Publications by authors named "Leila S Harima"
Article Synopsis
- A study aims to improve COVID-19 patient management by creating a computational model that analyzes electronic medical records to find correlations between drug prescriptions and patient outcomes.
- The research involved data from 3,674 hospitalized patients, focusing on drug prescriptions and their relationship to whether patients were discharged alive or deceased, using advanced machine learning techniques for analysis.
- Results indicated that anticoagulants improved prognosis when given after the first week of symptoms, while commonly prescribed antibiotics did not significantly affect patient outcomes, signifying a potential reevaluation of treatment strategies.
Background: COVID-19 caused more than 622 thousand deaths in Brazil. The infection can be asymptomatic and cause mild symptoms, but it also can evolve into a severe disease and lead to death. It is difficult to predict which patients will develop severe disease.
View Article and Find Full Text PDFBackground: Fibrosis has been the most cited variable in cirrhosis, but major alterations in hepatic vascularization have been pointed as basic elements in the physiopathology of the illness and its complications as portal hypertension, hepatic failure and hepatocellular carcinoma.
Methods: The present study aims at assessing microvascular density in 35 cases of necropsies of cirrhotic patients by immunohistochemical detection of endothelial marker CD34, comparing semi-quantification with morphometric quantitative method, also searching for a possible relation of vascular alterations with the main causal agents, injury patterns and major clinical complications.
Results: A significant association was detected between semi-quantitative and quantitative approach of microvessel density in parenchyma, but not in septa.