Active clinical trials for "COVID-19"

The Novel Coronavirus (2019-nCoV), also known as Wuhan coronavirus, causes the 2019-nCoV acute respiratory disease. The number of patients infected by 2019-nCoV in Italy closely followed an exponential trend, and Italy reported the highest number of infected patients and deaths in the world excluding China.

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

The study is designed to clarify the clinical characteristics, risk factors and long-term prognosis of children with 2019-nCoV infection in China.

The aim of this study is to provide optimum care to postoperative patients diagnosed with COVID-19 (after cesarean) and to help them with recovery, to determine and assist the expectation and satisfaction of pregnant women with COVID-19 regarding prenatal care.

A pneumonia of unknown cause detected in Wuhan, China was first reported to the WHO Country Office in China on 31 December 2019. The outbreak was declared a Public Health Emergency of International Concern on 30 January 2020. The spread and severity of the disease is variable from one country to another. Our team as well as many reports suggested that in some countries a " Flu like illness but much worse" was described in October, November and early in December before the WHO announcement. Was it COVID-19?

In view of increasing cases of SARS-CoV-2 leading to the COVID-19 Pandemic in India,there has been unprecedented restrictions on travel, work and other aspects of daily life. Our study has been designed to collect data of cancer patients to analyze their issues and challenges during Covid-19 Pandemic.

A novel coronavirus SARS-CoV-2 HAS arose in 2019 in Wuhan, China. Beside the classical semiology of this infection, numerous patients described olfactory and teste disorders. These symptoms are not described in this coronavirus, neurotropism of coronaviridae has been documented before. The aim of the study is to evaluate prevalence of anosmia and dysgeusia (olfactory and taste disorders) in coronavirus diagnosed patients and compare with different clinical conditions. The second endpoint is to evaluate the duration of these symptoms in order to better understand the semiology of this infection.

There is an urgent need to understand the outcomes of COVID-19 infected patients regarding the thromboembolic venous disease. Capturing real-world data and sharing Spanish national experience will inform the management of this complex group of patients, improving their clinical care. Interventions are needed to reduce both the incidence and severity of COVID-19. Although it shares characteristics with other similar viruses that also arose in outbreaks, the physiological mechanisms of the virus and its responses on the host are not yet fully known. There are indications that the clinical picture of this disease is in a procoagulant state, with possible increase in episodes of thromboembolic disease. This study aims to analyze the influence of COVID-19 on the incidence of deep vein thrombosis (DVT) in lower and upper limbs, and the variation in the clinical presentation of COVID-19, as well as to provide new evidence applicable to the clinical management of these patients and the establishment of prognostic factors that help early take therapeutic decisions. To this end, an observational, multicenter, national cohorts study will be carried out, sponsored by the Spanish Society of Angiology and Vascular Surgery (SEACV) and the Spanish Chapter of Phlebology and Linfology through its Vascular Research Network (RIV), which will collect demographic variables, comorability, concomitant treatment, analytical status and complementary and ultrasound diagnostic tests, parameters of clinical evolution, therapeutic and complications and mortality to 30 days. All national centers you wish to participate through a secure server that will be accessed through the SEACV and CEFyL website. The global community has recognised that rapid dissemination and completion of studies in COVID-19 infected patients is a high priority, so we encourage all stakeholders (local investigators, ethics committees, IRBs) to work as quickly as possible to approve this project. This investigator-led, non-commercial, non-interventional study is extremely low risk, or even zero risk. This study does not collect any patient identifiable information (including no dates) and data will not be analysed at hospital-level.

According to recent publications, the percentage of caregivers infected with COVID 19 is evaluated between 10 and 30% . This great variability is due, on the one hand to the intensity of the influx of covid plus patients and, on the other hand, to the disparity in the preparation of caregivers in the face of this emergency. Indeed, we can understand that the strict application of hygiene rules can be faulted in the face of the volume of patients, the lack of protective equipment and the lack of specific training for caregivers in this area. As a result, within healthcare teams, there are many questions that generate anxiety: will I be able to provide care properly while protecting myself from the risk of contamination? This anxiety is also present and sometimes manifests itself aggressively in the entourage or in the vicinity of caregivers, due to lack of scientific data adapted to the local ecology of the crisis. Thus, the aim of this study is to show that the risk for caregivers of being contaminated by COVID in an area dedicated to COVID positive patients is no higher than being a caregiver in a non-COVID area that he either in the adult or pediatric sector.

Investigators use clinical data from a large sample of COVID-19 disease patients to screen out biomarkers associated with disease severity. Then, a novel nomogram model will be established to predict covid-19 disease severity, which could provide important assistance and supplement for clinical work. In the case of extremely shortage of front-line medical resources, patients with potential severe diseases will be timely treated with the help of the novel nomogram model.