Publications by authors named "Tuladhar A"

Background: Patients with ischemic stroke at a young age (18-50 years) have an increased long-term risk of recurrent ischemic events. Hypercoagulability may contribute to this high risk.

Objectives: To investigate the associations between in vivo and ex vivo hemostatic parameters and recurrent ischemic events after an ischemic stroke or transient ischemic attack (TIA) at a young age.

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Introduction: Reduced white matter integrity outside the stroke lesion may be a potential contributor of post-stroke cognitive impairment. We aimed to investigate how a stroke lesion affects the integrity of surrounding white matter, and whether the integrity of the non-lesioned part of white matter tracts is associated with cognitive performance after ischemic stroke in young adults.

Methods: Patients from the ODYSSEY study, aged 18-49 years, with a first-ever ischemic stroke, underwent 3T MRI and cognitive assessment within six months after the index event.

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  • Cerebral small vessel disease (SVD) can lead to various cerebrovascular issues, but research on sex differences in SVD is limited.
  • This study analyzed data from over 20,000 patients with acute ischemic stroke to examine whether the presence and severity of cerebral microbleeds (CMB) and other SVD markers differ between males and females.
  • Results showed that males had more frequent CMB while females had fewer lacunes but higher severe white matter hyperintensities, indicating distinct SVD characteristics based on sex.
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  • Previous research hinted at differences in cerebellar white matter integrity related to stages of Parkinson's disease (PD), but the progression of these changes over time was not well understood.
  • The study involved 124 patients with PD, who underwent multiple MRI scans to track microstructural integrity in cerebellar white matter, focusing on the connections between the cerebellum and other brain areas, while assessing clinical symptoms and dopamine levels.
  • Results showed a non-linear pattern in cerebellar white matter changes, highlighting an initial increase in integrity followed by a decline, which mirrored declines in dopamine levels and clinical symptoms, suggesting adaptive changes in the brain as PD progresses.
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  • High mechanical loading induces temporary disruptions in cell membranes (PMD) that initiate a process called mechanotransduction, which is essential for bone adaptation.
  • The study hypothesized that disrupting a protein called β2-spectrin (Sptbn1), which supports cell structure, would increase membrane fragility, leading to altered responses in osteocytes (bone cells) under mechanical stress.
  • Results showed that disrupting Sptbn1 led to more PMD formation and slower repair rates in cells, impaired cell survival, and reduced bone thickening in response to mechanical loading, highlighting Sptbn1's crucial role in bone adaptation and cell response to stress.
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Objectives: SARS-CoV-2 infection is associated with a decline in functional outcomes; many patients experience persistent symptoms, while the underlying pathophysiology remains unclear. This study investigated white matter (WM) integrity on brain MRI in hospitalized COVID-19 patients and its associations with clinical outcomes, including long COVID.

Materials And Methods: We included hospitalized COVID-19 patients and controls from CORONavirus and Ischemic Stroke (CORONIS), an observational cohort study, who underwent MRI-DWI imaging at baseline shortly after discharge (<3 months after positive PCR) and 3 months after baseline scanning.

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  • The study investigates the long-term mortality risk in patients with small vessel disease (SVD), focusing on MRI markers over a 16-year follow-up to understand their impact on life expectancy.
  • Out of 503 participants, 39.9% died during the study period, with specific MRI findings like increased white matter hyperintensity and decreased brain volume linked to higher mortality rates.
  • The research reveals that both baseline MRI markers and changes over time in brain volume are significant predictors of all-cause mortality in SVD patients, highlighting the necessity for further exploration of these connections.
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Background: Atrial fibrillation (AF) is the most common heart arrhythmia worldwide and is linked to a higher risk of mortality and morbidity. To predict AF and AF-related complications, clinical risk scores are commonly employed, but their predictive accuracy is generally limited, given the inherent complexity and heterogeneity of patients with AF. By classifying different presentations of AF into coherent and manageable clinical phenotypes, the development of tailored prevention and treatment strategies can be facilitated.

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  • Cerebral small vessel disease is a leading cause of vascular dementia, and diffusion tensor imaging (DTI) is more effective at detecting white matter damage than traditional MRI methods, though it's less accessible.
  • Researchers created a deep learning model to generate synthetic maps of fractional anisotropy (FA) and mean diffusivity (MD) from standard T1 MRI scans, using data from nearly 5,000 participants and additional validation datasets.
  • The generated synthetic FA/MD maps closely matched actual brain scans and were nearly as accurate in predicting dementia risk, providing a faster alternative for clinical settings where DTI isn’t available.
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  • Cognitive impairment is prevalent in young cerebellar stroke patients, with about 60% experiencing deficits, especially in visuo-spatial skills and executive functioning.
  • The study found mixed outcomes over time, with some patients showing improvement while others experienced cognitive decline, regardless of recurrence of strokes.
  • Subjective cognitive complaints were high and correlated with levels of fatigue, indicating a significant impact on the patients' overall cognitive health and quality of life.
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  • This study aimed to evaluate the prevalence of cerebrovascular MRI markers in patients hospitalized for COVID-19 compared to healthy controls without prior COVID-19 infection or hospitalization.
  • Conducted as an observational cohort study, it involved brain MRIs done shortly after discharge and again after three months, focusing on various cerebrovascular issues.
  • The results showed no significant difference in cerebrovascular MRI markers between COVID-19 patients and controls, with only a small percentage experiencing new cerebrovascular lesions after three months, suggesting limited impact of COVID-19 on these markers.
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We and others have seen that osteocytes sense high-impact osteogenic mechanical loading via transient plasma membrane disruptions (PMDs) which initiate downstream mechanotransduction. However, a PMD must be repaired for the cell to survive this wounding event. Previous work suggested that the protein Prkd1 (also known as PKCμ) may be a critical component of this PMD repair process, but the specific role of Prkd1 in osteocyte mechanobiology had not yet been tested.

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Cerebral small vessel disease (SVD) is known to contribute to cognitive impairment, apathy and gait dysfunction. Although associations between cognitive impairment and either apathy or gait dysfunction have been shown in SVD, the inter-relations among these three clinical features and their potential common neural basis remain unexplored. The dopaminergic meso-cortical and meso-limbic pathways have been known as the important brain circuits for both cognitive control, emotion regulation and motor function.

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Background: Patients with sporadic cerebral amyloid angiopathy (sCAA) frequently report cognitive or neuropsychiatric symptoms. The aim of this study is to investigate whether in patients with sCAA, cognitive impairment and neuropsychiatric symptoms are associated with a cerebrospinal fluid (CSF) biomarker profile associated with Alzheimer's disease (AD).

Methods: In this cross-sectional study, we included participants with sCAA and dementia- and stroke-free, age- and sex-matched controls, who underwent a lumbar puncture, brain MRI, cognitive assessments, and self-administered and informant-based-questionnaires on neuropsychiatric symptoms.

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Background And Objectives: Previous studies have linked the MRI measures of perivascular spaces (PVSs), diffusivity along the perivascular spaces (DTI-ALPS), and free water (FW) to cerebral small vessel disease (SVD) and SVD-related cognitive impairments. However, studies on the longitudinal associations between the three MRI measures, SVD progression, and cognitive decline are lacking. This study aimed to explore how PVS, DTI-ALPS, and FW contribute to SVD progression and cognitive decline.

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Background: Patent foramen ovale (PFO) is a congenital anatomical variant which is associated with strokes in young adults. Contrary to vascular risk factors and atherosclerosis, a PFO is present from birth. However, it is completely unknown how an anatomical structure that is already present at birth in a large proportion of the population can convert into a PFO that causes stroke in a few.

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There is evidence that blood pressure variability (BPV) is associated with cerebral small vessel disease (SVD) and may therefore increase the risk of stroke and dementia. It remains unclear if BPV is associated with SVD progression over years. We examined whether visit-to-visit BPV is associated with white matter hyperintensity (WMH) progression over 14 years and MRI markers after 14 years.

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Introduction: The INflammation and Small Vessel Disease (INSVD) study aims to investigate whether peripheral inflammation, immune (dys)regulation and blood-brain barrier (BBB) permeability relate to disease progression in cerebral small vessel disease (SVD). This research aims to pinpoint specific components of the immune response in SVD relating to disease progression. This could identify biomarkers of SVD progression, as well as potential therapeutic targets to inform the development and repurposing of drugs to reduce or prevent SVD, cognitive decline and vascular dementia.

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Background And Objectives: Patients with cerebral small vessel disease (SVD) show a heterogenous clinical course. The aim of the current study was to investigate the longitudinal course of cognitive and motor function in patients who developed parkinsonism, dementia, both, or none.

Methods: Participants were from the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort study, a prospective cohort of patients with SVD.

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Importance: Cause of ischemic stroke in young people is highly variable; however, the risk of recurrence is often presented with all subtypes of stroke grouped together in classification systems such as the Trial of ORG (danaparoid sodium [Orgaran]) 10172 in Acute Stroke Treatment (TOAST) criteria, which limits the ability to individually inform young patients with stroke about their risk of recurrence.

Objective: To determine the short-term and long-term risk of recurrent vascular events after ischemic stroke at a young age by stroke cause and to identify factors associated with recurrence.

Design, Setting, And Participants: This cohort study used data from the Observational Dutch Young Symptomatic Stroke Study, a prospective, multicenter, hospital-based cohort study, conducted at 17 hospitals in the Netherlands between 2013 and 2021.

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Background: Limited data exists on cognitive recovery in young stroke patients. We aimed to investigate the longitudinal course of cognitive performance during the first year after stroke at young age and identify predictors for cognitive recovery.

Methods: We conducted a multicentre prospective cohort study between 2013 and 2021, enrolling patients aged 18-49 years with first-ever ischaemic stroke.

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Approximately 1 in 10 young stroke patients (18-50 years) will develop post-stroke epilepsy, which is associated with cognitive impairment. While previous studies have shown altered brain connectivity in patients with epilepsy, little is however known about the changes in functional brain connectivity in young stroke patients with post-stroke epilepsy and their relationship with cognitive impairment. Therefore, we aimed to investigate whether young ischaemic stroke patients have altered functional networks and whether this alteration is related to cognitive impairment.

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Background: Cerebral small vessel disease (SVD) contributes to 45% of dementia cases worldwide, yet we lack a reliable model for predicting dementia in SVD. Past attempts largely relied on traditional statistical approaches. Here, we investigated whether machine learning (ML) methods improved prediction of incident dementia in SVD from baseline SVD-related features over traditional statistical methods.

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