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.

Mucolipidosis type IV (MLIV) is a rare, progressive lysosomal storage disorder characterized by severe intellectual disability, delayed motor milestones and ophthalmologic abnormalities. MLIV is an autosomal recessive disease caused by mutations in the MCOLN1 gene, encoding mucolipin-1 which is responsible for maintaining lysosomal function.

Here, we report a family of four Iranian siblings with cognitive decline, progressive visual and pyramidal disturbances, and abnormal movements manifested by severe oromandibular dystonia and parkinsonism. MRI scans of the brain demonstrated signal abnormalities in the white matter and thinning of the corpus callosum.

Whole-exome sequencing identified a novel homozygous variant, c.362C > T:p. Thr121Met in the MCOLN1 gene consistent with a diagnosis of MLIV. The presentation of MLIV may overlap with a variety of other neurological diseases, and genetic analysis is an important strategy to clarify the diagnosis. This is an important point that clinicians should be familiar with. The novel variant c.362C > T:p. Thr121Met herein described may be related to a comparatively older age at onset. Our study also expands the clinical spectrum of MLIV associated with the MCOLN1 variants and introduces a novel likely pathogenic variant for testing in MLIV cases that remain unresolved.

Spinal muscular atrophy (SMA) is a progressive genetic disorder characterized by muscle weakness ultimately leading to pulmonary impairments that can be fatal. The recent approval of nusinersen, a disease-modifying therapy, substantially changed the prognosis for patients, particularly in children. However, real-world evidence about its long-term effectiveness in adults remains limited. This study aimed to document longitudinal data on motor function, pulmonary function and patient-reported outcome measures of Canadian adults with SMA type 2 and 3 treated with nusinersen.

Outcomes from 17 patients were collected at the Institut de réadaptation en déficience physique de Québec during routine clinical visits over 36 months post nusinersen treatment, using the Hammersmith Functional Motor Scale Expanded for SMA (HFMSE), Revised Upper Limb Module (RULM), 6-Minute Walk Test (6MWT), Children’s Hospital of Philadelphia Adult Test of Neuromuscular Disorders (CHOP-ATEND), SMA functional rating scale (SMAFRS), pulmonary function testing and subjective changes reported by patients.

After 36 months, 9 patients showed motor function improvement. Changes beyond the minimal clinically important difference were seen for four patients on the HFMSE, four patients on the RULM and five patients on the 6MWT. Pulmonary function remained stable for most subjects. Subjective positive changes were reported in 88% of patients and five patients showed improvement in the SMAFRS.

This real-world study demonstrates the positive effects of nusinersen in adults with SMA types 2 and 3. Although stabilizing the patient’s condition is considered therapeutic success, this study shows an improvement in motor function and subjective gains in several patients.

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.

We aimed to evaluate the effect of yoga on motor and non-motor symptoms and cortical excitability in patients with Parkinson’s disease (PD).

We prospectively evaluated 17 patients with PD at baseline, after one month of conventional care, and after one month of supervised yoga sessions. The motor and non-motor symptoms were evaluated using the Unified Parkinson’s disease Rating Scale (motor part III), Hoehn and Yahr stage, Montreal Cognitive Assessment, Hamilton depression rating scale, Hamilton anxiety rating scale, non-motor symptoms questionnaire and World Health Organization quality of life questionnaire. Transcranial magnetic stimulation was used to record resting motor threshold, central motor conduction time, ipsilateral silent period (iSP), contralateral silent period (cSP), short interval intracortical inhibition (SICI), and intracortical facilitation.

The mean age of the patients was 55.5 ± 10.8 years, with a mean duration of illness of 4.0 ± 2.5 years. The postural stability of the patients significantly improved following yoga (0.59 ± 0.5 to 0.18 ± 0.4, p = 0.039). There was a significant reduction in the cSP from baseline (138.07 ± 27.5 ms) to 4 weeks of yoga therapy (116.94 ± 18.2 ms, p = 0.004). In addition, a significant reduction in SICI was observed after four weeks of yoga therapy (0.22 ± 0.10) to (0.46 ± 0.23), p = 0.004).

Yoga intervention can significantly improve postural stability in patients with PD. A significant reduction of cSP and SICI suggests a reduction in GABAergic neurotransmission following yoga therapy that may underlie the improvement observed in postural stability.

CTRI/2019/02/017564

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.

Epidemiological studies on the association between migraine and Alzheimer’s disease (AD) risk have yielded inconsistent conclusions. We aimed to characterize the phenotypic and genetic relationships between migraine and AD.

To investigate the association between migraine and the risk of AD by analyzing data from a large sample of 404,318 individuals who were initially free from all-cause dementia or cognitive impairment, utilizing the UK Biobank dataset. We employed Cox regression modeling and propensity score matching techniques to examine the relationship between migraine and subsequent occurrences of AD. Additionally, the study utilized Mendelian randomization (MR) analysis to identify the genetic relationship between migraine and the risk of AD.

Migraine patients had a significantly increased risk of developing AD, compared to non-migraine patients (adjusted hazard ratio (HR) = 2.34, 95% confidence interval (CI) = 2.01–0.74, P < 0.001). Moreover, the propensity scores matching analyses found that migraine patients had a significantly higher risk of developing AD compared to non-migraine patients (HR = 1.85, 95%CI = 1,68–2.05, P < 0.001). Additionally, the MR suggested that significant causal effects of migraine on AD risks were observed [odds ratio (OR) = 2.315; 95% confidence interval (CI) = 1.029–5.234; P = 0.002]. Moreover, no evidence supported the causal effects of AD on migraine (OR = 1.000; 95%CI = 0.999–1.006; P = 0.971).

The present study concludes that migraine patients, compared to a matched control group, exhibit an increased risk of developing AD. Moreover, migraine patients exhibit an increased predisposition of genetic susceptibility to AD. These findings hold significant clinical value for early intervention and treatment of migraines to reduce the risk of AD.

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.