ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19
The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing como…
A Phase I/II Dose-Escalation Multi-Center Study to Evaluate the Safety of Infusion of Natural Killer Cells or Memory T Cells As Adoptive Therapy in Coronavirus Pneumonia and/or Lymphopenia: (RELEASE NCT04578210)
Abstract Background: Adoptive cell immunotherapies for opportunistic virus in immunocompromised patients using haploidentical memory T cells have shown to be safe and effective. Since severe cases of COVID-19 present a dysregulated immune system with T cell lymphopenia and a hyper-inflammatory state we have proposed that a similar strategy could be proven to be efficient for COVID-19 patients. This is a study protocol of an open-label, multicenter, double-arm, randomized, dose-finding phase I/II clinical trial to evaluate the feasibility, safety, tolerability, and efficacy of the administration of a single dose of allogenic SARS-CoV-2 specific memory CD45RA - T cells and Natural Killer (NK)…
Characteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19
Abstract Background We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients. Methods The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admiss…
The value of open-source clinical science in pandemic response
International audience