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Total 1309 results found since Jan 2013.

Development of a convolutional neural network (CNN) based assessment exercise recommendation system for individuals with chronic stroke: a feasibility study
CONCLUSIONS: This CNN deep-learning model provided time-effective and accurate prediction of clinical assessment results and exercise recommendations. This study provides preliminary evidence to support the use of biomechanical data and AI to assist treatment planning and shorten the decision-making process in rehabilitation.PMID:36189968 | DOI:10.1080/10749357.2022.2127669
Source: Topics in Stroke Rehabilitation - October 3, 2022 Category: Neurology Authors: Jiaqi Li Patrick W H Kwong E K Lua Mathew Y L Chan Anna Choo C J W Donnelly Source Type: research

Image level detection of large vessel occlusion on 4D-CTA perfusion data using deep learning in acute stroke
Acute ischemic stroke (AIS) secondary to LVOs represent approximately 30-40% of all stroke cases and are associated with disproportionately higher morbidity and mortality.1, 2 The importance of endovascular thrombectomy (EVT) in patients with acute ischemic stroke (AIS) has been well established in multiple randomized controlled trials for patients in both early and late stroke windows.3-6 A critical aspect of the patient triage is the accurate and timely detection of underlying large vessel occlusion (LVO).
Source: Journal of Stroke and Cerebrovascular Diseases - September 10, 2022 Category: Neurology Authors: Girish Bathla, Dhruba Durjoy, Sarv Priya, Edgar Samaniego, Colin P. Derdeyn Source Type: research

A Smartphone Application To Aid In The Evaluation, Treatment, And Clinical Trial Enrollment Of The Acute Stroke Patient (P7.125)
CONCLUSION: A smartphone application that centralizes various disparate resources may allow for more efficient management of the acute stroke patient. Further, such an application may allow easy screening for clinical trials by new practitioners as they learn of the various inclusion criteria for their studies.Disclosure: Dr. Nguyen has received royalty, or license fee, or contractual rights payments from the University of Texas. Dr. Wu has nothing to disclose. Dr. Barreto has nothing to disclose. Dr. Grotta has received personal compensation for activities with Lundbeck as a consultant. Dr. Savitz has received personal co...
Source: Neurology - April 9, 2014 Category: Neurology Authors: Nguyen, C., Wu, T.-C., Barreto, A., Grotta, J., Savitz, S. Tags: Cerebrovascular Disease and Interventional Neurology: Issues in Acute Stroke Treatment Source Type: research

Delayed Hyperbaric Oxygen Therapy Promotes Neurogenesis Through Reactive Oxygen Species/Hypoxia-Inducible Factor-1{alpha}/{beta}-Catenin Pathway in Middle Cerebral Artery Occlusion Rats Basic Sciences
Conclusions— Delayed HBO enhanced endogenous neurogenesis and improved neurofunctional recovery in the late-chronic phase of stroke possibly mediated by ROS/HIF-1α/β-catenin pathway. Delayed HBO may serve as an alternative treatment to improve long-term recovery of stroke survivors.
Source: Stroke - May 27, 2014 Category: Neurology Authors: Hu, Q., Liang, X., Chen, D., Chen, Y., Doycheva, D., Tang, J., Tang, J., Zhang, J. H. Tags: Animal models of human disease, Other Stroke Treatment - Medical Basic Sciences Source Type: research

Prophylactic Edaravone Prevents Transient Hypoxic-Ischemic Brain Injury: Implications for Perioperative Neuroprotection Basic Sciences
Conclusions— Acute application of Edaravone may be a useful strategy to prevent postsurgery stroke and cognitive impairment, especially in patients with severe carotid stenosis.
Source: Stroke - June 22, 2015 Category: Neurology Authors: Sun, Y.-Y., Li, Y., Wali, B., Li, Y., Lee, J., Heinmiller, A., Abe, K., Stein, D. G., Mao, H., Sayeed, I., Kuan, C.-Y. Tags: Animal models of human disease, Other Stroke Treatment - Medical, Coagulation and fibronolysis Basic Sciences Source Type: research

Transcranial direct current stimulation for children with perinatal stroke and hemiparesis
Conclusion: tDCS trials appear feasible and safe in hemiparetic children. Lack of change in objective motor function may reflect underdosing of therapy. Marked gains in subjective function with tDCS warrant further study. ClinicalTrials.gov identifier: NCT02170285. Classification of evidence: This study provides Class II evidence that for children with perinatal stroke and hemiparetic cerebral palsy, the addition of tDCS to moderate-dose motor learning therapy does not significantly improve motor function as measured by the AHA.
Source: Neurology - January 15, 2017 Category: Neurology Authors: Kirton, A., Ciechanski, P., Zewdie, E., Andersen, J., Nettel-Aguirre, A., Carlson, H., Carsolio, L., Herrero, M., Quigley, J., Mineyko, A., Hodge, J., Hill, M. Tags: Childhood stroke, Clinical trials Randomized controlled (CONSORT agreement), All Rehabilitation, Plasticity, TMS ARTICLE Source Type: research

Growth Hormone Improves Cognitive Function After Experimental Stroke Basic Sciences
Conclusions—These findings provide compelling preclinical evidence for the usage of GH as a potential therapeutic tool in the recovery phase of patients after stroke.
Source: Stroke - April 23, 2018 Category: Neurology Authors: Lin Kooi Ong, Wei Zhen Chow, Clifford TeBay, Murielle Kluge, Giovanni Pietrogrande, Katarzyna Zalewska, Patricia Crock, N. David Aberg, Andrew Bivard, Sarah J. Johnson, Frederick R. Walker, Michael Nilsson, Jorgen Isgaard Tags: Angiogenesis, Basic Science Research, Growth Factors/Cytokines, Cognitive Impairment, Neurogenesis Original Contributions Source Type: research

Texture Features of Magnetic Resonance Images: an Early Marker of Post-stroke Cognitive Impairment
AbstractStroke is frequently associated with delayed, long-term cognitive impairment (CI) and dementia. Recent research has focused on identifying early predictive markers of CI occurrence. We carried out a texture analysis of magnetic resonance (MR) images to identify predictive markers of CI occurrence based on a combination of preclinical and clinical data. Seventy-two-hour post-stroke T1W MR images of 160 consecutive patients were examined, including 75 patients with confirmed CI at the 6-month post-stroke neuropsychological examination. Texture features were measured in the hippocampus and entorhinal cortex and compar...
Source: Translational Stroke Research - October 31, 2019 Category: Neurology Source Type: research

Uric Acid and Gluconic Acid as Predictors of Hyperglycemia and Cytotoxic Injury after Stroke
AbstractHyperglycemia is a feature of worse brain injury after acute ischemic stroke, but the underlying metabolic changes and the link to cytotoxic brain injury are not fully understood. In this observational study, we applied regression and machine learning classification analyses to identify metabolites associated with hyperglycemia and a neuroimaging proxy for cytotoxic brain injury. Metabolomics and lipidomics were carried out using liquid chromatography-tandem mass spectrometry in admission plasma samples from 381 patients presenting with an acute stroke. Glucose was measured by a central clinical laboratory, and a s...
Source: Translational Stroke Research - October 17, 2020 Category: Neurology Source Type: research

Development and Validation of Machine Learning-Based Prediction for Dependence in the Activities of Daily Living after Stroke Inpatient Rehabilitation: A Decision-Tree Analysis
This study aimed to develop and assess the CPRs using machine learning-based methods to identify ADL dependence in stroke patients.
Source: Journal of Stroke and Cerebrovascular Diseases - September 26, 2020 Category: Neurology Authors: Yuji Iwamoto, Takeshi Imura, Ryo Tanaka, Naoki Imada, Tetsuji Inagawa, Hayato Araki, Osamu Araki Source Type: research

Decision Tree Algorithm Identifies Stroke Patients Likely Discharge Home After Rehabilitation Using Functional and Environmental Predictors
The importance of environmental factors for stroke patients to achieve home discharge was not scientifically proven. There are limited studies on the application of the decision tree algorithm with various functional and environmental variables to identify stroke patients with a high possibility of home discharge. The present study aimed to identify the factors, including functional and environmental factors, affecting home discharge after stroke inpatient rehabilitation using the machine learning method.
Source: Journal of Stroke and Cerebrovascular Diseases - February 3, 2021 Category: Neurology Authors: Takeshi Imura, Yuji Iwamoto, Tetsuji Inagawa, Naoki Imada, Ryo Tanaka, Haruki Toda, Yu Inoue, Hayato Araki, Osamu Araki Source Type: research

Discrepancies in Stroke Distribution and Dataset Origin in Machine Learning for Stroke
Machine learning algorithms depend on accurate and representative datasets for training in order to become valuable clinical tools that are widely generalizable to a varied population. We aim to conduct a review of machine learning uses in stroke literature to assess the geographic distribution of datasets and patient cohorts used to train these models and compare them to stroke distribution to evaluate for disparities.
Source: Journal of Stroke and Cerebrovascular Diseases - April 30, 2021 Category: Neurology Authors: Lohit Velagapudi, Nikolaos Mouchtouris, Michael P. Baldassari, David Nauheim, Omaditya Khanna, Fadi Al Saiegh, Nabeel Herial, M. Reid Gooch, Stavropoula Tjoumakaris, Robert H. Rosenwasser, Pascal Jabbour Source Type: research

Development of Machine Learning Models to Predict Probabilities and Types of Stroke at Prehospital Stage: the Japan Urgent Stroke Triage Score Using Machine Learning (JUST-ML)
AbstractIn conjunction with recent advancements in machine learning (ML), such technologies have been applied in various fields owing to their high predictive performance. We tried to develop prehospital stroke scale with ML. We conducted multi-center retrospective and prospective cohort study. The training cohort had eight centers in Japan from June 2015 to March 2018, and the test cohort had 13 centers from April 2019 to March 2020. We use the three different ML algorithms (logistic regression, random forests, XGBoost) to develop models. Main outcomes were large vessel occlusion (LVO), intracranial hemorrhage (ICH), suba...
Source: Translational Stroke Research - August 14, 2021 Category: Neurology Source Type: research

Determining the barriers and facilitators to adopting best practices in the management of poststroke unilateral spatial neglect: results of a qualitative study.
Conclusion: It is estimated that upwards of 40% of patients experience poststroke USN in the acute phase, and we have evidence of poor early management. This study identified several modifiable factors that prepare the ground for the creation and testing of a multimodal knowledge translation intervention aimed at improving clinicians' best practice management of poststroke USN. PMID: 24985390 [PubMed - in process]
Source: Topics in Stroke Rehabilitation - May 1, 2014 Category: Neurology Authors: Petzold A, Korner-Bitensky N, Salbach NM, Ahmed S, Menon A, Ogourtsova T Tags: Top Stroke Rehabil Source Type: research

Methodology of the Stroke Self-Management Rehabilitation Trial: An International, Multisite Pilot Trial
Stroke is a major cause of long-term adult disability with many survivors living in the community relying on family members for on-going support. However, reports of inadequate understanding of rehabilitation techniques are common. A self-management DVD-based observational learning tool may help improve functional outcomes for survivors of stroke and reduce caregivers' burden.
Source: Journal of Stroke and Cerebrovascular Diseases - December 9, 2014 Category: Neurology Authors: Kelly M. Jones, Rohit Bhattacharjee, Rita Krishnamurthi, Sarah Blanton, Alice Theadom, Suzanne Barker-Collo, Amanda Thrift, Priya Parmar, Annick Maujean, Annemarei Ranta, Emmanuel Sanya, Valery L. Feigin, SMART Study Group Source Type: research