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Therapeutic Effect of Repetitive Transcranial Magnetic Stimulation for Post-stroke Vascular Cognitive Impairment: A Prospective Pilot Study
ConclusionsHigh-frequency rTMS on the ipsilesional DLPFC may exert immediate efficacy on cognition with the anti-inflammatory response and changes in brain network in PSCI, lasting at least 3 months.
Source: Frontiers in Neurology - March 22, 2022 Category: Neurology Source Type: research

Bridging the Transient Intraluminal Stroke Preclinical Model to Clinical Practice: From Improved Surgical Procedures to a Workflow of Functional Tests
Acute ischemic stroke (AIS) remains a leading cause of mortality, despite significant advances in therapy (endovascular thrombectomy). Failure in developing novel effective therapies is associated with unsuccessful translation from preclinical studies to clinical practice, associated to inconsistent and highly variable infarct areas and lack of relevant post-stroke functional evaluation in preclinical research. To outreach these limitations, we optimized the intraluminal transient middle cerebral occlusion, a widely used mouse stroke model, in two key parameters, selection of appropriate occlusion filaments and time of occ...
Source: Frontiers in Neurology - March 11, 2022 Category: Neurology Source Type: research

Deep Learning-Enabled Clinically Applicable CT Planbox for Stroke With High Accuracy and Repeatability
ConclusionsCAPITAL-CT generated standard and reproducible images that could simplify the work of radiologists, which would be of great help in the follow-up of stroke patients and in multifield research in neuroscience.
Source: Frontiers in Neurology - March 11, 2022 Category: Neurology Source Type: research

Computational Approaches for Acute Traumatic Brain Injury Image Recognition
In recent years, there have been major advances in deep learning algorithms for image recognition in traumatic brain injury (TBI). Interest in this area has increased due to the potential for greater objectivity, reduced interpretation times and, ultimately, higher accuracy. Triage algorithms that can re-order radiological reading queues have been developed, using classification to prioritize exams with suspected critical findings. Localization models move a step further to capture more granular information such as the location and, in some cases, size and subtype, of intracranial hematomas that could aid in neurosurgical ...
Source: Frontiers in Neurology - March 9, 2022 Category: Neurology Source Type: research

Neurologic Music Therapy Improves Participation in Children With Severe Cerebral Palsy
This study aimed to quantify improvements in participation, as well as complexity on task-related manual activities in children with severe bilateral CP. This analytic quasi-experimental study exposed 17 children with severe cerebral palsy to 13 NMT sessions to improve motor learning through therapeutic instrumental music performance (TIMP), using principally percussion musical instruments. Hoisan software video recording was used to quantify participation involved in creating music. In addition, the number of active movements performed in each NMT session was quantified. Significant improvements were found in the particip...
Source: Frontiers in Neurology - March 9, 2022 Category: Neurology Source Type: research

Leveraging Factors of Self-Efficacy and Motivation to Optimize Stroke Recovery
The International Classification of Functioning, Disability and Health framework recognizes that an individual's functioning post-stroke reflects an interaction between their health condition and contextual factors encompassing personal and environmental factors. Personal factors significantly impact rehabilitation outcomes as they determine how an individual evaluates their situation and copes with their condition in daily life. A key personal factor is self-efficacy—an individual's belief in their capacity to achieve certain outcomes. Self-efficacy influences an individual's motivational state to execute behaviors nece...
Source: Frontiers in Neurology - February 24, 2022 Category: Neurology Source Type: research

Time Course and Mechanisms Underlying Standing Balance Recovery Early After Stroke: Design of a Prospective Cohort Study With Repeated Measurements
DiscussionThe current study aims to investigate how stroke survivors “re-learn” to maintain standing balance as an integral part of daily life activities. The knowledge gained through this study may contribute to recommending treatment strategies for early stroke rehabilitation targeting behavioral restitution of the most-affected leg or learning to compensate with the less-affected leg.
Source: Frontiers in Neurology - February 21, 2022 Category: Neurology Source Type: research

Effects of Repetitive Peripheral Sensory Stimulation in the Subacute and Chronic Phases After Stroke: Study Protocol for a Pilot Randomized Trial
DiscussionThe results of this study are relevant to inform future clinical trials to tailor RPSS to patients more likely to benefit from this intervention.Trial RegistrationNCT03956407.
Source: Frontiers in Neurology - February 16, 2022 Category: Neurology Source Type: research

Machine Learning Techniques in Blood Pressure Management During the Acute Phase of Ischemic Stroke
ConclusionThis is the first study to address BP management in the acute phase of ischemic stroke using ML techniques. The results indicate that the treatment choice should be adjusted to different clinical and BP parameters, thus, providing a better decision-making approach.
Source: Frontiers in Neurology - February 14, 2022 Category: Neurology Source Type: research

Myoelectric Arm Orthosis in Motor Learning-Based Therapy for Chronic Deficits After Stroke and Traumatic Brain Injury
ConclusionsUse of MyoPro in motor learning-based therapy resulted in clinically significant gains with a relatively short duration of in-person treatment. Further studies are warranted.Clinical Trial Registrationwww.ClinicalTrials.gov, identifier: NCT03215771.
Source: Frontiers in Neurology - February 8, 2022 Category: Neurology Source Type: research

Prediction-Driven Decision Support for Patients With Mild Stroke: A Model Based on Machine Learning Algorithms
Conclusions: DAMS and R-DAMS, as prediction-driven decision support tools, were designed to aid clinical decision-making for mild stroke patients in emergency contexts. In addition, even within a narrow range of baseline scores, NIHSS on admission is the strongest feature that contributed to the prediction.
Source: Frontiers in Neurology - December 23, 2021 Category: Neurology Source Type: research

The Construction of a Risk Prediction Model Based on Neural Network for Pre-operative Acute Ischemic Stroke in Acute Type A Aortic Dissection Patients
Conclusion: The established risk prediction model based on the deep neural network method may have the big potential to evaluate the risk of pre-operative AIS in patients with ATAAD.
Source: Frontiers in Neurology - December 23, 2021 Category: Neurology Source Type: research

Machine Learning in Action: Stroke Diagnosis and Outcome Prediction
This article provides an overview of machine learning technology and a tabulated review of pertinent machine learning studies related to stroke diagnosis and outcome prediction.
Source: Frontiers in Neurology - December 6, 2021 Category: Neurology Source Type: research

Machine Learning-Based Model for Predicting Incidence and Severity of Acute Ischemic Stroke in Anterior Circulation Large Vessel Occlusion
Conclusions: Machine learning methods with multiple clinical variables have the ability to predict acute ischemic stroke and the severity of neurological impairment in patients with AC-LVO.
Source: Frontiers in Neurology - December 2, 2021 Category: Neurology Source Type: research

Application of Machine Learning Techniques to Identify Data Reliability and Factors Affecting Outcome After Stroke Using Electronic Administrative Records
Conclusion: Electronic administrative records from this cohort produced reliable outcome prediction and identified clinically appropriate factors negatively impacting most outcome variables following hospital admission with stroke. This presents a means of future identification of modifiable factors associated with patient discharge destination. This may potentially aid in patient selection for certain interventions and aid in better patient and clinician education regarding expected discharge outcomes.
Source: Frontiers in Neurology - September 27, 2021 Category: Neurology Source Type: research

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