Prediction of stroke severity: systematic evaluation of lesion representations.

OBJECTIVE: To systematically evaluate which lesion-based imaging features and methods allow for the best statistical prediction of poststroke deficits across independent datasets. METHODS: We utilized imaging and clinical data from three independent datasets of patients experiencing acute stroke (N1 = 109, N2 = 638, N3 = 794) to statistically predict acute stroke severity (NIHSS) based on lesion volume, lesion location, and structural and functional disconnection with the lesion location using normative connectomes. RESULTS: We found that prediction models trained on small single-center datasets could perform well using within-dataset cross-validation, but results did not generalize to independent datasets (median R2 N1 = 0.2%). Performance across independent datasets improved using large single-center training data (R2 N2 = 15.8%) and improved further using multicenter training data (R2 N3 = 24.4%). These results were consistent across lesion attributes and prediction models. Including either structural or functional disconnection in the models outperformed prediction based on volume or location alone (P < 0.001, FDR-corrected). INTERPRETATION: We conclude that (1) prediction performance in independent datasets of patients with acute stroke cannot be inferred from cross-validated results within a dataset, as performance results obtained via these two methods differed consistently, (2) prediction performance can be improved by training on large and, importantly, multicenter datasets, and (3) structural and functional disconnection allow for improved prediction of acute stroke severity.

Quantifying brain health in acute ischemic stroke through effective reserve.

Objective: To quantify brain health using a measure of reserve that incorporates pre-existing pathology. Methods: We analyzed two retrospective ischemic stroke cohorts (GASROS and SALVO) with neuroimaging and 90-day modified Rankin Scores (mRS) available. White matter hyperintensity (WMHv), brain, and intracranial volumes were automatically extracted, and brain parenchymal fraction (BPF) calculated. The latent variable effective reserve (eR) was modeled using age, WMHv, and BPF or brain volume in GASROS. Models were compared using Bayes Information Criterion (BIC). The best model's eR estimates were categorized into quartiles and evaluated in SALVO. Results: GASROS included 476 (median age: 65.8; 65.3% male) and SALVO included 43 (median age: 69.2; 62.8% male) patients. Inverse associations between eR and mRS was seen in both models, with brain volume outperforming BPF (path coefficients: -0.67, -0.48, respectively; p < 0.001; |ΔBIC| = 362). Quartile-based eR stratification in SALVO showed a similar inverse trend, with worse outcomes in the low reserve group (mRS≤2 - highest vs lowest quartile: 85/90% vs 59/45% for GASROS/SALVO). Conclusions: Expanding the concept of eR, highlights its clinical translational potential. The strong link between higher eR and better outcomes underscores its value as a protective brain health metric.

Impact and determinants of door in-door out time for stroke thrombectomy transfers in a large hub-and-spoke network.

INTRODUCTION: The mantra "time is brain" cannot be overstated for patients suffering from acute ischemic stroke. This is especially true for those with large vessel occlusions (LVOs) requiring transfer to an endovascular thrombectomy (EVT) capable center. We sought to evaluate the spoke hospital door in-door out (DIDO) times for patients transferred to our hub center for EVT. METHODS: Individuals who first presented with LVO to a spoke hospital and were then transferred to the hub for EVT were retrospectively identified from a prospectively maintained database from January 2019 to November 2022. DIDO was defined as the time between spoke hospital door in arrival and door out exit. Baseline characteristics, treatments, and outcomes were compared, dichotomizing DIDO at 90 minutes based in the American Heart Association goal for DIDO ≤90 minutes for 50% of transfers. Multivariable regression analyses were performed for determinants of the 90-day ordinal modified Rankin Scale (mRS) and DIDO. RESULTS: We identified 194 patients transferred for EVT with available DIDO. The median age was 67 years (IQR 57-80), and 46% were female. The median National Institutes of Health Stroke Scale (NIHSS) was 16 (10-20), 50% were treated with intravenous thrombolysis at a spoke, and TICI 2B-3 reperfusion was achieved in 87% at the hub. The median DIDO was 120 minutes (97-149), with DIDO ≤90 minutes achieved in 18%. DIDO was a significant determinant of 90-day ordinal mRS (B = 0.007, 95% CI = 0.001-0.012, p = 0.013), even when accounting for the last known well-to-spoke door in, spoke door out-to-hub arrival, hub arrival-to-puncture, puncture-to-first pass, age, NIHSS, intravenous thrombolysis, TICI 2B-3, and symptomatic intracranial hemorrhage. Importantly, determinants of DIDO included Black race or Hispanic ethnicity (B = 0.918, 95% CI = 0.010-1.826, p = 0.048), atrial fibrillation or heart failure (B = 0.793, 95% CI = 0.257-1.329, p = 0.004), and basilar LVO location (B = 2.528, 95% CI = 1.154-3.901, p < 0.001). CONCLUSION: Spoke DIDO was the most important period of time for long-term outcomes of LVO stroke patients treated with EVT. Targets were identified to reduce DIDO and improve patient outcomes.

Brain volume is a better biomarker of outcomes in ischemic stroke compared to brain atrophy.

Brain parenchymal fraction (BPF) has been used as a surrogate measure of global brain atrophy, and as a biomarker of brain reserve in studies evaluating clinical outcomes after brain injury. Total brain volume at the time of injury has recently been shown to influence functional outcomes, where larger brain volumes are associated with better outcomes. Here, we assess if brain volume at the time of ischemic stroke injury is a better biomarker of functional outcome than BPF. Acute ischemic stroke cases at a single center between 2003 and 2011, with MR neuroimaging obtained within 48 hours from presentation were eligible. Functional outcomes represented by the modified Rankin Score (mRS) at 90 days post admission (mRS<3 deemed a favorable outcome) were obtained via patient interview or per chart review. Deep learning enabled automated segmentation pipelines were used to calculate brain volume, intracranial volume (ICV), and BPF on the acute neuroimaging data. Patient outcomes were modeled through logistic regressions, and model comparison was conducted using the Bayes Information Criterion (BIC). 467 patients with arterial ischemic stroke were included in the analysis. Median age was 65.8 years, and 65.3% were male. In both models, age and a larger stroke lesion volume were associated with worse functional outcomes. Higher BPF and a larger brain volume were both associated with favorable functional outcomes, however, comparison of both models suggested that the brain volume model (BIC=501) explains the data better compared to the BPF model (BIC=511). The extent of global brain atrophy has been regarded as an important biomarker of post-stroke functional outcomes and resilience to acute injury. Here, we demonstrate that a higher global brain volume at the time of injury better explains favorable functional outcomes, which can be directly clinically assessed.

Cerebral microbleeds and risk of symptomatic hemorrhagic transformation following mechanical thrombectomy for large vessel ischemic stroke.

BACKGROUND AND PURPOSE: In patients with acute ischemic stroke (AIS) treated with endovascular therapy (EVT), the association of pre-existing cerebral small vessel disease (cSVD) with symptomatic intracerebral hemorrhage (sICH) remains controversial. We tested the hypothesis that the presence of cerebral microbleeds (CMBs) and their burden would be associated with sICH after EVT of AIS. METHODS: We conducted a retrospective study combining cohorts of patients that underwent EVT between January 1st 2015 and January 1st 2020. CMB presence, burden, and other cSVD markers were assessed on a pre-treatment MRI, evaluated independently by two observers. Primary outcome was the occurrence of sICH. RESULTS: 445 patients with pretreatment MRI were included, of which 70 (15.7%) demonstrated CMBs on baseline MRI. sICH occurred in 36 (7.6%) of all patients. Univariate analysis did not demonstrate an association between CMB and the occurrence of sICH (7.5% in CMB+ group vs 8.6% in CMB group, p = 0.805). In multivariable models, CMBs' presence was not significantly associated with increased odds for sICH (-aOR- 1.19; 95% CI [0.43-3.27], p = 0.73). Only ASPECTs (aOR 0.71 per point increase; 95% CI [0.60-0.85], p < 0.001) and collaterals status (aOR 0.22 for adequate versus poor collaterals; 95% CI [0.06-0.93], p 0.019) were independently associated with sICH. CONCLUSION: CMB presence and burden is not associated with increased occurrence of sICH after EVT. This result incites not to exclude patients with CMBs from EVT. The risk of sICH after EVT in patients with more than10 CMBs will require further investigation. REGISTRATION: Registration-URL: http://www. CLINICALTRIALS: gov ; Unique identifier: NCT01062698.

Characterizing coma in large vessel occlusion stroke.

BACKGROUND: Coma is an unresponsive state of disordered consciousness characterized by impaired arousal and awareness. The epidemiology and pathophysiology of coma in ischemic stroke has been underexplored. We sought to characterize the incidence and clinical features of coma as a presentation of large vessel occlusion (LVO) stroke. METHODS: Individuals who presented with LVO were retrospectively identified from July 2018 to December 2020. Coma was defined as an unresponsive state of impaired arousal and awareness, operationalized as a score of 3 on NIHSS item 1a. RESULTS: 28/637 (4.4%) patients with LVO stroke were identified as presenting with coma. The median NIHSS was 32 (IQR 29-34) for those with coma versus 11 (5-18) for those without (p < 0.0001). In coma, occlusion locations included basilar (13), vertebral (2), internal carotid (5), and middle cerebral (9) arteries. 8/28 were treated with endovascular thrombectomy (EVT), and 20/28 died during the admission. 65% of patients not treated with EVT had delayed presentations or large established infarcts. In models accounting for pre-stroke mRS, basilar occlusion location, intravenous thrombolysis, and EVT, coma independently increased the odds of transitioning to comfort care during admission (aOR 6.75; 95% CI 2.87,15.84; p < 0.001) and decreased the odds of 90-day mRS 0-2 (aOR 0.12; 95% CI 0.03,0.55; p = 0.007). CONCLUSIONS: It is not uncommon for patients with LVO to present with coma, and delayed recognition of LVO can lead to poor outcomes, emphasizing the need for maintaining a high index of suspicion. While more commonly thought to result from posterior LVO, coma in our cohort was similarly likely to result from anterior LVO. Efforts to improve early diagnosis and care of patients with LVO presenting with coma are crucial.

Scaling behaviours of deep learning and linear algorithms for the prediction of stroke severity.

Deep learning has allowed for remarkable progress in many medical scenarios. Deep learning prediction models often require 105-107 examples. It is currently unknown whether deep learning can also enhance predictions of symptoms post-stroke in real-world samples of stroke patients that are often several magnitudes smaller. Such stroke outcome predictions however could be particularly instrumental in guiding acute clinical and rehabilitation care decisions. We here compared the capacities of classically used linear and novel deep learning algorithms in their prediction of stroke severity. Our analyses relied on a total of 1430 patients assembled from the MRI-Genetics Interface Exploration collaboration and a Massachusetts General Hospital-based study. The outcome of interest was National Institutes of Health Stroke Scale-based stroke severity in the acute phase after ischaemic stroke onset, which we predict by means of MRI-derived lesion location. We automatically derived lesion segmentations from diffusion-weighted clinical MRI scans, performed spatial normalization and included a principal component analysis step, retaining 95% of the variance of the original data. We then repeatedly separated a train, validation and test set to investigate the effects of sample size; we subsampled the train set to 100, 300 and 900 and trained the algorithms to predict the stroke severity score for each sample size with regularized linear regression and an eight-layered neural network. We selected hyperparameters on the validation set. We evaluated model performance based on the explained variance (R2) in the test set. While linear regression performed significantly better for a sample size of 100 patients, deep learning started to significantly outperform linear regression when trained on 900 patients. Average prediction performance improved by ∼20% when increasing the sample size 9× [maximum for 100 patients: 0.279 ± 0.005 (R2, 95% confidence interval), 900 patients: 0.337 ± 0.006]. In summary, for sample sizes of 900 patients, deep learning showed a higher prediction performance than typically employed linear methods. These findings suggest the existence of non-linear relationships between lesion location and stroke severity that can be utilized for an improved prediction performance for larger sample sizes.

Informed consent practices for acute stroke therapy: principles, challenges and emerging opportunities.

IMPORTANCE: Informed consent (IC) plays a crucial yet underexplored role in acute stroke treatment, particularly in the context of intravenous thrombolysis (IVT) and endovascular thrombectomy (EVT). This narrative review examines data on current IC practices in acute ischemic stroke management, specifically for patients treated with IVT or EVT, with the aim of identifying areas for improvement and strategies to enhance the IC process. OBSERVATIONS: IC practices for IVT vary significantly among hospitals and physicians with the frequency of always requiring consent ranging from 21 to 37%. Factors influencing IC for IVT include patient decision-making capacity, standard of care, time sensitive nature of treatments, legal and moral obligations, risk of complications, physician age and speciality, treatment delays, and hospital size. Consent requirements tend to be stricter for patients presenting within the 3-4.5-h window. The content and style of information shared as part of the IC process revealed discrepancies in the disclosure of stroke diagnosis, IVT mechanism, benefits, and risks. Research on IC practices for EVT is scarce, highlighting a concerning gap in the available evidence base. CONCLUSIONS AND RELEVANCE: This review underscores the significant variability and knowledge gaps in IC for EVT and IVT. Challenges related to decision-making capacity assessment and the absence of standardised guidance substantially contributes to these gaps. Future initiatives should focus on simplifying information delivery to patients, developing formal tools for assessing capacity, standardising ethical frameworks to guide physicians when patients lack capacity and harmonizing IC standards across sites. The ultimate goal is to enhance IC practices and uphold patient autonomy, while ensuring timely treatment initiation.

The Brain Health Imperative in the 21st Century-A Call to Action: The AAN Brain Health Platform and Position Statement.

Brain health is crucial to optimizing both the function and well-being of every person at each stage of life and is key to both individual and social progress. As a concept, brain health is complex and requires a multidisciplinary collaborative approach between many professional and public organizations to bring into effect meaningful change. Neurologists are uniquely positioned to serve as specialists in brain health and to advance the newly evolving field of preventive neurology, which aims to identify individuals at high risk of brain disorders and other neurologic conditions and offer strategies to mitigate disease emergence or progression. For decades, the American Academy of Neurology (AAN) has demonstrated a commitment to brain health through its public outreach and advocacy. The AAN's Brain Health Initiative launched in 2022 with a strategic plan prioritizing brain health as a key aspect of public engagement and positioning the AAN and neurologists as champions of brain health in collaboration with a broad range of other brain health providers. In this study, we present (1) the new definition of brain health developed by the AAN for neurologists, patients, partners in health care, and the public; (2) the strategic objectives of the AAN Brain Health Initiative; and (3) the AAN Brain Health Platform and Action Plan framework, including key positions on brain health, its 3 ambitious goals, and a national brain health vision. The top-line priorities of the AAN Brain Health Action Plan highlight the need for research, education, public policy, and direct-to-public messaging across the individual's life span and will serve as a catalyst for future cross-disciplinary collaborations within each epoch and longitudinally. The AAN Brain Health Platform is designed to communicate the AAN's vision for brain health and provide a blueprint toward achieving the future of optimal brain health across the life span for all. Through this position statement, we call upon neurologists and other stakeholders in brain health to join our collective efforts to accomplish the ultimate goal of transforming the current trajectory of public health of an increasing burden of neurologic disorders-from both illness and injury-to achieving optimal brain health for all.

Management of Inherited CNS Small Vessel Diseases: The CADASIL Example: A Scientific Statement From the American Heart Association.

Lacunar infarcts and vascular dementia are important phenotypic characteristics of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, the most common inherited cerebral small vessel disease. Individuals with the disease show variability in the nature and onset of symptoms and rates of progression, which are only partially explained by differences in pathogenic mutations in the NOTCH3 gene. Recognizing the disease early in its course and securing a molecular diagnosis are important clinical goals, despite the lack of proven disease-modifying treatments. The purposes of this scientific statement are to review the clinical, genetic, and imaging aspects of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, contrasting it with other inherited small vessel diseases, and to provide key prevention, management, and therapeutic considerations with the intent of reducing practice variability and encouraging production of high-quality evidence to support future treatment recommendations.

Mapping Lesion-Related Epilepsy to a Human Brain Network.

Importance: It remains unclear why lesions in some locations cause epilepsy while others do not. Identifying the brain regions or networks associated with epilepsy by mapping these lesions could inform prognosis and guide interventions. Objective: To assess whether lesion locations associated with epilepsy map to specific brain regions and networks. Design, Setting, and Participants: This case-control study used lesion location and lesion network mapping to identify the brain regions and networks associated with epilepsy in a discovery data set of patients with poststroke epilepsy and control patients with stroke. Patients with stroke lesions and epilepsy (n = 76) or no epilepsy (n = 625) were included. Generalizability to other lesion types was assessed using 4 independent cohorts as validation data sets. The total numbers of patients across all datasets (both discovery and validation datasets) were 347 with epilepsy and 1126 without. Therapeutic relevance was assessed using deep brain stimulation sites that improve seizure control. Data were analyzed from September 2018 through December 2022. All shared patient data were analyzed and included; no patients were excluded. Main Outcomes and Measures: Epilepsy or no epilepsy. Results: Lesion locations from 76 patients with poststroke epilepsy (39 [51%] male; mean [SD] age, 61.0 [14.6] years; mean [SD] follow-up, 6.7 [2.0] years) and 625 control patients with stroke (366 [59%] male; mean [SD] age, 62.0 [14.1] years; follow-up range, 3-12 months) were included in the discovery data set. Lesions associated with epilepsy occurred in multiple heterogenous locations spanning different lobes and vascular territories. However, these same lesion locations were part of a specific brain network defined by functional connectivity to the basal ganglia and cerebellum. Findings were validated in 4 independent cohorts including 772 patients with brain lesions (271 [35%] with epilepsy; 515 [67%] male; median [IQR] age, 60 [50-70] years; follow-up range, 3-35 years). Lesion connectivity to this brain network was associated with increased risk of epilepsy after stroke (odds ratio [OR], 2.82; 95% CI, 2.02-4.10; P < .001) and across different lesion types (OR, 2.85; 95% CI, 2.23-3.69; P < .001). Deep brain stimulation site connectivity to this same network was associated with improved seizure control (r, 0.63; P < .001) in 30 patients with drug-resistant epilepsy (21 [70%] male; median [IQR] age, 39 [32-46] years; median [IQR] follow-up, 24 [16-30] months). Conclusions and Relevance: The findings in this study indicate that lesion-related epilepsy mapped to a human brain network, which could help identify patients at risk of epilepsy after a brain lesion and guide brain stimulation therapies.

Spatial-Intensity Transforms for Medical Image-to-Image Translation.

Image-to-image translation has seen major advances in computer vision but can be difficult to apply to medical images, where imaging artifacts and data scarcity degrade the performance of conditional generative adversarial networks. We develop the spatial-intensity transform (SIT) to improve output image quality while closely matching the target domain. SIT constrains the generator to a smooth spatial transform (diffeomorphism) composed with sparse intensity changes. SIT is a lightweight, modular network component that is effective on various architectures and training schemes. Relative to unconstrained baselines, this technique significantly improves image fidelity, and our models generalize robustly to different scanners. Additionally, SIT provides a disentangled view of anatomical and textural changes for each translation, making it easier to interpret the model's predictions in terms of physiological phenomena. We demonstrate SIT on two tasks: predicting longitudinal brain MRIs in patients with various stages of neurodegeneration, and visualizing changes with age and stroke severity in clinical brain scans of stroke patients. On the first task, our model accurately forecasts brain aging trajectories without supervised training on paired scans. On the second task, it captures associations between ventricle expansion and aging, as well as between white matter hyperintensities and stroke severity. As conditional generative models become increasingly versatile tools for visualization and forecasting, our approach demonstrates a simple and powerful technique for improving robustness, which is critical for translation to clinical settings. Source code is available at github.com/clintonjwang/spatial-intensity-transforms.

The role of population-level preventive care for brain health in ageing.

Over the past several decades, a worldwide demographic transition has led to an increasing number of older adults with chronic neurological conditions. These conditions, which have a profound effect on the cognitive function and physical ability of older adults, also have a long preclinical phase. This feature provides a unique opportunity to implement preventive measures for high-risk groups and the population as a whole, and therefore to reduce the burden of neurological diseases. The concept of brain health has emerged as the overarching theme to define overall brain function independently of underlying pathophysiological processes. We review the concept of brain health from the ageing and preventive care perspectives, discuss the mechanisms underpinning ageing and brain ageing, highlight the interplay of various forces resulting in deviation from brain health towards brain disease, and provide an overview of strategies to promote brain health with a life-course approach.

Neuroimaging standards for research into small vessel disease-advances since 2013.

Cerebral small vessel disease (SVD) is common during ageing and can present as stroke, cognitive decline, neurobehavioural symptoms, or functional impairment. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive and other symptoms and affect activities of daily living. Standards for Reporting Vascular Changes on Neuroimaging 1 (STRIVE-1) categorised and standardised the diverse features of SVD that are visible on structural MRI. Since then, new information on these established SVD markers and novel MRI sequences and imaging features have emerged. As the effect of combined SVD imaging features becomes clearer, a key role for quantitative imaging biomarkers to determine sub-visible tissue damage, subtle abnormalities visible at high-field strength MRI, and lesion-symptom patterns, is also apparent. Together with rapidly emerging machine learning methods, these metrics can more comprehensively capture the effect of SVD on the brain than the structural MRI features alone and serve as intermediary outcomes in clinical trials and future routine practice. Using a similar approach to that adopted in STRIVE-1, we updated the guidance on neuroimaging of vascular changes in studies of ageing and neurodegeneration to create STRIVE-2.

Cognitive Impairment After Ischemic and Hemorrhagic Stroke: A Scientific Statement From the American Heart Association/American Stroke Association.

PURPOSE: Cognitive impairment is a common consequence of stroke and has direct implications for poststroke functioning and quality of life, including the ability to maintain a job, live independently, sustain interpersonal relationships, and drive a vehicle. In this scientific statement, we critically appraise the literature on the prevalence, diagnosis, and management of poststroke cognitive impairment (PSCI) and provide a framework for clinical care while highlighting gaps that merit further study. METHODS: We performed a scoping literature review of randomized controlled clinical trials, prospective and retrospective cohort studies, case-control studies, clinical guidelines, review articles, and editorials on the incidence and prevalence, natural history, diagnosis, and management of PSCI. Scoping reviews determine the scope of a body of literature on a given topic to indicate the volume of literature and the studies currently available and provide an overview of its focus. RESULTS: PSCI is common after stroke, especially in the first year, and ranges from mild to severe. Although cognitive impairment is reversible in some cases early after stroke, up to one-third of individuals with stroke develop dementia within 5 years. The pathophysiology is not yet fully elucidated but is likely attributable to an acute stroke precipitating a series of pathological events, often in the setting of preexisting microvascular and neurodegenerative changes. Screening for associated comorbidities and interdisciplinary management are integral components of the care of individuals with PSCI. There is a need for prospective studies evaluating the individual trajectory of PSCI and the role of the acute vascular event in the predisposition for Alzheimer disease and related dementias, as well as high-quality, randomized clinical trials focused on PSCI management.

Bayesian stroke modeling details sex biases in the white matter substrates of aphasia.

Ischemic cerebrovascular events often lead to aphasia. Previous work provided hints that such strokes may affect women and men in distinct ways. Women tend to suffer strokes with more disabling language impairment, even if the lesion size is comparable to men. In 1401 patients, we isolate data-led representations of anatomical lesion patterns and hand-tailor a Bayesian analytical solution to carefully model the degree of sex divergence in predicting language outcomes ~3 months after stroke. We locate lesion-outcome effects in the left-dominant language network that highlight the ventral pathway as a core lesion focus across different tests of language performance. We provide detailed evidence for sex-specific brain-behavior associations in the domain-general networks associated with cortico-subcortical pathways, with unique contributions of the fornix in women and cingular fiber bundles in men. Our collective findings suggest diverging white matter substrates in how stroke causes language deficits in women and men. Clinically acknowledging such sex disparities has the potential to improve personalized treatment for stroke patients worldwide.

Spoke-administered thrombolysis improves large vessel occlusion early recanalization: the real-world experience of a large academic hub-and-spoke telestroke network.

Introduction: Intravenous thrombolysis (IVT) prior to mechanical thrombectomy (MT) for large vessel occlusion (LVO) stroke is increasingly controversial. Recent trials support MT without IVT for patients presenting directly to MT-capable "hub" centers. However, bypassing IVT has not been evaluated for patients presenting to IVT-capable "spoke" hospitals that require hub transfer for MT. A perceived lack of efficacy of IVT to result in LVO early recanalization (ER) is often cited to support bypassing IVT, but ER data for IVT in patients that require interhospital transfer is limited. Here we examined LVO ER rates after spoke-administered IVT in our hub-and-spoke stroke network. Methods: Patients presenting to 25 spokes before hub transfer for MT consideration from 2018-2020 were retrospectively identified from a prospectively maintained database. Inclusion criteria were pre-transfer CTA-defined LVO, ASPECTS ≥6, and post-transfer repeat vessel imaging. Results: Of 167 patients, median age was 69 and 51% were female. 76 received spoke IVT (+spokeIVT) and 91 did not (-spokeIVT). Alteplase was the only IVT used in this study. Comorbidities and NIHSS were similar between groups. ER frequency was increased 7.2-fold in +spokeIVT patients [12/76 (15.8%) vs. 2/91 (2.2%), P<0.001]. Spoke-administered IVT was independently associated with ER (aOR=11.5, 95% CI=2.2,99.6, p<0.05) after adjusting for timing of last known well, interhospital transfer, and repeat vessel imaging. Interval NIHSS was improved in patients with ER (median -2 (IQR -6.3, -0.8) vs. 0 (-2.5, 1), p<0.05). Conclusion: Within our network, +spokeIVT patients had a 7.2-fold increased ER relative likelihood. This real-world analysis supports IVT use in eligible patients with LVO at spoke hospitals before hub transfer for MT.

Poststroke Disability: Association Between Sex and Patient-Reported Outcomes.

BACKGROUND: Ischemic stroke (IS) is a leading cause of long-term disability with sex-specific differences in outcomes. Identifying the influential factors that contribute to sex-specific disparities in stroke outcomes, therefore, holds potential to develop individualized interventions for reducing long-term disability. Further, investigating the association between sex and Patient-Reported Outcome Measures (PROMs) provides additional information on the individual impact and heterogeneity of IS. We aimed to identify sex-specific differences in stroke outcomes and relationship with PROMs in IS patients with 3-month follow-up. METHODS: Between February 2017 and February 2020, a total of 410 patients admitted with IS to the Massachusetts General Hospital, in Boston, were enrolled in this prospective cohort. At 3-month poststroke, patients were assessed for Barthel Index, modified Rankin Scale, and PROM-10 questionnaires. T scores for physical and mental health were determined from the summing of PROM-10 responses in each domain. Regression analysis was performed to identify sex-specific determinants of functional and patient-reported outcomes. RESULTS: At baseline, 242 participants were male (mean age, 65 years) and 168 were female (mean age, 70 years). Groups had similar rates of cardiovascular risk factors, admission National Institutes of Health Stroke Scale, and discharge modified Rankin Scale. At follow-up, male participants were more likely to have better rates of T Physical and Barthel Index. In regression analysis, PROMs T Physical (odds ratio, 1.06; P=0.01), Barthel Index (odds ratio, 1.06; P=0.01), and modified Rankin Scale score of ≥2 (odds ratio, 2.60; P=0.01) were associated with female sex. Female sex was also associated with lower scores for PROMs Physical subcomponents and with patient-reported general health and emotional problems. CONCLUSIONS: Women have worse outcomes after ischemic stroke, including objective measures of functional disability and patient-reported outcomes. Incorporating PROMs into IS outcome measures may offer additional insight into sex-specific differences in stroke recovery and outcomes.

In a hub-and-spoke network, spoke-administered thrombolysis reduces mechanical thrombectomy procedure time and number of passes.

BACKGROUND: The utility of intravenous thrombolysis (IVT) prior to mechanical thrombectomy (MT) in large vessel occlusion stroke (LVO) is controversial. Some data suggest IVT increases MT technical difficulty. Within our hub-and-spoke telestroke network, we examined how spoke-administered IVT affected hub MT procedure time and pass number. METHODS: Patients presenting to 25 spoke hospitals who were transferred to the hub and underwent MT from 2018 to 2020 were identified from a prospectively maintained database. MT procedure time, fluoroscopy time, and pass number were obtained from operative reports. RESULTS: Of 107 patients, 48 received IVT at spokes. Baseline characteristics and NIHSS were similar. The last known well (LKW)-to-puncture time was shorter among IVT patients (4.3 ± 1.9 h vs. 10.5 ± 6.5 h, p < 0.0001). In patients that received IVT, mean MT procedure time was decreased by 18.8 min (50.5 ± 29.4 vs. 69.3 ± 46.7 min, p = 0.02) and mean fluoroscopy time was decreased by 11.3 min (21.7 ± 15.8 vs. 33.0 ± 30.9 min, p = 0.03). Furthermore, IVT-treated patients required fewer MT passes (median 1 pass [IQR 1.0, 1.80] vs. 2 passes [1.0, 2.3], p = 0.0002) and were more likely to achieve reperfusion in ≤2 passes (81.3% vs. 59.3%, p = 0.01). An increased proportion of IVT-treated patients achieved TICI 2b-3 reperfusion after MT (93.9% vs. 83.8%, p = 0.045). There were no associations between MT procedural characteristics and LKW-to-puncture time. CONCLUSION: Within our network, hub MT following spoke-administered IVT was faster, required fewer passes, and achieved improved reperfusion. This suggests spoke-administered IVT does not impair MT, but instead may enhance it.