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1,304 results for “acute stroke”
Dataset for: Effects of acute ischemic stroke on binaural perception, Dietze et al., Frontiers in Neurosciences, 2022
<p>This dataset contains the MNI-registered lesion masks of patients with strokes at different locations and the psychoacoustic results (tone in noise detection and lateralization) of stroke and control groups.<br> The dataset is described in Dietze A, Sörös P, Bröer M, Methner A, Pöntynen H, Sundermann B, Witt K and Dietz M (2022) Effects of acute ischemic stroke on binaural perception. Front. Neurosci. 16:1022354. doi: 10.3389/fnins.2022.1022354</p>
Predictive models for secondary Epilepsy in patients with acute Ischemic Stroke within one year
Open the record for dataset details and reuse information.
Diagnostic and prediction value of synthetic magnetic resonance imaging in acute ischemic stroke patients
<p>This is the supplementary tables for the above paper, mainly including original statistical analysis data.</p>
CPAISD: Core-Penumbra Acute Ischemic Stroke Dataset
<p>The dataset contains 112 non-contrast cranial CT scans of patients with hyperacute stroke, featuring delineated zones of penumbra and core of the stroke on each slice where present. The data in the dataset are anonymized using the Kitware DicomAnonymizer, with standard anonymization settings, except for preserving the values of the following fields:</p> <ul> <li>(0x0010, 0x0040) – Patient's Sex</li> <li>(0x0010, 0x1010) – Patient's Age</li> <li>(0x0008, 0x0070) – Manufacturer</li> <li>(0x0008, 0x1090) – Manufacturer’s Model Name</li> </ul> <p>The patient's sex and age are retained for demographic analysis of the samples, and the equipment manufacturer and model are kept for dataset statistics and the potential for domain shift analysis.</p> <p>The dataset is split into three folds:</p> <ul> <li>Training fold (92 studies, 8,376 slices).</li> <li>Validation fold (10 studies, 980 slices).</li> <li>Testing fold (10 studies, 809 slices).</li> </ul> <p>The dataset has the following structure:</p> <ul> <li>metadata.json – dataset metadata</li> <li>summary.csv – metadata of each study in a CSV format table</li> <li>Part of the dataset (train, val, and test) <ul> <li>Study <ul> <li>Slice <ul> <li>raw.dcm – original slice file</li> <li>image.npz – slice in Numpy array format</li> <li>mask.npz – segmentation mask in Numpy array format</li> <li>metadata.json – slice metadata in JSON format</li> </ul> </li> <li>metadata.json – study metadata in JSON format</li> </ul> </li> </ul> </li> </ul> <p>The metadata.json at the root of the dataset has the following format:</p> <ul> <li>generation_params – dataset generation parameters: <ul> <li>test_size – proportion of the test part</li> <li>val_size – proportion of the validation part</li> </ul> </li> <li>stats – statistical data: <ul> <li>common – general statistical data: <ul> <li>train_size_in_studies – number of studies in the training part of the dataset.</li> <li>train_size_in_images – number of slices in the training part of the dataset.</li> <li>val_size_in_studies – number of studies in the validation part of the dataset.</li> <li>val_size_in_images – number of slices in the validation part of the dataset.</li> <li>test_size_in_studies – number of studies in the test part of the dataset.</li> <li>test_size_in_images – number of slices in the test part of the dataset.</li> </ul> </li> <li>train – statistical data for the training part of the dataset: <ul> <li>min – minimum pixel value.</li> <li>max – maximum pixel value.</li> <li>mean – average pixel value.</li> <li>std – standard deviation for all pixel values.</li> </ul> </li> </ul> </li> </ul> <p>The metadata.json at the root of the study has the following format, if a field value is unknown, it is given as 'unknown':</p> <ul> <li>manufacturer – manufacturer of the tomograph.</li> <li>model – model of the tomograph.</li> <li>device – full name of the tomograph (manufacturer + model).</li> <li>age – patient's age in years.</li> <li>sex – patient's sex. M – male, F – female.</li> <li>dsa – whether cerebral angiography was performed. true if yes, false if no.</li> <li>nihss – NIHSS score.</li> <li>time – time in hours from the onset of the stroke to the conduct of the study. Can be either a number or a range.</li> <li>lethality – whether the person died as a result of this stroke. true if yes, false if no.</li> </ul> <p>The summary.csv contains the same fields as the `metadata.json` from the root of the study, plus two additional fields:</p> <ul> <li>name – name of the study.</li> <li>part – part of the dataset in which the study is located.</li> </ul>
Acute_ischemic_stroke_subregions_MCA
<p>This dataset contains information of 302 people with acute ischemic stroke within the territory of the middle cerebral artery. This information regards to age, sex, race, and predominance of the infarct in the frontal or temporoparietal areas.</p>
Overview of acute stroke and rehabilitation pathway.
<p><strong><em>This image is supplementary material for:</em></strong></p> <p>Currie, C. S.M. Monks, T. (2018) <em>Modelling Diseases: Prevention, Cure, and Management.</em> In M. Rabe, A. Juan, N. Mustafee, A. Skoogh, & B. Johansson (Eds.). Proceedings of the Winter Simulation Conference 2018. Gothenburg, Sweden.</p> <p><em>Relevant to:</em></p> <p><em>Section 5.1</em></p>
A multi-laboratory preclinical trial to assess treatment candidates for acute ischemic stroke
<p>Human diseases may be modeled in animals to allow preclinical assessment of putative new clinical interventions. Recent, highly publicized failures of large clinical trials called into question the rigor, design, and value of preclinical assessment. We established the Stroke Preclinical Assessment Network (SPAN) to design and implement a randomized, controlled, blinded, multi-laboratory network for the rigorous assessment of candidate stroke treatments combined with intravascular thrombectomy. Futility boundaries in a Multi-Arm Multi-Stage statistical design aimed to exclude less effective interventions, and efficacy boundaries allowed early declaration of success after each of four sequential stages. Six independent research laboratories performed a standard focal cerebral ischemic insult in five animal models that included equal numbers of males and females: young mice, young rats, aging mice, mice with diet-induced obesity, and spontaneously hypertensive rats. The laboratories adhered to a common protocol and efficiently enrolled 2,615 animals with full data completion and comprehensive animal tracking. SPAN successfully implemented treatment masking, randomization, pre-randomization inclusion and exclusion criteria, and blinded assessment of outcomes. <a>The</a> SPAN design and infrastructure provide an effective approach that could be used in similar preclinical, multi-laboratory studies in other disease areas, and should help improve reproducibility in translational science.</p>
THALES - Acute STroke or Transient IscHaemic Attack Treated With TicAgreLor and ASA for PrEvention of Stroke and Death
ClinicalTrials.gov study NCT03354429. IPD Sharing: Not stated. Countries: 28. Publications: 9.
Which Parameters of Short-term Blood Pressure Variability Best Predict Early Outcomes in Acute Ischemic Stroke
ClinicalTrials.gov study NCT02675972. IPD Sharing: NO. Countries: 1. Publications: 1.
Safety and Pharmacokinetics of MCI-186 in Subjects With Acute Ischemic Stroke
ClinicalTrials.gov study NCT00821821. IPD Sharing: Not stated. Countries: 3. Publications: 1.
SEdation Versus General Anesthesia for Endovascular Therapy in Acute Ischemic Stroke
ClinicalTrials.gov study NCT03263117. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Alteplase Treatment in Elderly Acute Ischaemic Stroke (AIS) Patients
ClinicalTrials.gov study NCT05401149. IPD Sharing: NO. Countries: 1. Publications: 1.
Sub-Acute Stroke Rehabilitation With AMES
ClinicalTrials.gov study NCT00609115. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Systematic Evaluation of Patients Treated With Stroke Devices for Acute Ischemic Stroke (STRATIS) Registry
ClinicalTrials.gov study NCT02239640. IPD Sharing: NO. Countries: 1. Publications: 8.
Study of the Combination Therapy of Rt-PA and Eptifibatide to Treat Acute Ischemic Stroke (CLEAR-FDR)
ClinicalTrials.gov study NCT01977456. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A Proof of Concept Study to Evaluate the Safety of Afamelanotide in Patients With Acute Arterial Ischaemic Stroke (AIS)
ClinicalTrials.gov study NCT04962503. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Rivaroxaban Versus Warfarin in Acute Ischemic Stroke With Atrial Fibrillation
ClinicalTrials.gov study NCT02042534. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.
Evaluation of Mechanical Thrombectomy in Acute Ischemic Stroke Related to a Distal Arterial Occlusion
ClinicalTrials.gov study NCT05030142. IPD Sharing: YES. Countries: 1. Publications: 1.
A Phase Ib/II in Patients With Acute Ischemic Stroke
ClinicalTrials.gov study NCT02963376. IPD Sharing: Not stated. Countries: 1. Publications: 1.
China Antihypertensive Trial in Acute Ischemic Stroke
ClinicalTrials.gov study NCT01840072. IPD Sharing: NO. Countries: 1. Publications: 31.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.