Active clinical trials for "COVID-19"

This study inquires about the development of Telogen effluvium following the SARS-CoV-2 infection

The aim of the study is to develop a prognostic prediction model based on machine learning algorithms in patients affected by coronavirus disease 2019 (COVID-19), the prediction model will be capable to recognize patient with favorable prognosis or patient with poor prognosis by intelligent systems data analysis.

The management of COVID-19 patients in overwhelmed hospital facing the pandemic is a clinical challenge. The improvement of decision making may allow a better allocation of available resources and a better treatment of patients at higher risk. Chest CT has been widely adopted for COVID-19 pneumonia diagnosis. Several experiences documented the capability of Artificial Intelligence to improve and fasten COVID-19 pneumonia detection, mainly using chest X-ray. Aim of the present study was to develop and validate an Artificial Intelligence approach integrating clinical and imaging data (automatically extracted through the adoption of dedicated neural networks) for the creation of a cloud platform capable of performing automatic patients risk stratification. Such an approach could be used for triage of COVID-19 patients in the emergency department, with the aim to improve healthcare personnel decision-making and allocation of resources during health emergencies.

COVID-19 infection coud induce cardiac injuries. Before returning to sport, cardiac evaluation is recommended by sports federations, based on the precautionary principle and the opinion of expert consensus. The aim of this study is to to determine the prevalence of abnormalities in cardiological examinations realized in athletes who have suffered from COVID-19 infection, symptomatic or not.

Use of rapid serological tests to assess the vulnerability to SARS-CoV-2 infection of subjects aged 4-16 years old and cohabiting with at least one family member who tested positive to SARS-CoV-2

The investigators aim to determine the immune status of the employees of the cantonal police of Bern against SARS-CoV-2 over a period of 1 year, and to investigate the risk profile of the study participants and their risk of SARS-CoV-2 exposure in their working and private environments, as well as to evaluate the use of personal protective equipment at potential exposure instances.

Multi-centre prospective study evaluating computed tomography angiography studies performed for stroke patients as a diagnostic and prognostic imaging biomarker.

Background: Invasive mechanical ventilation (IMV) in COVID-19 patients has been associated with a high mortality rate. In this context, the utility of tracheostomy has been questioned in this group of ill patients. This study aims to compare in-hospital mortality in COVID-19 patients with and without tracheostomy due to prolonged IMV Methods: Cohort study of adult COVID-19 patients subjected to prolonged IMV. Since the first COVID-19 case (March 3, 2020) up to November 30, 2020, all adult critical patients supported with IMV by 10 days or more at the Hospital Clínico Universidad de Chile will be included in the cohort. Pregnant women and non-adult patients will be excluded. Baseline characteristics, comorbidities, laboratory data, disease severity, and ventilatory support will be retrospectively collected from clinical records. The indication of tracheostomy, as part of our standard of care, will be indicated by a team of specialists in intensive care medicine, following national guidelines, and consented to by the patient's family. The 90-days mortality rate will be the primary outcome, whereas IMV days, hospital/CU length of stay, and the frequency of healthcare-associated infections will be the secondary outcomes. Also, a follow-up interview will be performed one year after a hospital discharged in order to assess the vital status and quality of life. The mortality of patients subjected to tracheostomy will be compared with the group of patients without tracheostomy by logistic regression models. Furthermore, propensity-score methods will be performed as a complementary analysis.

This project is an unfunded collaboration of approximately 30 emergency departments across Europe led by the EUSEM research network. It involves collection of data in relation to determining the epidemiology and outcome of adult patients who present to emergency departments with a suspected Covid infection.

The study will look at the immunological characteristics of COVID-19 patients and determine neutralizing antibodies against SARS-CoV-2 virus.