We investigated the impact of workflow times on the outcomes of patients treated with endovascular thrombectomy (EVT) in the late time window.

Individual patients’ data who underwent EVT in the late time window (onset to imaging >6 hours) were pooled from seven registries and randomized clinical trials. Multiple time intervals were analyzed. Mixed-effects logistic regression was used to estimate the likelihood of functional independence at 90 days (modified Rankin Scale 0–2). Mixed-effects negative binomial regression was used to evaluate the relationship between patient characteristics and workflow time intervals.

608 patients were included. The median age was 70 years (IQR: 58–71), 307 (50.5%) were female, and 310 (53.2%) had wake-up strokes. Successful reperfusion was achieved in 493 (81.2%) patients, and 262 (44.9%) achieved 90-day mRS 0–2. The estimated odds of functional independence decreased by 13% for every 30 minute delay from emergency department (ED) arrival to imaging time and by 7% from ED arrival to the end of EVT in the entire cohort. Also, the estimated odds of functional independence decreased by 33% for every 30 minute delay in the interval from arterial puncture to end of EVT, 16% in the interval from arrival in ED to end of EVT and 6% in the interval from stroke onset to end of EVT among patients who had a wake-up stroke.

Faster workflow from ED arrival to end of EVT is associated with improved functional independence among stroke patients treated in the late window.

Understanding disease-modifying therapy (DMT) use and healthcare resource utilization by different geographical areas among people living with multiple sclerosis (pwMS) may identify care gaps that can be used to inform policies and practice to ensure equitable care.

Administrative data was used to identify pwMS on April 1, 2017 (index date) in Alberta. DMT use and healthcare resource utilization were compared between those who resided in various geographical areas over a 2-year post-index period; simple logistic regression was applied.

Among the cohort (n = 12,338), a higher proportion of pwMS who resided in urban areas (versus rural) received ≥ 1 DMT dispensation (32.3% versus 27.4%), had a neurologist (67.7% versus 63.9%), non-neurologist specialist (88.3% versus 82.9%), ambulatory care visit (87.4% versus 85.3%), and MS tertiary clinic visit (59.2% versus 51.7%), and a lower proportion had an emergency department (ED) visit (46.3% versus 62.4%), and hospitalization (20.4% versus 23.0%). Across the provincial health zones, there were variations in DMT selection, and a higher proportion of pwMS who resided in the Calgary health zone, where care is managed by MS tertiary clinic neurologists, had an outpatient visit to a neurologist or MS tertiary clinic versus those who resided in other zones where delivery of MS-related care is more varied.

Urban/rural inequalities in DMT use and healthcare resource utilization appear to exist among pwMS in Alberta. Findings suggest the exploration of barriers with consequent strategies to increase access to DMTs and provide timely outpatient MS care management, particularly for those pwMS residing in rural areas.

Identifying a patient’s dominant language hemisphere is an important evaluation performed prior to epilepsy surgery and is commonly assessed using functional magnetic resonance imaging (fMRI). However, the lack of standardization and resultant heterogeneity of fMRI paradigms used in clinical practice limits the ability of cross-center comparisons to be made regarding language laterality results.

Through surveying Canadian Epilepsy Centres in combination with reviewing supporting literature, current fMRI language lateralization practices for the clinical evaluation of patients with epilepsy were assessed. To encourage standardization of this practice, we outlined a two-part paradigm series that demonstrates widespread acceptance, reliability and accessibility in lateralizing various aspects of language functioning in individuals with average or near-average IQ and normal literacy skills.

The collected data confirm a lack of standardization in fMRI laterality assessments leading to clinical heterogeneity in stimulation and control tasks, paradigm design and timing, laterality index calculations, thresholding values and analysis software and technique. We suggest a Sentence Completion (SC) and Word Generation (WG) paradigm series as it was most commonly employed across Canada, demonstrated reliability in lateralizing both receptive and expressive language areas in supporting literature, and could be readily intelligible to an inclusive population.

Through providing recommendations for a two-part paradigm series, we hope to contribute to the standardization of this practice across Canada to reduce clinical heterogeneity, encourage communicability between institutions, and enhance methodologies for the surgical treatment of epilepsy for the benefit of all individuals living with epilepsy in Canada.

To examine the association of co-morbidity with home-time after acute stroke and whether the association is influenced by age.

We conducted a province-wide study using linked administrative databases to identify all admissions for first acute ischemic stroke or intracerebral hemorrhage between 2007 and 2018 in Alberta, Canada. We used ischemic stroke-weighted Charlson Co-morbidity Index of 3 or more to identify those with severe co-morbidity. We used zero-inflated negative binomial models to determine the association of severe co-morbidity with 90-day and 1-year home-time, and logistic models for achieving ≥ 80 out of 90 days of home-time, assessing for effect modification by age and adjusting for sex, stroke type, comprehensive stroke center care, hypertension, atrial fibrillation, year of study, and separately adjusting for estimated stroke severity. We also evaluated individual co-morbidities.

Among 28,672 patients in our final cohort, severe co-morbidity was present in 27.7% and was associated with lower home-time, with a greater number of days lost at younger age (−13 days at age < 60 compared to −7 days at age 80+ years for 90-day home-time; −69 days at age < 60 compared to −51 days at age 80+ years for 1-year home-time). The reduction in probability of achieving ≥ 80 days of home-time was also greater at younger age (−22.7% at age < 60 years compared to −9.0% at age 80+ years). Results were attenuated but remained significant after adjusting for estimated stroke severity and excluding those who died. Myocardial infarction, diabetes, and cancer/metastases had a greater association with lower home-time at younger age, and those with dementia had the greatest reduction in home time.

Severe co-morbidity in acute stroke is associated with lower home-time, more strongly at younger age.

Depressive symptoms are common in stroke survivors. While obesity has been associated with stroke and depression, its influence on the association between stroke and depressive symptoms is unknown.

Cross-sectional data from 2015 to 2016 Canadian Community Health Survey was used. History of stroke was self-reported and our outcome of interest was depressive symptoms in the prior 2 weeks, measured using the 9-item Patient Health Questionnaire. Self-reported body mass index (BMI) was modeled as cubic spline terms to allow for nonlinear associations. We used multivariable logistic regression to evaluate the association between stroke and depressive symptoms and added an interaction term to evaluate the modifying effect of BMI.

Of the 47,521 participants, 694 (1.0%) had a stroke and 3314 (6.5%) had depressive symptoms. Those with stroke had a higher odds of depressive symptoms than those without (aOR = 3.13, 95% CI 2.48, 3.93). BMI did not modify the stroke-depressive symptoms association (P interaction = 0.242) despite the observed variation in stroke-depressive symptoms association across BMI categories,: normal BMI [18.5–25 kg/m2] (aOR† = 3.91, 95% CI 2.45, 6.11), overweight [25–30 kg/m2] (aOR† = 2.63, 95% CI 1.58, 4.20), and obese [>30 kg/m2] (aOR† = 2.76, 95% CI 1.92, 3.94). Similar results were found when depressive symptoms were modeled as a continuous measure.

The association between stroke and depressive symptoms is not modified by BMI, needing additional work to understand the role of obesity on depression after stroke.

Limited evidence exists regarding care pathways for stroke survivors who do and do not receive poststroke spasticity (PSS) treatment.

Administrative data was used to identify adults who experienced a stroke and sought acute care between 2012 and 2017 in Alberta, Canada. Pathways of stroke care within the health care system were determined among those who initiated PSS treatment (PSS treatment group: outpatient pharmacy dispensation of an anti-spastic medication, focal chemo-denervation injection, or a spasticity tertiary clinic visit) and those who did not (non-PSS treatment group). Time from the stroke event until spasticity treatment initiation, and setting where treatment was initiated were reported. Descriptive statistics were performed.

Health care settings within the pathways of stroke care that the PSS (n = 1,079) and non-PSS (n = 22,922) treatment groups encountered were the emergency department (86 and 84%), acute inpatient care (80 and 69%), inpatient rehabilitation (40 and 12%), and long-term care (19 and 13%), respectively. PSS treatment was initiated a median of 291 (interquartile range 625) days after the stroke event, and most often in the community when patients were residing at home (45%), followed by “other” settings (22%), inpatient rehabilitation (18%), long-term care (11%), and acute inpatient care (4%).

To our knowledge, this is the first population based cohort study describing pathways of care among adults with stroke who subsequently did or did not initiate spasticity treatment. Areas for improvement in care may include strategies for earlier identification and treatment of PSS.

Contrast-induced encephalopathy (CIE) is an adverse event associated with diagnostic and therapeutic endovascular procedures. Decades of animal and human research support a mechanistic role for pathological blood-brain barrier dysfunction (BBBd). Here, we describe an institutional case series and review the literature supporting a mechanistic role for BBBd in CIE.

A literature review was conducted by searching MEDLINE, Web of Science, Embase, CINAHL and Cochrane databases from inception to January 31, 2022. We searched our institutional neurovascular database for cases of CIE following endovascular treatment of cerebrovascular disease during a 6-month period. Informed consent was obtained in all cases.

Review of the literature revealed risk factors for BBBd and CIE, including microvascular disease, pathological neuroinflammation, severe procedural hypertension, iodinated contrast load and altered cerebral blood flow dynamics. In our institutional series, 6 of 52 (11.5%) of patients undergoing therapeutic neuroendovascular procedures developed CIE during the study period. Four patients were treated for ischemic stroke and two patients for recurrent cerebral aneurysms. Mechanical stenting or thrombectomy were utilized in all cases.

In this institutional case series and literature review of animal and human data, we identified numerous shared risk factors for CIE and BBBd, including microvascular disease, increased procedure length, large contrast volumes, severe intraoperative hypertension and use of mechanical devices that may induce iatrogenic endothelial injury.

Stroke outcomes research requires risk-adjustment for stroke severity, but this measure is often unavailable. The Passive Surveillance Stroke SeVerity (PaSSV) score is an administrative data-based stroke severity measure that was developed in Ontario, Canada. We assessed the geographical and temporal external validity of PaSSV in British Columbia (BC), Nova Scotia (NS) and Ontario, Canada.

We used linked administrative data in each province to identify adult patients with ischemic stroke or intracerebral hemorrhage between 2014-2019 and calculated their PaSSV score. We used Cox proportional hazards models to evaluate the association between the PaSSV score and the hazard of death over 30 days and the cause-specific hazard of admission to long-term care over 365 days. We assessed the models’ discriminative values using Uno’s c-statistic, comparing models with versus without PaSSV.

We included 86,142 patients (n = 18,387 in BC, n = 65,082 in Ontario, n = 2,673 in NS). The mean and median PaSSV were similar across provinces. A higher PaSSV score, representing lower stroke severity, was associated with a lower hazard of death (hazard ratio and 95% confidence intervals 0.70 [0.68, 0.71] in BC, 0.69 [0.68, 0.69] in Ontario, 0.72 [0.68, 0.75] in NS) and admission to long-term care (0.77 [0.76, 0.79] in BC, 0.84 [0.83, 0.85] in Ontario, 0.86 [0.79, 0.93] in NS). Including PaSSV in the multivariable models increased the c-statistics compared to models without this variable.

PaSSV has geographical and temporal validity, making it useful for risk-adjustment in stroke outcomes research, including in multi-jurisdiction analyses.

Prognosticating outcomes for traumatic brain injury (TBI) patients is challenging due to the required specialized skills and variability among clinicians. Recent attempts to standardize TBI prognosis have leveraged machine learning (ML) methodologies. This study evaluates the necessity and influence of ML-assisted TBI prognostication through healthcare professionals’ perspectives via focus group discussions.

Two virtual focus groups included ten key TBI care stakeholders (one neurosurgeon, two emergency clinicians, one internist, two radiologists, one registered nurse, two researchers in ML and healthcare and one patient representative). They answered six open-ended questions about their perceptions and potential ML use in TBI prognostication. Transcribed focus group discussions were thematically analyzed using qualitative data analysis software.

The study captured diverse perceptions and interests in TBI prognostication across clinical specialties. Notably, certain clinicians who currently do not prognosticate expressed an interest in doing so independently provided they had access to ML support. Concerns included ML’s accuracy and the need for proficient ML researchers in clinical settings. The consensus suggested using ML as a secondary consultation tool and promoting collaboration with internal or external research resources. Participants believed ML prognostication could enhance disposition planning and standardize care regardless of clinician expertise or injury severity. There was no evidence of perceived bias or interference during the discussions.

Our findings revealed an overall positive attitude toward ML-based prognostication. Despite raising multiple concerns, the focus group discussions were particularly valuable in underscoring the potential of ML in democratizing and standardizing TBI prognosis practices.