Results 221 to 230 of about 53,219 (293)

Fibrinogen Changes Before and After Intravenous Thrombolysis as Predictors of Cerebral Injury and Clinical Outcomes in Acute Ischemic Stroke: A Multicenter Prospective Cohort Study

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Plasma fibrinogen is essential in thrombosis and fibrinolysis, yet its dynamic changes pre‐ and post‐intravenous thrombolysis (IVT) for predicting brain injury severity and prognosis in acute ischemic stroke (AIS) patients remain unclear.
Wenhai Zhai   +28 more
wiley   +1 more source

Arousal as a universal embedding for spatiotemporal brain dynamics. [PDF]

open access: yesNature
Raut RV   +10 more
europepmc   +1 more source

Changes in Immune‐Inflammation Status and Acute Ischemic Stroke Prognosis in Prospective Cohort

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Inflammation is a critical risk factor for poor outcomes in cerebral infarction. Prior studies focused primarily on baseline inflammation status, neglecting dynamic longitudinal changes. We try to investigate the association between immune‐inflammation status alterations and stroke prognosis, and evaluated three systemic biomarkers'
Songfang Chen   +11 more
wiley   +1 more source

Exploratory Analysis of ELP1 Expression in Whole Blood From Patients With Familial Dysautonomia

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Familial dysautonomia (FD) is a hereditary neurodevelopmental disorder caused by aberrant splicing of the ELP1 gene, leading to a tissue‐specific reduction in ELP1 protein expression. Preclinical models indicate that increasing ELP1 levels can mitigate disease manifestations.
Alejandra González‐Duarte   +13 more
wiley   +1 more source

Prediction of Myasthenia Gravis Worsening: A Machine Learning Algorithm Using Wearables and Patient‐Reported Measures

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Myasthenia gravis (MG) is a rare disorder characterized by fluctuating muscle weakness with potential life‐threatening crises. Timely interventions may be delayed by limited access to care and fragmented documentation. Our objective was to develop predictive algorithms for MG deterioration using multimodal telemedicine data ...
Maike Stein   +7 more
wiley   +1 more source

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