Background And Aims: The clinical evolution of acute ischemic stroke patients with isolated proximal posterior cerebral artery (PCA) occlusion treated with medical management alone has been poorly described. We aimed to determine the clinical and radiological factors associated with poor functional outcome in this population.
Methods: We conducted a multicenter international retrospective study of consecutive stroke patients with isolated occlusion of the first (P1) or second (P2) segment of PCA admitted within 6hrs from symptoms onset in 26 stroke centers in France, Switzerland and the USA, treated with best medical management alone.
Background: Cholangiocarcinoma (CCA) represents a global health challenge, with rising incidence and mortality rates. This study aimed to elucidate the clinical course and practices of CCA in Latin America.
Methods: This observational cohort study investigated individuals diagnosed with CCA between 2010 and 2023 at five referral centres across Latin America.
Human mobility drives the spread of many infectious diseases, yet the health impacts of changes in mobility due to new infrastructure development are poorly understood and currently not accounted for in impact assessments. We take a novel quasi-experimental approach to identifying the link between mobility and infectious disease, leveraging historical road upgrades as a proxy for regional human mobility changes. We analyzed how highway paving altered transmission of dengue-a high-burden mosquito-borne disease-via changes in human movement in the Madre de Dios region of Peru.
View Article and Find Full Text PDFBackground: The rising prevalence of acute ischemic stroke (AIS) in young adults, particularly with undetermined pathogenesis, is a growing concern. This study assessed risk factors, treatments, and outcomes between young AIS patients with undetermined and determined pathogeneses.
Methods And Results: This was a retrospective cohort study including AIS patients aged 18 to 55 years in Switzerland, treated between 2014 and 2022.
Background: Prediction of outcome after stroke is critical for treatment planning and resource allocation but is complicated by fluctuations during the first days after onset. We propose a machine learning model that can provide hourly predictions based on the integration of continuous variables acquired within 72 h of hospital admission.
Methods: We analyzed 2492 admissions for ischemic stroke in the Geneva University Hospital from 01.