COVID-19 Clinical Trials and Expanded Access

The outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the COVID-19 (Coronavirus Disease-2019) in December 2019 has led to an unprecedented international health situation. Exceptional measures have been taken by public authorities worldwide in order to slow the spread of the virus and prevent healthcare systems from becoming overloaded. In France, a national lockdown has been established during approximately 2 months to increase social distancing and restrict population movements. Hospital routine care appointments have been cancelled, in order to reallocate medical resources towards COVID-19 units and limit contacts between patients within hospitals or waiting rooms. While the virus itself, the disease and potential treatments are currently extensively studied, little data are available on the effect of these public health decisions on the management of a chronic condition such as diabetes. The French regional CONFI-DIAB study aims at assessing the collateral impact of routine care cancellation during the national lockdown due to COVID-19 in patients with a chronic condition such as diabetes. Special attention will be given to metabolic control and access to health care. This cross-sectional study should provide information on the consequences of a global lockdown and the associated routine care cancellation on the management of diabetes, and inform future decision making in the event of a new pandemic.

Clinical Picture: Symptomatic COVID-19 presents with a recognizable clinical syndrome that is predictable prior to testing. Clinical judgement remains important, particularly when interpreting negative test results; 2. Biomarkers Associated with COVID-19 Patients: The most common laboratory features reported in patients with COVID-19

The aim of the study is to identify the knowledge that CCSPT nurses have in relation to care aimed at addressing anxiety, fear or loneliness and the use they have made of it in the recent crisis. The design of the research/action will also enable the training of the participating professionals to improve nursing care in these areas in the future

In this 16-week randomized control study, health care workers will receive a bolus dose followed by a weekly dose of vitamin D or a placebo bolus and weekly dose. This study will test whether high-dose of vitamin D supplementation decreases the incidence of laboratory-confirmed COVID19 infection (primary outcome), reduces illness severity, duration, as well as work absenteeism among health care workers (HCW) in setting at high-risk of contact with COVID-19 cases in high COVID-19 incidence areas.

To evaluate and compare nebulized platelet lysate to placebo control of saline administered via handheld nebulizer 1x daily for eight weeks to determine effect on lung function in patients with post-COVID-19 ARDS syndrome.

Problem: The COVID- 19 pandemic has not only affected our healthcare system, but the impact on the worldwide financial systems and our "normal" way of life is still to be determined. Although the percentage of patients infected with COVID-19 that need hospital care is low, Its high rate of contagiousness makes the total number of patients in need of hospital care cripple any healthcare system, limiting the space available for other patients in need of critical care, who cannot be admitted or even prefer not to attend the hospital in fear of infection. Early investigations report an Increase risk of thromboembolic complications, and a systemic inflammatory response not clearly understood. There is a possible vascular endothelial dysfunction due to chronic comorbidities (Hypertension, diabetes, obesity, chronic kidney disease, lung disease) as a risk factor for a more severe presentation. Justification: Sulodexide is a two-compound drug, each of them with different endothelial action that can be beneficial in COVID-19 patients. Glycosaminoglycans: Can help restore venous and arterial endothelial glycocalyx which can downregulate or limit the response to inflammatory molecules, by maintaining the integrity lost in certain chronic diseases (high blood pressure, diabetes). Heparin compound: It has an antithrombotic effect that could help reduce the incidence of thromboembolic complications, and also add to the anti-inflammatory response due to it anti-thrombin action (similar or a bit less to that of low molecular weight heparin) with less risk of major bleeding. It's a medication that can be used orally with minimal adverse effects and is less expensive than low molecular weight heparin. Hypothesis: We hypothesize that sulodexide instituted early in populations at significant risk and symptomatic patients affected with COVID-19 (shortness of breath, fever, weakness, diarrhoea) and risk factors of diabetes, hypertension, COPD, atherosclerosis, chronic kidney disease, will provide improvement in endothelial integrity, decrease inflammatory responses, and improved clinical outcomes with decreased hospital admission, decrease VTE and arterial complications, morbidity, and mortality. Objective: To use sulodexide in patients that have early onset of COVID-19 symptoms to mitigate the progression of the disease process that can allow them to recover at home, and limit the need of hospital care and a more severe clinical manifestation

Boswellia Serrata gum and Licorice extract are two nutritional agents that have pharmacological actions that could support the medical intervention for COVID-19. They have broad antiviral activity, anti-inflammatory, anti-lung injury, antibacterial activity, antithrombic formation, and immunomodulatory activity. The study will be conducted after January 18, 2017

To assess the prognostic performance of an early global LUS score with respect to the mortality in ICU and duration of ventilation.

It is our hypothesis that a course of Ta1 administered to hospitalized individuals with COVID-19 infection and lymphocytopenia will improve the time to recovery (primary objective) and severity of infection (secondary objectives) compared to untreated individuals in the same hospital with comparable lymphocytopenia. After screening, hospitalized patients with COVID-19 and lymphocytopenia who meet the inclusion criteria will receive Ta1 (1.6 mg) administered subcutaneously (SC) daily for 1 week. Individuals in the control arm will be followed on the identical protocol but will not receive daily Ta1.

COVID-19 is an infectious disease caused by a newly discovered Coronavirus which was first identified in Wuhan, China in December 2019. Then the novel coronavirus outbreak was described and announced as a pandemic by World Health Organization (WHO) on March 11, 2020. Reverse transcription-polymerase chain reaction (RT-PCR) is currently the gold standard test for diagnosis of COVID-19. Nevertheless, due to its high false-negative rates (%10-50), diagnosis and treatment decisions do not depend on RT-PCR alone. Clinical presentation of patient and radiological findings are also important. However, neither clinical presentation nor computed tomography (CT) findings are specific for COVID-19. As a consequence of these challenges, the diagnosis of the disease and the protection of the community health become more difficult. The investigators of this study hypothesized that deep learning-based decision support system may help for definitive diagnosis of COVID-19. The aim is to develop a deep learning-based decision support system algorithm based on clinical presentation of patient, laboratory and CT findings and RT-PCR data. Previously, deep learning algorithms with the use of widely known deep neural network architectures such as Inception, UNet, ResNet were developed. However all of these studies were based on CT findings. There are not any deep learning study in literature combining the clinical, radiological, and laboratory findings of patients. The project is based on the available data of COVID-19 patients that will be obtained from the Ministry of Health. Then the data will be evaluated for relevance and reliability and labeled for the training of machine. Following the anonymization of data, data will be processed according to the predetermined inclusion-exclusion criteria. Thorax CT data will be labeled as typical / indeterminate / atypical / negative for COVID-19 pneumonia. Also, CT images of patients with known non-COVID-19 diseases will be labeled for the training of machine. Then, fever, lymphocyte count, neutrophil to lymphocyte ratio, contact information, RT-PCR findings will be labeled. Subsequently, the patients will be labeled and the machine will be trained with deep learning method with the help of this grouped and labeled data. Following the training phase, the algorithm will be tested and if the machine reaches the target specificity and sensitivity, the prototype will be tested. And then, the prototype will be embedded into the hospital software system. This software and algorithm will serve as an early warning system for clinicians and provide a better diagnostic rate especially with decreasing false-negative results. The effects of a pandemic cannot be measured by only the number of people diagnosed and isolated, or treatment provided. A pandemic affects not only community health but also individuals' psychological status, education, teaching methods, working models, daily lifestyles, producer/consumer behaviors, supply/demand balance; in other words every single area of life. On top of that, a pandemic causes long-term damages hard to reverse. The software will increase the diagnostic success rates, help to control the pandemic and minimize the collateral damages mentioned above. The investigators believe that, the product that will be produced at the end of this project will be of great benefit in controlling the secondary wave of COVID-19 expected to occur.