COVID-19 Clinical Trials and Expanded Access

The goal of this study is to evaluate if CT (Computerized Tomography) can effectively and accurately predict disease progression in patients with SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2). You may be eligible if you have been diagnosed with SARS-CoV-2, are an inpatient at Beaumont Hospital-Royal Oak and meet eligibility criteria. After consent and determination of eligibility, enrolled patients will have a CT scanning session. After the CT scan, patients are followed for 30 days by reviewing their medical records and by phone after discharge from hospital.

COVID-19 outbreak is often lethal. Mortality has been associated with several cardio-vascular risk factors such as diabetes, obesity, hypertension and tobacco use. Other clinico-biological features predictive of mortality or transfer to Intensive Care Unit are also needed. Cases of myocarditis have also been reported with COVID-19. Cardio-vascular events have possibly been highly underestimated. The study proposes to systematically collect cardio-vascular data to study the incidence of myocarditis and coronaropathy events during COVID-19 infection.We will also assess predictive factors for transfer in Intensive Care Unit or death.

There is a high risk of transmission of COVID-19 to healthcare workers. In a recent cohort, 29% of the patients hospitalized were healthcare workers. Among the WHO's primary strategic objectives for the response to COVID-19, the first was to limit human-to-human transmission, including reducing secondary infections among close contacts and health care workers. Automated oxygen titration, weaning and monitoring (FreeO2 device) may be a solution to reduce the number of interventions of healthcare workers related to oxygen therapy, to reduce complications related to oxygen and to improve monitoring.

This study is expected to provide, for the first time, data on Cov2-SARS circulation in asymptomatic children and children with moderate respiratory symptoms in order to construct the severity pyramid of this novel pathogen. This information will be essential in the coming weeks to understand the dynamics of the transmission of this pathogen at the population level and to highlight the relevance of public health interventions, particularly with regard to the systematic closure of schools and childcare facilities.

This study aim to evaluate the immune response of negative patients during a COVID-19 outbreak. Patients are serially tested with a VivaDiag ™ COVID-19 lgM / IgG Rapid Test to evaluate the immune response in negative patients and the reliability of the test in those patients who develop clinical signs of COVID-19 during the trial.

This project aims to use artificial intelligence (image discrimination) algorithms, specifically convolutional neural networks (CNNs) for scanning chest radiographs in the emergency department (triage) in patients with suspected respiratory symptoms (fever, cough, myalgia) of coronavirus infection COVID 19. The objective is to create and validate a software solution that discriminates on the basis of the chest x-ray between Covid-19 pneumonitis and influenza

Our project intends to independently develop a fully enclosed rapid detection system for a total of 22 pathogens, including SARS-CoV-2, on the basis of the QIAstat-Dx fully automatic multiple PCR detection platform. The reasonably designed experiments are used to verify the performance of the cartridge detection and prove its clinical application value. The 22 pathogens tested in this project includes 4 coronavirus subtypes, A / B flu, parainfluenza virus, respiratory syncytial virus, etc., which is of great significance for the differential diagnosis of similar patients.

Since Dec 2019, over 70000 novel coronavirus infection pneumonia (NCIP) patients were confirmed. 2019 novel coronavirus (2019 nCoV) is a RNA virus, which spread mainly from person-to-person contact. Most of the symptoms are non-specific, including fever, fatigue, dry cough. Sever NCIP patients may have shortness of breath and dyspnea, and progress to acute respiratory distress syndrome (ARDS) and multiple organ dysfunction syndrome (MODS). The mortality is reported to be around 2.3%. Thus, early detection and early treatment is very important to the improvement of NCIP patients' prognosis. At present, NCIP RNA detection of pharyngeal swab specimen by RT-PCR is recommended. However, due to the universal susceptibility to 2019 nCoV in general population and limited number of NCIP RNA detection kits available, to identify an efficient screening strategy is urgently needed. This study aim to develop and validate the diagnostic accuracy and screening efficiency of a new NCIP screening strategy, which can benefit the disease prevention and control.

The purpose of this study is two-fold. First we would like to confirm that non-contact ECG provides equivalency to current contact methods of obtaining ECG data. Second we would like to investigate whether non-contact ECG can detect ECG changes prior to the onset symptoms from COVID19.

Covid-SER is a prospective multi-center study for the evaluation of diagnostic performance of available serological tests