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Condition: Thrombosis
Education: Learning
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Total 128 results found since Jan 2013.
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
Machine Learning-Based Prediction of Brain Tissue Infarction in Patients With Acute Ischemic Stroke Treated With Theophylline as an Add-On to Thrombolytic Therapy: A Randomized Clinical Trial Subgroup Analysis
Conclusions: The predicted follow-up brain lesions for each patient were not significantly different for patients virtually treated with theophylline or placebo, as an add-on to thrombolytic therapy. Thus, this study confirmed the lack of neuroprotective effect of theophylline shown in the main clinical trial and is contrary to the results from preclinical stroke models.
Source: Frontiers in Neurology - May 21, 2021 Category: Neurology Source Type: research
Cerebral Venous Thrombosis Mimicking Acute Ischemic Stroke in the Emergency Assessment of Thrombolysis Eligibility: Learning from a Misdiagnosed Case
CONCLUSION: Patients with CVT have a higher risk of thrombolysis-related intracranial hemorrhage than other stroke mimics. A greater focus on noncontrast brain CT and the venous phase of CT angiography help identifying this stroke mimic before thrombolysis.PMID:34841501
Source: Acta Neurologica Taiwanica - November 29, 2021 Category: Neurology Authors: Po-Yu Lin Ying-Chen Chen Yuan-Ting Sun Source Type: research
