Publications by authors named "J M Ospel"
This two part series on statistical principles in neurointervention offers a comprehensive foundation for neurointerventionalists to engage with both fundamental and advanced statistical principles. This series aims to equip neurointerventionalists with essential statistical knowledge for critically reviewing literature and conducting methodologically sound research. Part one of this series covered fundamental concepts such as frequentism, study types, data types, summarization, visualization, hypothesis testing, and univariable analysis.
View Article and Find Full Text PDFNeurointervention has seen significant advancements in recent decades with the adoption of myriad new technologies and techniques. Initially reliant on case reports and small case series, we now benefit from multicenter studies and randomized trials that can provide robust practice-changing evidencea and often employ sophisticated statistical methods. This two-part series on statistical principles in neurointervention aims to equip neurointerventionalists with essential statistical knowledge for critically reviewing literature and conducting methodologically sound research.
View Article and Find Full Text PDFBackground: In the ESCAPE-NA1 trial (Efficacy and Safety of Nerinetide for the Treatment of Acute Ischemic Stroke), treatment with nerinetide was associated with a smaller infarct volume among patients who did not receive intravenous alteplase. We assessed the effect of nerinetide on the surrogate imaging outcome of final infarct volume in patients who did not receive intravenous alteplase and explored predictors of outcome and modifiers of nerinetide's effect on infarct volume.
Methods: ESCAPE-NA1 was a multicenter, randomized trial in which patients with acute stroke with a baseline Alberta Stroke Program Early CT Score >4, undergoing endovascular thrombectomy, were randomized to receive intravenous nerinetide or placebo.
Article Synopsis
- Hematoma expansion (HE) occurs in a significant portion of patients with acute intracerebral hemorrhage (ICH), impacting their outcomes; the study focuses on the predictive accuracy of the Black-&-White (B&W) sign in identifying HE.
- In a multicenter cohort from the PREDICT study, the association between the B&W sign and HE was analyzed, revealing that patients with the B&W sign had a higher frequency of HE and more substantial growth of hematomas compared to those without it.
- The B&W sign strongly predicts HE, with an adjusted odds ratio of 7.83 for HE and 5.67 for severe HE, indicating that its presence significantly increases the risk of hematoma expansion.
Sex differences in brain MRI using deep learning toward fairer healthcare outcomes.
Front Comput Neurosci
November 2024
Article Synopsis
- - This study uses deep learning to analyze sex differences in brain MRI data, involving 3D images from four diverse datasets while maintaining balanced representation in sex and demographics.
- - A Convolutional Neural Network model achieved 87% accuracy in sex classification without adjusting for total intracranial volume, revealing some biases related to brain size but performing better with overlapping TIV distributions.
- - The research highlighted key brain regions important for sex differentiation and aims to inform strategies for reducing bias in medical imaging, ultimately contributing to fairer AI algorithms and healthcare outcomes.