiological classi-
fication of recurrent IS during the follow-up period were not
assessed systematically in all MICON cohorts; and (7) the
median follow-up period of our study was 23.5 months thus
we cannot determine long-term risks and benefits of different
antithrombotic treatments beyond 2 years.

To the best of our knowledge, this is the largest
study so far investigating the impact of CMBs in patients
with AF. Our study has the following additional strengths
(1) we used well characterized pooled individual patient
data from MICON with prospective data for CMBs eval-
uation and outcome events from different ethnic groups;
and (2) a detailed analysis of the stroke risk associated
with different CMB burden, stratified by observed anti-
thrombotic treatments, which pragmatically helps with
decision making in daily clinical practice.

In conclusion, among patients with AF on anti-
thrombotic therapy for secondary prevention after IS or tran-
sient ischemic attack, presence of CMBs was associated with
increased risk of both subsequent ICH and IS, with stronger
association with the former. Among the 4 antithrombotic
treatments in this study which reflects a real-world treatment
setting, DOAC was the only agent which was not associated
with IS, ICH, or vascular death in the presence of CMBs.
Although the absolute incidence of IS was higher than ICH
regardless of CMB burden for most patient, patients under
combination therapy with multiple CMBs might have an
absolute risk of ICH exceeding that of IS. As the findings
are hypothesis generating, further randomized controlled tri-
als are needed to determine the best strategy for stroke pre-
vention in this high-risk group.

Acknowledgments

This study was funded by the Swiss Heart Foundation.
Furthermore, the study was funded in part by Wellcome
Trust (WT088134/Z/09/A) and for the purpose of open
access, co-authors have applied a CC BY public copyright
license to any Author Accepted Manuscript version arising
from this submission. The authors would like to thank
the patients that participated in the various cohorts. Open
access funding provided by Universitat Basel.

Authors Contributions

Y.S., A.Z., and N.P. contributed to the conception and
design of the study, acquisition and analysis of data, and
drafting the text or preparing the figures. B.Y., S.F.T.,
V.M., A.P., D.S., G.A., D.W., T.L., S.T., W.C., J.A.,
K.L., J.L., M.S.; M.K., H.C., M.H., D.W., H.M., R.C.,
S.I., K.Y., E.A., S.H., J.P., B.L., A.W., Y.K., T.S., R.L.,
S.E., T.G., E.U., D.D., N.B., E.A., H.H., J.M., M.N.,
J.T., S.C., L.K., R.S., R.J., G.L., M.G., L.P., J.M., L.L.,
C.K., T.P., M.F., F.C., S.M., D.H., D.W., D.D., P.N.,
C.B., S.B., K.W., A.T., D.K., C.Y., A.M., S.K., R.O.,
Y.Z., C.X., S.H., B.G. C.C., M.L., J.S., R.B., N.K., F.L.,
R.S., J.H., P.K., J.W., F.F. V.S., D.C., S.J., V.K., E.S.,
H.H., Y.Y., D.O., F.F., V.T., J.H., R.V., H.A., T.I.,
G.L., E.J., K.T., H.B., J.F., L.P., P.L., J.B., D.W., and
S.E. contributed to the acquisition and analysis of data.

Potential Conflict of Interest

Nothing to report.

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