2021
DOI: 10.1038/s41598-021-89871-4
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Predictors for affected stroke territory and outcome of acute stroke treatments are different for posterior versus anterior circulation stroke

Abstract: Distinct patient characteristics have been proposed for ischaemic stroke in the anterior versus posterior circulation. However, data on functional outcome according to stroke territory in patients with acute stroke treatment are conflicting and information on outcome predictors is scarce. In this retrospective study, we analysed functional outcome in 517 patients with stroke and thrombolysis and/or thrombectomy treated at the University Hospital Zurich. We compared clinical factors and performed multivariate l… Show more

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Cited by 10 publications
(7 citation statements)
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“…In four studies, the female sex was higher in ACS cases, contrary to De Marchis and our study, which was the same in both sexes 4 , 5 , 8 , 9 , 13 .…”
Section: Discussioncontrasting
confidence: 85%
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“…In four studies, the female sex was higher in ACS cases, contrary to De Marchis and our study, which was the same in both sexes 4 , 5 , 8 , 9 , 13 .…”
Section: Discussioncontrasting
confidence: 85%
“…In a study on 18-month follow-up of IVT cases, there was 34.3% mortality, possibly making acceptable a mortality rate of 17.75% after a 3-month follow-up in the present work. PCS cases were about 7.00% of IVT therapy cases in this study, while in ours, it was about 4.60%; in other studies, more cases were reported compared to ours 4 , 5 , 9 , 20 , 22 . This difference could be due to the delay in diagnosis and admission of our PCS cases and fewer data collection.…”
Section: Discussioncontrasting
confidence: 62%
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“…AIS outcomes depend on the clinical setting and patient demographics as well as on a multitude of variables associated with cerebral core infarction, perfusion, etc. 1–3 Information management strategies for AIS are helpful for improving the prediction of clinical prognosis. Many studies have attempted to combine these prognostic factors into standardized scores or use machine learning to predict clinical outcomes.…”
mentioning
confidence: 99%