About: Protocol for the development and evaluation of a tool for predicting risk of short-term adverse outcomes due to COVID-19 in the general UK population

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About: Protocol for the development and evaluation of a tool for predicting risk of short-term adverse outcomes due to COVID-19 in the general UK population Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Protocol for the development and evaluation of a tool for predicting risk of short-term adverse outcomes due to COVID-19 in the general UK population
Creator	Horby, Peter Sheikh, Aziz Hayward, Andrew Kee, Frank Semple, Calum Coggon, David Harrison, Ewen Hemingway, Harry Khunti, Kamlesh Valabhji, Jonathan Williamson, Elizabeth Lyons, Ronan Benger, Jonathan Clift, Ash Coupland, Carol Diaz-Ordaz, Karla Hippisley-Cox, Julia Jebb, Susan Johnson, Peter Keogh, Ruth Mehta, Nisha Robson, John Speigelhalter, David Williams, Tony
Source	MedRxiv
abstract	Introduction: Novel coronavirus 2019 (COVID-19) has propagated a global pandemic with significant health, economic and social costs. Emerging emergence has suggested that several factors may be associated with increased risk from severe outcomes or death from COVID-19. Clinical risk prediction tools have significant potential to generate individualised assessment of risk and may be useful for population stratification and other use cases. Methods and analysis: We will use a prospective open cohort study of routinely collected data from 1205 general practices in England in the QResearch database. The primary outcome is COVID-19 mortality (in or out-of-hospital) defined as confirmed or suspected COVID-19 mentioned on the death certificate, or death occurring in a person with SARS-CoV-2 infection between 24th January and 30th April 2020. Our primary outcome in adults is COVID-19 mortality (including out of hospital and in hospital deaths). We will also examine COVID-19 hospitalisation in children. Time-to-event models will be developed in the training data to derive separate risk equations in adults (19-100 years) for males and females for evaluation of risk of each outcome within the 3-month follow-up period (24th January to 30th April 2020), accounting for competing risks. Predictors considered will include age, sex, ethnicity, deprivation, smoking status, alcohol intake, body mass index, pre-existing medical co-morbidities, and concurrent medication. Measures of performance (prediction errors, calibration and discrimination) will be determined in the test data for men and women separately and by ten-year age group. For children, descriptive statistics will be undertaken if there are currently too few serious events to allow development of a risk model. The final model will be externally evaluated in (a) geographically separate practices and (b) other relevant datasets as they become available. Ethics and dissemination: The project has ethical approval and the results will be submitted for publication in a peer-reviewed journal.
has issue date	2020-06-29(xsd:dateTime)
bibo:doi	10.1101/2020.06.28.20141986
has license	medrxiv
sha1sum (hex)	3d5ff2f6be2bee43a37e8ef746b29c6f7549621d
schema:url	https://doi.org/10.1101/2020.06.28.20141986
resource representing a document's title	Protocol for the development and evaluation of a tool for predicting risk of short-term adverse outcomes due to COVID-19 in the general UK population
resource representing a document's body	covid:3d5ff2f6be2bee43a37e8ef746b29c6f7549621d#body_text
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