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Condition: Thrombosis
Education: Training
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Total 178 results found since Jan 2013.
Time is Brain - Preclinical Emergency Care for Acute Ischemic Stroke
Anasthesiol Intensivmed Notfallmed Schmerzther. 2021 Dec;56(11-12):746-759. doi: 10.1055/a-1330-5239. Epub 2021 Nov 24.ABSTRACTStroke is one of the most common neurological emergencies and requires rapid detection and treatment (time is brain). There is still insufficient knowledge about stroke warning signs. It is therefore of crucial importance that trained personnel in the preclinical setting recognize the relevant warning symptoms and collect the necessary information to quickly refer the patient to the appropriate additional care structure. For this purpose, training of the emergency medical services (EMS) and the cor...
Source: Anasthesiologie, Intensivmedizin, Notfallmedizin, Schmerztherapie : AINS - November 25, 2021 Category: Intensive Care Authors: Leona M öller Lars Timmermann Anja Gerstner Source Type: research
Telemedicine remote controlled stroke evaluation and treatment, the experience of radiographers, paramedics and junior doctors in a novel rural stroke management team
CONCLUSIONS: The telemedicine-based, remote controlled, stroke evaluation and treatment was experienced, by the participants, to be well organised and of high quality. Communication and image reading appear to be the salient challenges. Regular training sessions and follow-up, as well as an evaluation of incidents by the project manager, proved to be of great importance in retaining and securing the continued running of the service and ensuring high-quality treatment. Further research is indicated in the comparison of this telemedicine service with stroke treatment given in a mainstream hospital.PMID:34090447 | DOI:10.1186/s12913-021-06591-1
Source: Rural Remote Health - June 6, 2021 Category: Rural Health Authors: Elin Kjelle Aud Mette Myklebust Source Type: research
Risk factor identification and prediction models for prolonged length of stay in hospital after acute ischemic stroke using artificial neural networks
ConclusionThe artificial neural network model achieved adequate discriminative power for predicting prolonged length of stay after acute ischemic stroke and identified crucial factors associated with a prolonged hospital stay. The proposed model can assist in clinically assessing the risk of prolonged hospitalization, informing decision-making, and developing individualized medical care plans for patients with acute ischemic stroke.
Source: Frontiers in Neurology - February 9, 2023 Category: Neurology Source Type: research
Clot-based radiomics model for cardioembolic stroke prediction with CT imaging before recanalization: a multicenter study
ConclusionThe proposed CT-based radiomics model could reliably predict CE stroke in AIS, performing better than the routine radiological method.Key Points• Admission CT imaging could offer valuable information to identify the acute ischemic stroke source by radiomics analysis.• The proposed CT imaging–based radiomics model yielded a higher area under the curve (0.838) than the routine radiological method (0.713; p = 0.007).• Several radiomic features showed significantly stronger correlations with two main thrombus constituents (red blood cells, |rmax|, 0.74; fibrin and platelet, |rmax|, 0.68) than routine radiolog...
Source: European Radiology - September 6, 2022 Category: Radiology Source Type: research
Combination of hand-crafted and unsupervised learned features for ischemic stroke lesion detection from Magnetic Resonance Images
Publication date: Available online 14 February 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): G.B. Praveen, Anita Agrawal, Ponraj Sundaram, Sanjay SardesaiAbstractDetection of ischemic stroke lesions plays a vital role in the assessment of stroke treatments such as thrombolytic therapy and embolectomy. Manual detection and quantification of stroke lesions is a time-consuming and cumbersome process. In this paper, we present a novel automatic method to detect acute ischemic stroke lesions from Magnetic Resonance Image (MRI) volumes using textural and unsupervised learned features. The proposed method profic...
Source: Biocybernetics and Biomedical Engineering - February 15, 2019 Category: Biomedical Engineering Source Type: research
Improving stroke risk prediction in the general population: Common clinical rules, a new multimorbid index and machine learning based algorithms
Conclusion Complex relationships of various comorbidities uncovered using a ML approach for diverse(and dynamic) multimorbidity changes have major consequences for stroke risk prediction.PMID:33765685 | DOI:10.1055/a-1467-2993
Source: Thrombosis and Haemostasis - March 25, 2021 Category: Hematology Authors: Gregory Yh Lip Ash Genaidy George Tran Patricia Marroquin Cara Estes Sue Sloop Source Type: research
