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학제간연구 과학기술학 뇌인지과학 기술정책 기타 복합학

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논문 기본 정보

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학술저널
저자정보
Johanna M. Ospel (Department of Diagnostic Imaging, University of Calgary, Calgary, AB, Canada Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada) Leon Rinkel (Department of Diagnostic Imaging, University of Calgary, Calgary, AB, Canada, Department of Neurology, Amsterdam University Medical Centers, location AMC, Amsterdam, The Netherlands) Aravind Ganesh (Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada) Andrew Demchuk (Department of Diagnostic Imaging, University of Calgary, Calgary, AB, Canada Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada) Manraj Heran (Department of Radiology, University of British Columbia, Vancouver, BC, Canada) Eric Sauvageau (Lyerly Neurosurgery, Baptist Hospital, Jacksonville, FL, USA) Manish Joshi (Department of Diagnostic Imaging, University of Calgary, Calgary, AB, Canada Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada) Diogo Haussen (Emory University School of Medicine, Grady Memorial Hospital, Atlanta, GA, USA) Mahesh Jayaraman (Warren Alpert School of Medicine, Brown University, Providence, RI, USA) Shelagh Coutts (Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada) Amy Yu (University of Toronto, Toronto, ON, Canada; Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada) Volker Puetz (University Hospital Carl Gustav Carus at the Technische Universität Dresden, Department of Neurology and Dresden Neurovascular Center, Dresden, Germany) Dana Iancu (Centre Hospitalier de l’Université de Montréal, Montreal, QC, Canada) Oh Young Bang (Department of Neurology, Samsung Medical Center, Sungkyunkwan University, Seoul, Korea) Jason Tarpley (Providence Little Company of Mary Medical Center, Providence Saint John’s Health Center and The Pacific Neuroscience Institute, Torrance, CA, USA) Staffan Holmin (Department of Clinical Neuroscience, Karolinska Institutet and Departments of Neuroradiology and Neurology, Karolinska University Hospital, Stockholm, Sweden) Michael Kelly (Royal University Hospital, University of Saskatchewan, Saskatoon, SK, Canada) Michael Tymianski (NoNO Inc., Toronto, ON, Canada) Michael Hill (Department of Diagnostic Imaging, University of Calgary, Calgary, AB, Canada Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada) Mayank Goyal (Department of Diagnostic Imaging, University of Calgary, Calgary, AB, Canada Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada)
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대한뇌졸중학회 대한뇌졸중학회지 대한뇌졸중영문학회지 제26권 제2호
발행연도
2024.5
수록면
252 - 259 (8page)

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초록· 키워드

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Background and Purpose Infarct volume and other imaging markers are increasingly used as surrogate measures for clinical outcome in acute ischemic stroke research, but how improvements in these imaging surrogates translate into better clinical outcomes is currently unclear. We investigated how changes in infarct volume at 24 hours alter the probability of achieving good clinical outcome (modified Rankin Scale [mRS] 0–2). Methods Data are from endovascular thrombectomy patients from the randomized controlled ESCAPE-NA1 (Efficacy and Safety of Nerinetide for the Treatment of Acute Ischaemic Stroke) trial. Infarct volume at 24 hours was manually segmented on non-contrast computed tomography or diffusion-weighted magnetic resonance imaging. Probabilities of achieving good outcome based on infarct volume were obtained from a multivariable logistic regression model. The probability of good outcome was plotted against infarct volume using linear spline regression. Results A total of 1,099 patients were included in the analysis (median final infarct volume 24.9 mL [interquartile range: 6.6–92.2]). The relationship between total infarct volume and good outcome probability was nearly linear for infarct volumes between 0 mL and 250 mL. In this range, a 10% increase in the probability of achieving mRS 0–2 required a decrease in infarct volume of approximately 34.0 mL (95% confidence interval: -32.5 to -35.6). At infarct volumes above 250 mL, the probability of achieving mRS 0–2 probability was near zero. The relationships of tissue-specific infarct volumes and parenchymal hemorrhage volume generally showed similar patterns, although variability was high. Conclusion There seems to be a near-linear association between total infarct volume and probability of achieving good outcome for infarcts up to 250 mL, whereas patients with infarct volumes greater than 250 mL are highly unlikely to have a favorable outcome.
#Acute stroke #Ischemia #Infarct volume #Thrombectomy

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