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COVID-19 Longitudinal Biomarkers in Lung Injury

Dr. Andrew Baker · 2020
ClinicalTrials.gov · Datasets · License: Public Domain · 2020
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covid19critical-illness
Profile known and novel biomarkers in blood in COVID19 patients to characterize the host response to SARS-CoV-2 over time and in response to treatment. The investigators aim to: * Better understand the disease. The investigators will achieve this by characterizing the biology of COVID-19 infection and the pathophysiology of the host response using clinical data together with cellular and molecular measurements over the course of the disease. This will allow better insights for the discovery and development of novel therapeutics. * Understand why different patients have different phenotypes and disease presentations over time. The investigators will achieve this by analyzing for patient subgroups. This will allow targeted patient stratification and better matching of resources. * Understand how patients are responding to the different medications being tested in clinical trials. The investigators will achieve that by co-enrolling with therapeutic trials. This will allow an understanding of the biological effects of these interventions. Study Design: Observational adaptive study of a translational nature, combining clinical data and basic science investigations in blood samples in the same patients, longitudinally, with serial interim analyses. Primary outcomes: 90 day ICU mortality. Secondary outcomes: measures of ICU utilization and disease severity, and 90 day in-hospital mortality. The study ends after 3 months from admission to the ICU, hospital discharge or death. Location: St. Michael's Hospital (Unity Health Toronto), an academic center in downtown Toronto affiliated with the University of Toronto. The investigators will collect: A) Detailed clinical data including investigations, mechanical ventilation and cardiovascular parameters. B) Blood samples for state-of-the-art multi-omics biomarker discovery and development: cytokines, anti-COVID19 antibodies, autoimmune serology, metabolomics, transcriptomics, epigenomics, deep immune phenotyping, viral load
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