Approved uses of platform data

The following research proposals include both those approved by the platform’s independent Data Access Committee and those which are ISARIC Partner Analyses. Please review these proposals before submitting a Data Access Request. In the interest of maximising the production of evidence to reduce the impact of COVID-19, the platform aims to avoid unnecessary duplication of analyses.  

Creative rendition of SARS-COV-2 virus particles. Note: not to scale
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Credit: National Institute of Allergy and Infectious Diseases, NIH

DAC approved proposals

These analyses have been approved by the COVID-19 Data Access Committee. 

 

Global COVID-19 Clinical Data Platform for clinical characterization and management of hospitalized patients with suspected or confirmed COVID-19

World Health Organization, Switzerland

The aim of the Global COVID-19 Clinical Data Platform is to collect standardized and anonymized clinical data from across the globe related to COVID-19. This project will describe clinical and therapeutic features, demographics, and outcomes in COVID-19 patients, evaluate variations in clinical characterisation management in different subpopulations, and evaluate risk factors associated with clinical outcomes in different geographical areas. The analysis of this data is essential for the development of evidence-based WHO global guidelines on clinical management of COVID-19 and to effectively support the public health response in WHO regions and countries. The results also inform policies related to clinical management on subpopulations (e.g. HIV infected patients) and inform the identification of priority groups for vaccination.

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Formative Evaluation of a Minimally Viable COVID-19 Dataset

C-Path, United States

The CURE-ID database, a collaboration between the FDA and the National Center for Advancing Translational Sciences (NCATS), is an internet-based repository that lets the clinical community report novel uses of existing drugs for difficult-to-treat infectious diseases. The platform enables the crowdsourcing of medical information from health care providers to facilitate the development of new treatments.

The utility of the database is being explored in the context of novel treatments for COVID-19. To evaluate the design of the CURE-ID database for COVID-19, CURE-ID dataset will be simulated using ISARIC data and model analyses to determine if the feasibility of assessing outcomes using the variables included. This project aims to assess correlation of all covariates with key outcomes to inform the continued development and design of the CURE-ID dataset and the planned analyses to ensure the optimal methodological and statistical design through understanding of what can be expected from a global COVID-19 dataset.

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Pathogen evolution towards Evolutionarily Stable Strategies (ESS) in a socially age-structured epidemic

University of Oslo, Norway, University of Copenhagen, Denmark

The aim of this research is to understand the evolutionary dynamics (both in the initial phase of transmission and long-term state) of human pathogens in a socially age-structured framework. Using numerical analysis with a mechanistic model it has been found that the long-term dynamics of pathogens are highly dependent upon the demography of the host population. Real-life clinical data and infections data related to COVID-19 from various populations will be used to test the theoretical mechanistic model result that virus variants in older populations are more virulent among older people but last longer among younger people. The findings in this research would contribute to understanding the evolution of novel pathogens such as SARS-CoV-2 that are in the initial phase of transmission but with possible long-term dynamics.

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Avoiding preventable deaths through the provision of essential treatment in critical illness in the COVID-19 pandemic

London School of Hygiene & Tropical Medicine and Centre for Global Development, UK, Ifakara Health Institute, Tanzania, and Karolinska Institute, Sweden

Scaling-up critical care to meet the need of critically ill in the context of COVID-19 could follow alternative scenarios emphasising Essential Emergency Critical Care (EECC) – a low cost package of care feasible in all hospital settings - or advanced critical care. Domestic and international actors continue to lobby for a full range of services. However, budgets are limited so choices will be made between different types of care.  To inform the choice of strategy and ensure the maximum benefit from any new investments, this research will model the costs and consequences of investing in basic provision of oxygen therapy and EECC relative to mechanical ventilators and advanced critical care.

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Sepsis in COVID-19

Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China

This is a multi-centre international observational study of patients with COVID-19 based on the COVID-19 Data Platform to report and describe the demographic characteristics, clinical features, prevalence, risk factors, and sepsis prognosis. The study aims to: summarise the demographic and clinical characteristics of patients with sepsis hospitalized for COVID-19; to investigate the incidence of sepsis in non-ICU and ICU patients; to identify the time variation at different ICU stay stages, including treatments received, time in the intensive care unit, and mechanical ventilation time; to describe the complications and clinical outcomes associated with sepsis in patients with COVID-19; to explore the risk factors and protective factors associated with mortality in these patients; to construct clinical prediction models for the risk of sepsis and death in COVID-19 patients and perform external validation.

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COVID-Intelligence, a Bayesian Network Clinical Decision Support System for COVID-19

Monash University, Australia

With the aim to improve the diagnosis and management of COVID-19, mathematical models have been developed by the research team that describe the COVID-19 disease process, from infection through to the outcome (recovery or death). The models have been built using the knowledge volunteered by a large number of medical experts from various fields, and will now be developed further using data from known and suspected cases of COVID-19. Patient data will be used to test, strengthen and confirm the researchers’ individual patient predictions of COVID-19 disease progression. Ultimately, it is anticipated that the model will be used to understand COVID-19 disease and guide individual patient management.

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Clinical presentation and outcome of hospitalised Dutch patients with COVID-19

Franciscus Gasthuis and Vlietland, Rotterdam, The Netherlands

The emergence of COVID-19 has had a tremendous impact on global health and international society. In a Dutch multicentre collaboration, the research team describe the clinical characteristics of patients who were admitted to Dutch hospitals with COVID-19 and assess the clinical outcomes of these patients. The objectives of the research are: to describe the clinical features of patients who were admitted to Dutch hospitals with COVID-19, including demographics, admission characteristics (symptoms, signs, and laboratory), treatment-related variables and complications; to assess patient outcomes and determine associations between demographic (including age, gender, ethnicity, comorbidity), admission characteristics (including inclusion O2 saturation, GCS, creatinine, CRP) and patient outcomes.

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ISARIC Partner Analyses

These analyses are submitted by researchers who contribute data to the ISARIC collaboration, and approved by the ISARIC governance committees.

ISARIC COVID-19 Clinical Data Reports

Data from the ISARIC collaboration are continuously analysed, reported and made available to the clinical, research, and public health communities.

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Extracorporeal Membrane Oxygenation for COVID-19 Respiratory Distress Syndrome: a ISARIC Risk Factor Analysis

ALMA Mater Studiorum University of Bologna, Italy, Pablo Tobón Uribe Hospital, Colombia, and UMAE Hospital de Pediatria CMN, Mexico

Infection with SARS-CoV-2 can result in severe respiratory distress syndrome due to alveolar damage. The rate of severe respiratory distress syndrome ranges from 15% to 30%. Currently, no specific therapy exists, but several medical organisations recommend administering venovenous (VV) extracorporeal membrane oxygenation (ECMO) to eligible patients with COVID-19 related severe respiratory distress syndrome. The probably of day 60 mortality for ECMO-treated patients is estimated to be 31%.

This analysis will investigate what pre-ECMO, on-ECMO, and ICU variables are associated with ECMO-related adverse events and mortality while on ECMO support to provide a descriptive analysis of ECMO-treated COVID-19 patients.

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Characteristics, presentation, risk factors, treatments and outcomes in patients with cancer and COVID-19 (ARC: ISARC International Cancer)

University of Oxford and University of Liverpool, UK, and Universidad del Cauca and Pontificia Universidad Javeriana, Colombia

Patients with cancer are at a higher risk of severe COVID-19 and death if infected with SARS-CoV-2. Among hospitalized patients with COVID-19, cancer has been shown to be associated with a higher risk of death, with relative risks up to ~5 compared to patients without cancer, which vary by age, comorbidities and other characteristics. Most evidence has been from high-income countries and global studies on patients from diverse settings are lacking. This study will assess the associations of cancer with clinical presentation, risk factors, treatments, and outcomes among hospitalized patients with COVID-19.

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Characterising SARS-CoV-2 Omicron vs Delta variant in terms of vaccination status, clinical presentation and outcomes

University of Oxford, UK

As of 1 December 2021, more than 300 cases of the SARS-CoV-2 Omicron variant of concern (VOC) have been identified in 27 countries, representing a potential threat to pandemic control efforts. To provide key information for public health response, this analysis aims to assess whether disease caused by the Omicron variant differs in terms of severity and vaccine efficacy against hospitalisation compared with the currently dominant Delta (B.1.617.2) variant. Primary objectives are estimation of the association between vaccination status and hospitalisation with the Omicron variant relative to the Delta variant, and characterisation of severity of clinical presentation and outcomes in hospitalised patients with the Omicron variant relative to those with the Delta variant. In addition, clinical profiles, comorbidity prevalence, and associations of variables (age, sex, symptoms, comorbidities, treatments) with poor outcomes will be assessed.

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Characterization of long term Covid-19 outcomes in different populations: ISARIC Global Collaborative Adult Covid-19 Follow up analysis

University of Oxford, UK, Universidade de La Sabana, Colombia, and Sechenov University, Russia

This analysis builds on data collected using the ISARIC/WHO Covid-19 Clinical Characterisation Protocol (CCP) and associated data collection forms already in operation, the Core and Rapid case report forms (CRFs) which were developed to standardise clinical data collection during the acute phase on patients admitted with suspected or confirmed Covid-19.

Recognising that post-acute Covid-19 sequelae and post-Covid condition affects people who were hospitalised and those who were not, for this follow up study case report forms were developed to enable inclusion of both community and hospitalised cohorts. A subset of the global cohort was followed up  after their acute illness or Covid-19 testing, to create the global follow up cohort.

This analysis investigates the medium and long-term impacts of Covid-19 infection on physical health and psychosocial health and functioning, and the risk factors for developing post-acute Covid-10 sequelae in first 6 – 12 months of follow-up.

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Clinical outcomes in children with severe Covid-19: a retrospective study in limited vs. enormous resource countries

National Cardiovascular Center Harapan Kita, Universitas Udayana, and Saiful Anwar Hosptial, Indonesia, and Chonnam National University Children’s Hospital, South Korea

Severe Covid-19 disease is widely reported in adults, but in children this disease is reported to be milder, with most reports from developed countries. The latest report from a child referral hospital in Indonesia found that 20 out of 490 children (4%) who were confirmed or suspected of having Covid19 had died. Evaluation of the clinical outcomes of children with Covid-19 who are critically ill and the risk factors that determine clinical outcomes are urgently needed for planning health services for children with Covid-19.

This analysis investigates the incidence of and risk factors for mortality and morbidity in children with severe COVID-19. This analysis also investigates the differences in these outcomes between developing and developed countries.

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Lymphopenia in severe COVID19 patients: are they a unique immunologically compromised population?

Hospital São Francisco Xavier, Portugal, and University Technology MARA, Malaysia

The importance of cytotoxic T lymphocytes and natural killer cells in the control of viral infections is well known. However, the prognostic value on patients’ outcome and mortality rate is unclear, and could potentially impact the clinical approach and predict the severity of COVID19 and its outcomes. This study will investigate the association between lower lymphocyte count and a poor prognosis, and verify if lower lymphocyte count is independently correlated to COVID19 infection outcomes. This study will also ascertain how lymphocyte total count influences poor prognosis variables and if lymphocyte count could be a predictor of infection outcomes.

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Cardiovascular impact in COVID19 patients: a multicenter cohort analysis

Hospital São Francisco Xavier, and Universidade Algarve Portugal, and University Technology MARA, Malaysia

COVID19 can be associated with life-threatening organ dysfunction due to septic shock, frequently requiring ICU admission, respiratory and vasopressor support. Evidence has emerged indicating direct myocardial injury due to COVID19, with associated increased mortality. Troponin as a well-documented noninvasive biomarker of cardiac injury and myocyte necrosis stands as a possible predictor of a poor outcome in these patients. This study aims to investigate the rate and impact of cardiovascular dysfunction in COVID19 patients, identify characteristics of severe COVID19 patients that predict cardiovascular dysfunction, and assess the prognostic value of troponin on cardiac outcomes and mortality.

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Liver function abnormalities in patients admitted with COVID-19 and association with outcomes: A draft analysis plan using data collected by the ISARIC Collaborators

Apollo Hospitals, India, University of Toronto, Canada, and University of Oxford, and ISARIC, UK

Liver function derangement has been reported in COVID-19 patients, particularly in severe cases. Liver function has also been observed to worsen during hospitalization with severe COVID-19. Static and dynamic trends of liver function derangement may be associated with clinical severity and outcomes. This study aims to determine the prevalence and severity of liver function derangement in patients with COVID-19, and evaluate the association between liver function and hospital outcomes.

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Applicability of commonly used COVID-19 clinical case definitions and severity score amongst patients hospitalized with COVID-19 in LMICs

Clinical Research Unit Nepal and Centre for Tropical Medicine and Global Health, University of Oxford, UK

Due to lack of availability and limited resources for testing in resource-limited settings, clinical decision-making is more reliant on clinical case definition. Hence, understanding the sensitivity of commonly used clinical case definition for COVID-19 in low and middle-income countries (LMICs) and assessing the need for alternative case definitions is essential. The overall aim for this project is to describe LMIC data on the COVID-19 Data Platform in terms of completeness and conduct following analysis given the availability of required data: (1) to assess the adequacy of common COVID-19 clinical case definitions to COVID-19 hospitalized patients in LMICs with reference to sensitivity; (2) to assess applicability/adequacy of common severity scores to COVID-19 hospitalized patients in LMICs.

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COVID-19 among healthcare workers in a worldwide multicentre study: geographical distribution, characteristics and outcomes

National Institute for Communicable Diseases, South Africa and CUB-Hôpital Erasme, Belgium

There is no robust large-scale data that exist concerning the initial risk factors, characteristics, outcomes and the respective geographical variation of health care workers’ (HCWs) COVID-19 exposure compared to those of the general population. Such findings may aid in implementing national public health policies given the facts that mortality rates among HCWs could paralyze the response to COVID-19 with a possible long-term impact on healthcare services. This study will investigate and report prevalence, characteristics and outcomes of COVID-19 infection among HCWs, addressing: (1) the prevalence of HCW among COVID-19 patients; (2) the baseline characteristics of HCW in the study cohort; (3) the distribution of outcomes of COVID-19 HCW patients in the study cohort according to the WHO; (4) the case-fatality ratio among HCWs; (5) the hospital length of stay among HCWs; (6) the survival distribution of HCWs equal to non HCWs.

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Risk to admission of COVID19 patients from the Emergency Department

Universidad del Cauca, Colombia, and Hospital Universitario La Paz, Spain

This study seeks to compare those COVID-19 patients who are admitted from those who are early discharged, and to describe those patients in high risk for complications. To achieve these objectives, clinical questions examined include: the characteristics of patients admitted for more than 72 hours versus those discharged before 72 hours; the characteristics of patients admitted in risk for complications due to COVID-19; the COVID-19 patients admitted in the hospital that could have been discharged without admission. Patient data in the COVID-19 Data Platform will be split into the following cohorts: (1) patients admitted in the hospital who do not require specific treatment or supplemental oxygen; (2) patients admitted in the hospital who require specific treatment or supplemental oxygen; (3) patients discharged in the first 72 hours; (4) patients discharged after 72 hours.

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Potassium in COVID-19 patients admitted to hospital

Inserm, Nancy Regional and University Hospital Center and INI-CRCT Network, France, and Hospital Civil de Guadalajara, Mexico

Hypokalemia has been described in COVID-19 patients in China and in other countries, but discordant findings to date require assessment in a larger multicentre study. The main objective of this research is to study the association of baseline potassium and in-hospital death. In addition, the research will: examine prevalence of dyskalemia (hypo/hyperkalemia) at baseline and during the hospitalization; determine the factors associated with hypo-hyperkalemia at baseline; study the association of repeated potassium measurements and in-hospital death; analyse hospital potassium changes (i.e. potassium normalization) in relation to in-hospital death; examine association of baseline potassium and time to discharge.

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The utility and limitations of clinical trials and cohort studies to determine treatment efficacy during a disease outbreak

University of Melbourne, Australia, All India Institute Of Medical Sciences, India, and Sunnybrook Health Sciences Centre, Canada

This research aims to demonstrate the utility, and the limitations of observational data to determine drug safety and efficacy, by exploration of an international observational dataset and by comparing observationally collected data in the ISARIC international cohort, with the outcomes of the RECOVERY trial for corticosteroids. Research objectives are: to describe use of corticosteroids for hospitalised patients with COVID-19; to compare the association of corticosteroids with mortality, among patients in observational studies, with effects of corticosteroids as measured in RCTs; to compare assessment of safety of corticosteroids in patients using observational data with RCT data; to compare similar observational and RCT analyses for other agents (such as, but not limited to hydroxychloroquine and remdesivir) should feasible approaches be identified using corticosteroids as an example.

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Influence of nutrition status on COVID-related outcome

CUB-Hopital Erasme, Belgium

The aim of this research is to compare COVID-19-related mortality according to underweight status and malnutrition, before and after adjustments for known demographic confounders. The study will target patients hospitalized for COVID-19 infection worldwide, requiring or not a stay in an intensive care unit (ICU) or high-dependency unit.

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Utility of measures of oxygenation for COVID-19 case management and outcome

University of Oxford, UK, Apollo Hospitals Group, India, and Luxembourg Institute of Health, Luxembourg

The primary objective of this research is to assess the utility of measures of oxygenation as a predictor of poor outcome in COVID-19. A secondary objective is to assess the utility of measures of oxygenation to guide patient management decisions. An additional secondary objective is to evaluate the ROX index, S/F94 rox and ROX-HR in a subset of patients.

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Coagulopathy and thrombosis among COVID-19 patients

University of Utah School of Medicine, USA and Fundação Oswaldo Cruz, Brazil

Due to the novelty of COVID-19 and the conflicting implications of attempting to avoid both serious thrombosis and serious haemorrhage, guidelines on evaluation and management of COVID-19 patients with coagulopathy have substantial variations. This research proposes to characterise patients with bleeding, thrombosis, and coagulopathy with an approach that leverages the strengths of the large database available. Determination of geographic variation in COVID-19 associated coagulopathy observations may provide insight into whether different regions may have different coagulopathy phenotypes. Describing and characterizing the bleeding and coagulopathy seen among COVID-19 patients who are critically ill may help refine risk assessment for the sickest patients. Describing regional variation in practices of anticoagulation may aid in designing prospective clinical trials.

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Neurological manifestation and outcome for patients admitted to hospital with COVID-19

Johns Hopkins University School of Medicine, USA and University of Cape Town, South Africa

This is a multi-centre international observational study in patients with COVID-19 to report and characterize the prevalence, risk factor, and outcome of neurological manifestations. Recent findings suggested that COVID-19 patients may also develop neurological symptoms by mechanisms not yet elucidated. To date, neurological manifestations have been characterised into three main areas: central nervous system disorders, peripheral nervous system disorder and skeletal muscle symptoms. It is well known that neurological outcome in critically ill patients can be influenced by the development of secondary brain damage, and that COVID-19 patients frequently present hypoxia, as a result of severe respiratory distress, hypotension, and microvascular abnormalities. It can be hypothesized that one of the possible mechanisms involved in neurological manifestations of COVID-19 patients could be the promotion of neuroinflammation and excitotoxicity with increased permeability of the blood brain barrier. The aim of this observational multi-centre international study is to identify the prevalence of neurological manifestations in critically ill confirmed COVID-19 patients and to assess risk factors and outcomes of neurological complications of COVID-19.

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Acute Kidney Injury in COVID-19

University of Queensland, Australia and Universidad Mayor de San Simon, Cochabamba, Bolivia 

Close to half of all patients admitted to hospital with COVID 19 have kidney involvement and a variable proportion, between 0.5 to 36%, will develop acute kidney injury (AKI) during their hospital stay. AKI is especially common among patients who require mechanical ventilation, with much of its burden observed in the intensive care unit setting and around the time of intubation. In this context, development of AKI has been characterised as both a marker of disease severity as well as a negative prognostic indicator. To date, studies looking at kidney disease in COVID 19 patients have been limited to single centre or regional cohorts mostly from China, Europe or USA, which fail to reflect the global experience of kidney disease, particularly in low and middle income countries where the burden of disease may be much higher and the therapeutic resources limited. This analysis has three aims: to characterise patients with COVID-19 who develop AKI; to identify the temporal profile of AKI in patients with COVID-19 throughout the hospital journey; to develop a predictive machine learning model for AKI in COVID-19, using data from predominantly upper middle-income countries, and externally validate this model in a LMIC setting (Latin America).

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Analysis of the ISARIC International COVID-19 Critically Ill Cohort

British Columbia Children's Hospital, Canada and Universidad De La Sabana, Columbia 

There are few international cohorts of the critically-ill patient population described in the literature and this collaborative project aims to address this gap. The study aims to describe the first and subsequent waves of the COVID-19 pandemic by: summarising the demographic characteristics and clinical features of ~16,000 critically ill patients of any age, admitted to hospital with COVID-19 across high-income and low- and middle-income settings, across temporal phases of the pandemic; describing clinical outcomes (e.g. ICU length of stay, hospital length of stay, ICU mortality, hospital mortality, days of mechanical ventilation) of critically-ill patients with severe COVID-19; characterising the variability in the clinical features and management strategies of these patients; exploring the risk and protective factors associated with mortality for these patients; determining variation over time in various phases of the ICU ‘journey’ including treatments received, length of stay in ICU and duration of mechanical ventilation.

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Development of a predictive analytics model for need of extracorporeal support in COVID-19

Washington University in St Louis, USA, INOVA Fairfax Hospital, USA and National Cardiovascular Center Harapan Kita, Indonesia

The most resource-intensive and comprehensive support for patients with COVID-19 is extracorporeal membrane oxygenation (ECMO), functioning as an artificial heart and/or lung, removing carbon dioxide, supplementing oxygen to a patient’s blood, and providing life-sustaining oxygen delivery. The decision to place a patient on ECMO is one that takes place after standard therapies such as steroids, mechanical ventilation, and prone positioning among others have failed. During a pandemic it is critical to be cognizant of the significant resources required to place and maintain patients on ECMO, and more than 10 months into the pandemic, there remains difficulty in predicting who will require ECMO. This research plans to construct a model to aid in the prediction of which COVID-19 patients are most likely to necessitate the use of ECMO utilising the ISARIC database. The specific aims of the project are: to predict the necessity for ECMO support utilising variables 24-48 hours prior to ECMO initiation; to develop, validate and test a machine learning model for predicting the need for ECMO at various time windows using a large international database; to test the developed model in a local, holdout dataset, using a simulated real-time approach, and evaluate the decision alert rate.

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Characteristics and outcomes of an international cohort of hospitalised patients with Covid-19 

University of Oxford, UK

An overall descriptive dataset has been identified in collaborator meetings as a priority outcome. There are few international cohorts described in the literature and so this collaborative project hopes to address this. The project aims are: to summarize the demographic characteristics and clinical features of 10,941 patients admitted to hospital with COVID-19 across high-income, middle-income, and low-income settings; to characterise the variability in the clinical features of these patients; to explore the risk factors associated with mortality and ICU admission for these patients. All contributors to the ISARIC database are invited to participate in this analysis through review and input on the statistical analysis plan and resulting publication. The outputs of this work will be disseminated as widely as possible to inform patient care and public health policy.

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International comparison of age-specific presenting symptoms for patients admitted to hospital with coronavirus disease 2019

University of Oxford, UK

Case definitions for COVID-19 generally require an epidemiological link demonstrating possible exposure to a case. However, as the global pandemic has spread, many countries have sustained community transmission meaning everyone is potentially exposed. For settings where microbiological testing for the causative pathogen (SARS-CoV-2) is not available, and for patients who have mild symptoms and do not seek medical attention, symptomology is the main feature for identifying possible cases. The objectives of this study are: to investigate patterns of symptoms at arrival to hospital for patients admitted to hospital with COVID-19, stratified by age, sex and country; to investigate the utility of commonly used clinical case definitions of COVID-19 for patients of different ages and in different countries.

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Time variation in the inpatient journey

University of Oxford, UK

This study addresses the following research questions: Does the ‘inpatient journey’ change over time in the course of the COVID-19 pandemic? Do patient’s presenting characteristics change in the course of the COVID-19 pandemic? Do patient’s presenting characteristics explain changes in the ‘inpatient journey’? These will be examined through exploring variation in: the overall ‘inpatient journey’, using both interactive visualization and by taking snapshots (e.g. for the first 100, 1,000, 10,000 patients, and for every 10,000-patient increment in the global dataset); time from symptom onset to hospital admission; time from hospital admission to ICU admission; length of ICU stay; time from hospital admission to oxygen supplementation; time on oxygen supplementation; length of hospital stay.

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