Development of a mortality prediction model in hospitalised SARS-CoV-2 positive patients based on routine kidney biomarkers

Boss, A.N., Banerjee, A., Mamalakis, M. orcid.org/0000-0002-4276-4119 et al. (8 more authors) (2022) Development of a mortality prediction model in hospitalised SARS-CoV-2 positive patients based on routine kidney biomarkers. International Journal of Molecular Sciences, 23 (13). 7260. ISSN 1422-0067

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Keywords: SARS-CoV-2; prediction model; kidney function; COVID-19
Dates:
  • Accepted: 28 June 2022
  • Published (online): 30 June 2022
  • Published: 1 July 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
The University of Sheffield > Sheffield Teaching Hospitals
Funding Information:
FunderGrant number
WELLCOME TRUST (THE)205188/Z/16/Z
Depositing User: Symplectic Sheffield
Date Deposited: 18 Aug 2022 15:00
Last Modified: 18 Aug 2022 15:00
Status: Published
Publisher: MDPI AG
Refereed: Yes
Identification Number: https://doi.org/10.3390/ijms23137260
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