Brain Frailty and Outcomes of Acute Minor Ischemic Stroke With Large-Vessel Occlusion

- ^aDepartment of Neurology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Korea.
- ^bClinical Research Center, Asan Institute for Life Sciences, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
- ^cDepartment of Neurology, Cerebrovascular Center, Seoul National University Bundang Hospital, Seongnam, Korea.
- ^dDepartment of Neurology, Yongin Severance Hospital, Yongin, Korea.
- ^eDepartment of Neurology, Korea University Guro Hospital, Seoul, Korea.
- ^fDepartment of Neurology, Asan Medical Center, Seoul, Korea.
- ^gDepartment of Neurology, Daejeon Eulji Medical Center, Eulji University School of Medicine, Daejeon, Korea.
- ^hDepartment of Radiology, Seoul National University Bundang Hospital, Seongnam, Korea.
- ⁱDepartment of Neurology, Uijeongbu Eulji Medical Center, Eulji University School of Medicine, Uijeongbu, Korea.
- ^jDepartment of Neurology, Nowon Eulji Medical Center, Eulji University School of Medicine, Seoul, Korea.
- ^kDepartment of Neurology, Keimyung University Dongsan Medical Center, Keimyung University School of Medicine, Daegu, Korea.
- ^lDepartment of Neurology, Dong-A University Hospital, Busan, Korea.
- ^mDepartment of Neurology, Seoul Medical Center, Seoul, Korea.
- ⁿDepartment of Neurology, Soonchunhyang University Seoul Hospital, Soonchunhyang University College of Medicine, Seoul, Korea.
- ^oDepartment of Neurology, Yeungnam University Medical Center, Daegu, Korea.
- ^pDepartment of Neurology, Inje University Ilsan Paik Hospital, Goyang, Korea.
- ^qDepartment of Neurology, Hallym University Sacred Heart Hospital, Anyang, Korea.
- ^rDepartment of Neurology, Dongguk University Ilsan Hospital, Goyang, Korea.
- ^sDepartment of Neurology, Jeju National University Hospital, Jeju National University School of Medicine, Jeju, Korea.
- ^tDepartment of Neurology, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Korea.
- ^uDepartment of Neurology, Chungbuk National University Hospital, Cheongju, Korea.
- ^vDepartment of Neurology, Hallym University Chuncheon Sacred Heart Hospital, Chuncheon, Korea.
- ^wArtificial Intelligence Research Center, JLK Inc., Seoul, Korea.
- ^xDepartment of Biostatistics, Korea University, Seoul, Korea.
Correspondence: Joon-Tae Kim, MD, PhD. Department of Neurology, Chonnam National University Hospital, Chonnam National University Medical School, 42 Jebong-ro, Dong-gu, Gwangju 61469, Korea. Tel +82-62-220-6180, Fax +82-62-228-3461, Email: alldelight2@jnu.ac.kr

Correspondence: Beom Joon Kim, MD, PhD. Department of Neurology, Cerebrovascular Center, Seoul National University Bundang Hospital, 82 Gumi-ro 173beon-gil, Bundang-gu, Seongnam 13620, Korea. Tel +82-31-787-7467, Fax +82-31-787-4059, Email: kim.bj.stroke@gmail.com

Received May 19, 2023; Revised June 30, 2023; Accepted July 04, 2023.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background and Purpose

The influence of imaging features of brain frailty on outcomes were investigated in acute ischemic stroke patients with minor symptoms and large-vessel occlusion (LVO).

Methods

This was a retrospective analysis of a prospective, multicenter, nationwide registry of consecutive patients with acute (within 24 h) minor (National Institutes of Health Stroke Scale score=0–5) ischemic stroke with anterior circulation LVO (acute minor LVO). Brain frailty was stratified according to the presence of an advanced white-matter hyperintensity (WMH) (Fazekas grade 2 or 3), silent/old brain infarct, or cerebral microbleeds. The primary outcome was a composite of stroke, myocardial infarction, and all-cause mortality within 1 year.

Results

In total, 1,067 patients (age=67.2±13.1 years [mean±SD], 61.3% males) were analyzed. The proportions of patients according to the numbers of brain frailty burdens were as follows: no burden in 49.2%, one burden in 30.0%, two burdens in 17.3%, and three burdens in 3.5%. In the Cox proportional-hazards analysis, the presence of more brain frailty burdens was associated with a higher risk of 1-year primary outcomes, but after adjusting for clinically relevant variables there were no significant associations between burdens of brain frailty and 1-year vascular outcomes. For individual components of brain frailty, an advanced WMH was independently associated with an increased risk of 1-year primary outcomes (adjusted hazard ratio [aHR]=1.33, 95% confidence interval [CI]=1.03–1.71) and stroke (aHR=1.32, 95% CI=1.00–1.75).

Conclusions

The baseline imaging markers of brain frailty were common in acute minor ischemic stroke patients with LVO. An advanced WMH was the only frailty marker associated with an increased risk of vascular events. Further research is needed into the association between brain frailty and prognosis in patients with acute minor LVO.

Graphical Abstract

Keywords

brain frailty; white-matter hyperintensity; acute ischemic stroke; large-vessel occlusion; acute minor stroke

INTRODUCTION

A substantial proportion of patients with acute minor ischemic stroke and large-vessel occlusion (acute minor LVO) neurologically deteriorate during the acute periods and experience unfavorable outcomes.1 Further research is therefore warranted into the factors related to worse outcomes in patients with acute minor LVO.

Baseline imaging features of small-vessel disease (SVD) and brain frailty are commonly associated with worse outcomes after acute stroke, particularly in the small-vessel stroke subtype.2 Imaging markers of brain frailty including white-matter hyperintensities (WMHs), cerebral atrophy, and silent brain infarct (SBI) are shared with markers of SVD, including WMHs, microbleeds (MBs), prominent perivascular spaces, cerebral atrophy, and lacunes, all of which are linked to poor outcomes.3, 4 Although individual imaging features of SVD or brain frailty (except WMH) might not be directly related to the overall prognosis, combined features representing global brain health, such as the SVD score or brain frailty score, have been linked to outcomes,5, 6 mainly in the small-vessel stroke subtype.2, 7 Impairment of functional connectivity might partly account for poor outcomes, especially in the small-vessel stroke subtype.

However, there have been conflicting findings for whether imaging features of SVD (including WMH) are associated with an increased risk of poor outcomes in LVO strokes treated with or without endovascular thrombectomy.8, 9 LVO stroke differs from small-vessel stroke in its clinical presentation, risk factors, and outcomes.10 Nonetheless, the total burden of SVD has predictive value for stroke recurrence in stroke patients with the large-artery atherosclerosis subtype.11 Determining how the imaging features of brain frailty or SVD influence outcomes may help to identify useful therapeutic strategies for the specific stroke populations of acute minor LVO.

This study therefore investigated whether the 1-year vascular outcomes of patients with acute minor LVO were associated with individual and combined imaging markers of brain frailty or SVD, including WMH, SBI, and MB.

METHODS

Subjects

This study performed a post-hoc analysis of an imaging registry for acute minor LVO that was derived from the Clinical Research Center for Stroke–Korea (CRCS-K) registry. The CRCS-K registry is a prospective, multicenter, nationwide registry of consecutive patients with acute stroke or transient ischemic attack (TIA) admitted to 17 academic hospitals in South Korea. Detailed methodology information about the CRCS-K registry and the acute minor LVO registry has been reported previously.12, 13, 14 We identified patients with acute ischemic stroke admitted between January 2015 and March 2019. We included patients who 1) presented within 24 h after the last known time when they were well (n=24,596), 2) had a baseline National Institutes of Health Stroke Scale (NIHSS) score of 0 to 5 points (n=15,436), 3) had anterior circulation LVO (ICA, or M1 or proximal M2 segment of the MCA) confirmed by neuroimaging (n=1,083), and 4) underwent imaging analysis of brain frailty (n=1,067). A detailed patient selection flowchart is shown in Supplementary Fig. 1 (in the online-only Data Supplement).

Ethics statement

Clinical information was collected from the CRCS-K registry and the acute minor LVO registry with approval from the local institutional review boards of all participating centers. A waiver of the need to obtain informed consents was provided because the study subjects were anonymous and there was minimal risk to the participants. The secondary use of the registry data and additional reviews of the medical records and imaging data by this study were approved by the Institutional Review Boards (IRB No. CNUH-2023-243). The data used in this study are available upon reasonable request following the submission of a legitimate academic research proposal, which would be assessed by the CRCS-K steering committee.

Data collection

Demographic, clinical, and laboratory data were collected prospectively, as detailed in the Supplementary Methods (in the online-only Data Supplement). The ischemic stroke subtypes were classified according to the Trial of Org 10172 in Acute Stroke Treatment (TOAST) criteria, which were refined to incorporate additional information from more-recent imaging studies.15

All neuroimaging data were collected retrospectively and independently evaluated by a central imaging laboratory. The details of the imaging analysis method are available elsewhere14 and in the Supplemental Methods. In briefly, the images were assessed for the Alberta Stroke Program Emergent CT Score (ASPECTS), location of cerebral artery occlusion, tandem occlusion, WMH (Fazekas grade), SBI, and MB. An advanced WMH was defined as Fazekas grade 2 or 3. Brain frailty was stratified according to the presence of an advanced WMH (grade 2 or 3), SBI, or cerebral MB.2 These three findings were summed to generate a score for the burden of brain frailty or SVD (we described this as the brain frailty burden for this study), which ranged from 0 to 3.

The central imaging laboratory consisted of vascular neurologists (J.H.H., B.J.K., B.J.K., C.K.K., and J.T.K.), interventional neurologists (J.G.K., H.P., and J.S.Y.), and an interventional radiologist (S.H.B.). All images were independently evaluated by at least two raters. Any discrepancy in the readings between the raters was adjudicated by a panel (B.J.K., J.S.Y., and S.H.B.) to reach the final assessment. Details on the collection, anonymization, storage, and backing-up of images as well as on the image reading process are available elsewhere.14

Outcomes

To explore several hypotheses from previous studies, the outcomes of interest were in two domains: 1) 1-year vascular events and 2) early functional outcomes at 3 months. The primary outcome for vascular events was a composite of stroke (either ischemic or hemorrhagic), myocardial infarction (MI), and all-cause mortality within 1 year. Stroke events included neurological progression associated with enlarged or discrete new lesions during the acute period. The secondary outcomes were individual outcomes except for MI due to a low event rate: 1) stroke and 2) all-cause mortality. Detailed definitions of the vascular outcome events and the methods used for outcome capture in the current study are available elsewhere.12

The main functional outcome was no or minimal disability at 3 months, defined as a modified Rankin Scale (mRS) score of 0 or 1. The secondary outcomes were functional independence at 3 months (mRS score=0–2), hemorrhagic transformation (HT), and parenchymal hematoma (PH).

Statistical analysis

The baseline characteristics and outcomes were compared according to the brain frailty burdens using the chi-square test, ANOVA, or Kruskal–Wallis test as appropriate. The event probabilities of 1-year vascular outcomes according to the total number of brain frailty burdens and each brain frailty were calculated using the Kaplan–Meier method, and the log-rank test was performed to analyze the differences among the groups. Hazard ratios (HRs) and 95% confidence intervals (CIs) of 1-year vascular outcomes were analyzed using the Cox proportional-hazards model. We tested the proportional-hazards assumption using the numerical method proposed by Lin et al.16 derived from cumulative sums of Martingale residuals. Adjustments were made for the following predetermined variables with clinically relevant associations with the outcome variables: age, sex, initial NIHSS score, arrival delay, TOAST stroke subtype, history of stroke, history of coronary artery disease, hypertension (HTN), diabetes mellitus (DM), atrial fibrillation, dyslipidemia, artery occlusion, glucose, and systolic blood pressure. Interactions among WMH, SBI, and MB were evaluated using the Wald test in a Cox model.

A logistic regression model was used to explore the relationships of each brain frailty and the total number of brain frailty burdens with the functional outcomes at 3 months (mRS score=0 or 1, mRS score=0–2, HT, and PH). Estimates of the effect size are provided as adjusted odds ratio (aOR) and 95% CI values.

Statistical analyses were performed with R software using the “rms” package (version 3.6.0, R Foundation for Statistical Computing, Vienna, Austria) and SAS software (version 9.4, SAS Institute, Cary, NC, USA).

RESULTS

General characteristics

Among the 24,596 patients with stroke or TIA registered in the CRCS-K database during the study period, 1,067 patients (age=67.2±13.1 years [mean±SD], 61.3% males) were finally included. The median baseline NIHSS score was 2 (interquartile range [IQR]=1–4). The proportion of patients with different numbers of brain frailty burdens were as follows: no burden in 49.2%, one burden in 30.0%, two burdens in 17.3%, and three burdens in 3.5%. Patients with more brain frailty burdens were more likely to have HTN, DM, and a history of stroke, while patients without a brain frailty burden were younger (Table 1). The imaging findings of the subjects and the characteristics of the individual and combined features of brain frailty are presented in Supplementary Tables 1 and 2 (in the online-only Data Supplement). An advanced WMH (grade 2 or 3), MB, and SBI were observed in 28.6%, 11.1%, and 35.4% of the patients, respectively.

Table 1
General characteristics of the subjects according to the number of brain frailty burdens

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One-year vascular outcomes

The median follow-up duration was 365 days (IQR=355–374 days, 342±93 days), with 91% of the patients completing the 1-year follow-up. The primary composite outcome of stroke, MI, and all-cause mortality occurred in 315 patients, and the 1-year cumulative event rate was 30.2%. For individual components of the composite outcome, the 1-year event rates were 26.2% for stroke, 0.7% for MI, and 6.9% for all-cause mortality. Early progressive/recurrent stroke during hospitalization occurred in 226 patients (21.2%).

In the crude analysis, the primary outcome events at 1 year occurred in 49.5%, 35.8%, 31.9%, and 25.8% of the patients with three, two, one, and no burden, respectively (p value in log-rank test=0.006). The rate of all-cause mortality was lowest in the no-burden group (4.4%) and highest in the three-burdens group (11.4%) (p value in log-rank test=0.014). Table 2 lists the 1-year event rates according to the individual components and burdens of brain frailty. The 1-year rates of primary outcomes, stroke, and all-cause mortality differed significantly according to the presence of an advanced WMH and the WMH severity.

Table 2
One-year event rates according to brain frailty

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In the Cox proportional-hazards analysis, a larger number of brain frailty burdens (compared with no burden) was associated with 1-year primary outcomes, all-cause mortality, and stroke. However, there was no longer a significant association between brain frailty burdens and 1-year vascular outcomes after adjusting for clinically relevant variables (Table 3). Regarding the individual components of brain frailty, an advanced WMH (grade 2 or 3) was independently associated with an increased risk of 1-year primary outcomes (adjusted HR [aHR]=1.33, 95% CI=1.03–1.71) and stroke (aHR=1.32, 95% CI=1.00–1.75). Compared with no WMH, more-severe WMH was associated with higher risks of 1-year primary outcomes (mild WMH: aHR=1.43, 95% CI=0.97–2.10; moderate WMH: aHR=1.68, 95% CI=1.07–2.62; and severe WMH: aHR=2.32, 95% CI=1.38–3.90) and stroke (mild WMH: aHR=1.53, 95% CI=1.02–2.30; moderate WMH: aHR=1.79, 95% CI=1.11–2.88; and severe WMH: aHR=2.42, 95% CI=1.38–4.25).

Table 3
Associations of brain frailty with 1-year primary outcomes

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The associations of the different components of brain frailty with 1-year vascular outcomes are presented in Table 3. Kaplan–Meier curves of event-free survival for 1-year primary outcomes according to brain frailty burdens and the presence of individual brain frailty components in brain MRI are shown in Figs. 1 and 2. Additionally, Kaplan–Meier curves of event-free survival for individual vascular outcomes within 1 year are shown in Supplementary Fig. 2 (for brain frailty burden), Supplementary Table 3, Supplementary Fig. 3 (for all-cause mortality), and Supplementary Table 4, Supplementary Fig. 4 (for stroke) in the online-only Data Supplement.

Fig. 1
Kaplan–Meier curves of event-free survival for 1-year primary outcomes according to the number of brain frailty burdens. MI, myocardial infarction.

Fig. 2
Kaplan–Meier curves of event-free survival for 1-year primary outcomes according to WMH severity (A) and the presence of advanced WMH (B), silent brain infarct (C) and cerebral microbleed (D) on MRI. WMH, white-matter hyperintensity.

Three-month functional outcomes

Three months of mRS scores were available for 1,056 patients, among whom 569 (53.9%) had excellent outcomes (no or minimal disability; mRS score=0 or 1) at 3 months. Excellent outcomes at 3 months were significantly more common in the patients with fewer brain frailty burdens (no burden, 62.8%; one burden, 50.2%; two burdens, 6.6%; and three burdens, 44.4%, p<0.001). The frequency of a good outcome at 3 months (functional independence; mRS score=0–2) also differed significantly according to brain frailty burdens (Supplementary Table 5 in the online-only Data Supplement). However, the prevalence rates of HT and PH did not differ significantly with the number of brain frailty burdens. The 3-month functional outcomes according to the imaging markers of brain frailty are presented in Supplementary Table 6 (in the online-only Data Supplement).

The associations of the 3-month functional outcomes with brain frailty burdens are presented in Supplementary Tables 7 and 8 (in the online-only Data Supplement). In the crude analysis, the brain frailty burdens and the presence of individual brain frailty were significantly associated with a lower probability of excellent and good outcomes at 3 months. After adjusting for clinically relevant variables, the only individual components of brain frailty that were independently associated with functional outcomes at 3 months were the severity of WMH and the presence of advanced WMH (mRS score=0 or 1: aOR=0.70, 95% CI=0.52–0.96; mRS score=0–2: aOR=0.74, 95% CI=0.53–1.02).

DISCUSSION

The present analysis of 1,067 patients with acute minor ischemic stroke with LVO revealed that baseline imaging markers of brain frailty were common but not significantly associated with increased risks of 1-year vascular outcomes and worse functional outcomes at 3 months. However, an advanced WMH (one of the imaging features of brain frailty) was significantly associated with higher risks of 1-year primary vascular outcomes and 3-month worse functional outcomes.

We observed imaging features of brain frailty in approximately half of the patients with acute minor ischemic stroke with LVO. Multiple imaging features of brain frailty were observed in one of every five patients with acute minor LVO. Although this study did not analyze all imaging markers for SVD and brain frailty, the MRI markers of MB, WMH, and SBI that were used in our study are clinically practical because they can be objectively assessed visually.

The present results are consistent with previous reports that SVD burdens can co-occur with LVO stroke17 and that there is a potential link between LVO stroke and SVD burdens in terms of risk factors and pathogenesis.18 While MRI markers such as WMH, SBI, and MB are often associated with small vascular events in the brain, it must be remembered that they can also have other causes.19, 20 Additionally, SVD is commonly attributed to factors such as longstanding HTN, DM, and aging. Hence, brain frailty may arise as a consequence of these underlying conditions rather than being a predictive factor for stroke prognosis. Further research is necessary to characterize this relationship in more detail.

We also found that the number of brain frailty burdens was consistently correlated with the risk of recurrent vascular events for up to 1 year, increasing from 25.8% with no burden to 49.5% with three burdens. Although being statistically not significant, the unadjusted event rates of vascular outcomes numerically increased with the number of brain frailty burdens in our study. A WMH was the imaging frailty marker that contributed the most to the differences in vascular outcomes. It is well known that WMHs are very common in elderly individuals, implying higher morbidity and severity of the related diseases.21, 22 A WMH might be an imaging marker of disruption to the white-matter fiber tracts and/or network architecture of the brain, and widespread changes in white-matter tissue microstructure may result in unfavorable outcomes partially due to impaired brain plasticity.23, 24 Moreover, a WMH may represent advanced impairment of the microvasculature of the brain and increase the risk of ischemic stroke recurrence.

Additionally, patients with more brain frailty burdens seemed to be less likely to have good outcomes at 3 months. More brain frailty burdens, and especially advanced WMHs, represent worse global brain health rather than merely a collection of individual brain lesions, and these patients could be vulnerable to ischemic insult due to impaired autoregulation and compensatory collateral flows.25, 26 Our results are consistent with previous findings of increased brain frailty features or SVD burdens being related to increased risks of recurrent stroke and worse functional outcomes at 3 months.2, 27

Most ischemic stroke patients present with minor symptoms and are generally considered to have a favorable long-term outcome.28 In the CRCS-K registry, outcomes after 3 months were good (mRS score=0–2) in 74.4% of an overall stroke population13 and in 71.5% of those with acute minor LVO.14 However, a substantial number of patients with acute minor LVO showed neurologically deterioration during the early periods after stroke and had unfavorable outcomes.1 We found that among patients with acute minor LVO, those with more brain frailty burdens (especially an advanced WMH) are at a higher risk and potentially frail, which could lead to more subsequent vascular events and unfavorable functional outcomes. Further studies are warranted to determine whether the additional factors affecting the risk of worse outcomes are useful in decision-making for such patients.

This study had several limitations. First, certain imaging markers of brain frailty and SVD were not comprehensively assessed, such as prominent perivascular spaces, cerebral atrophy, and lacunes. Although it would be ideal to analyze all markers of brain frailty, this study considered only three imaging markers because they could be visually assessed in actual clinical settings, which is practically useful for determining their clinical significance. This study did not consider the burden and location of cerebral MB, and did not incorporate the recently published Boston criteria for cerebral amyloid angiopathy,29 since the focus was specifically on patients with acute minor ischemic stroke with LVO. Therefore, the findings might not reflect the impact of these criteria. The study also did not consider the location of SBI and WMHs (deep or periventricular). The lack of a significant association between brain frailty burdens and outcomes may have been due to our sample being statistically underpowered. Further studies with larger samples are therefore warranted. Second, restricting the study population to those with acute minor LVO may have introduced a particular type of selection bias known as collider stratification bias. This can distort the relationship of baseline risk factors with the outcome of interest. Third, the rate of stroke events within 1 year was substantially higher than in previous stroke studies. Because this study included patients with acute minor ischemic stroke with LVO, early progressive or recurrent stroke events were included as stroke events. Additionally, the participating hospitals were tertiary (university) hospitals or regional stroke centers (e.g., comprehensive stroke centers). Fourth, this study had inherent limitations associated with its registry-based retrospective design. Although rigorous adjusting for clinically relevant variables was used to mitigate the baseline differences, the possibility of unmeasured or residual confounding cannot be excluded. Fifth, although this was a large, prospective, nationwide study, the patient cohort was restricted to an Asian population (South Korea), and so studies involving other racial and ethnic groups are needed to confirm the generalizability of the present results.

In conclusion, imaging markers of brain frailty were common among the included acute minor ischemic stroke patients with LVO. In particular, advanced WMHs were significantly associated with higher risks of 1-year vascular outcomes and 3-month worse functional outcomes. These results might necessitate a more-vigilant approach for mild LVO patients with advanced WMHs; this possibly needs to be elucidated in future studies.

Supplementary Materials

The online-only Data Supplement is available with this article at https://doi.org/10.3988/jcn.2023.0181.

Supplemental Methods

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Supplementary Table 1

Imaging characteristics of the subjects

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Supplementary Table 2

General characteristics of the subjects according to individual imaging markers of brain frailty (WMH, old infarcts, and cerebral microbleeds)

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Supplementary Table 3

Associations of brain frailty with 1-year all-cause mortality

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Supplementary Table 4

Associations of brain frailty with 1-year stroke

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Supplementary Table 5

Three-month functional outcomes according to the burden of brain frailty (n=1,067)

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Supplementary Table 6

Three-month functional outcomes according to the imaging markers of brain frailty

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Supplementary Table 7

Associations of brain frailty with 3-month excellent outcome (mRS 0–1)

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Supplementary Table 8

Associations of brain frailty with 3-month good outcome (mRS 0–2)

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Supplementary Fig. 1

Study flow chart. CRCS-K, Clinical Research Center for Stroke–Korea; NIHSS, National Institutes of Health Stroke Scale; TIA, transient ischemic attack.

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Supplementary Fig. 2

Kaplan–Meier curve of event-free survival for 1-year all-cause mortality (A) and stroke (B) according to the burden of brain frailty.

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Supplementary Fig. 3

Kaplan–Meier curves of event-free survival for 1-year all-cause mortality according to the presence of old infarcts (A), WMH (B), advanced WMH (C) and microbleeds (D) on MRI. WMH, white-matter hyperintensity.

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Supplementary Fig. 4

Kaplan–Meier curves of event-free survival for 1-year stroke according to the presence of old infarcts (A), WMH (B), advanced WMH (C) and microbleeds (D) on MRI. WMH, white-matter hyperintensity.

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Notes

Author Contributions:

Conceptualization: Je-Woo Park, Joon-Tae Kim.
Data curation: Joon-Tae Kim, Ji Sung Lee, Beom Joon Kim.
Formal analysis: Ji Sung Lee, Joon-Tae Kim.
Funding acquisition: Joon-Tae Kim, Hee-Joon Bae.
Investigation: all authors.
Methodology: Joon-Tae Kim, Ji Sung Lee, Beom Joon Kim.
Writing—original draft: Je-Woo Park, Joon-Tae Kim.
Writing—review & editing: all authors.

Conflicts of Interest:The authors have no potential conflicts of interest to disclose.

Funding Statement:This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute, funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI22C0454). This research was supported by funding (2023-ER1006-00) from Research of Korea Centers for Disease Control and Prevention. This study was supported by a grant (BCRI22032) of Chonnam National University Hospital Biomedical Research Institute.

Availability of Data and Material

The datasets generated or analyzed during the study are available from the corresponding author on reasonable request.

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