Ewan Carr1, Rebecca Bendayan2,3, James T Teo4,5, Ajay M Shah5,6, Richard J B Dobson2,3,7,8,9, Daniel Bean2,7, Matt Stammers10,11,12, Wenjuan Wang13, Huayu Zhang14, Thomas Searle2,3, Zeljko Kraljevic2, Anthony Shek4, Hang T T Phan10,11, Walter Muruet13, Rishi K Gupta15, Anthony J Shinton12, Mike Wyatt16, Ting Shi14, Xin Zhang17, Andrew Pickles2,3, Daniel Stahl2, Rosita Zakeri5,6, Mahdad Noursadeghi18, Kevin O'Gallagher5,6, Matt Rogers16, Amos Folarin2,7,8,9, Andreas Karwath19,20,21, Kristin E Wickstrøm22, Alvaro Köhn-Luque23, Luke Slater19,20,21, Victor Roth Cardoso19,20,21, Christopher Bourdeaux16, Aleksander Rygh Holten24, Simon Ball21,25, Chris McWilliams26, Lukasz Roguski7,8,20, Florina Borca10,11,12, James Batchelor10, Erik Koldberg Amundsen22, Xiaodong Wu27,28, Georgios V Gkoutos19,20,21,25, Jiaxing Sun27, Ashwin Pinto12, Bruce Guthrie14, Cormac Breen13, Abdel Douiri13, Honghan Wu7,8, Vasa Curcin13. 1. Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, 16 De Crespigny Park, London, SE5 8AF, UK. ewan.carr@kcl.ac.uk. 2. Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, 16 De Crespigny Park, London, SE5 8AF, UK. 3. NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK. 4. Department of Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. 5. King's College Hospital NHS Foundation Trust, London, UK. 6. School of Cardiovascular Medicine & Sciences, King's College London British Heart Foundation Centre of Excellence, London, SE5 9NU, UK. 7. Health Data Research UK London, University College London, London, UK. 8. Institute of Health Informatics, University College London, London, UK. 9. NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust, London, UK. 10. Clinical Informatics Research Unit, University of Southampton, Coxford Rd., Southampton, SO16 5AF, UK. 11. NIHR Biomedical Research Centre at University Hospital Southampton NHS Trust, Coxford Road, Southampton, UK. 12. UHS Digital, University Hospital Southampton, Tremona Road, Southampton, SO16 6YD, UK. 13. School of Population Health and Environmental Sciences, King's College London, London, UK. 14. Usher Institute, University of Edinburgh, Edinburgh, UK. 15. UCL Institute for Global Health, University College London Hospitals NHS Trust, London, UK. 16. University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK. 17. Department of Pulmonary and Critical Care Medicine, People's Liberation Army Joint Logistic Support Force 920th Hospital, Kunming, Yunnan, China. 18. UCL Division of Infection and Immunity, University College London Hospitals NHS Trust, London, UK. 19. College of Medical and Dental Sciences, Institute of Cancer and Genomics, University of Birmingham, Birmingham, UK. 20. Institute of Translational Medicine, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK. 21. Health Data Research UK Midlands, Birmingham, UK. 22. Department of Medical Biochemistry, Blood Cell Research Group, Oslo University Hospital, Oslo, Norway. 23. Oslo Centre for Biostatistics and Epidemiology, Faculty of Medicine, University of Oslo, Oslo, Norway. 24. Department of Acute Medicine, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway. 25. University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK. 26. Department of Engineering Mathematics, University of Bristol, Bristol, UK. 27. Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai, China. 28. Department of Pulmonary and Critical Care Medicine, Taikang Tongji Hospital, Wuhan, China.
Abstract
BACKGROUND: The National Early Warning Score (NEWS2) is currently recommended in the UK for the risk stratification of COVID-19 patients, but little is known about its ability to detect severe cases. We aimed to evaluate NEWS2 for the prediction of severe COVID-19 outcome and identify and validate a set of blood and physiological parameters routinely collected at hospital admission to improve upon the use of NEWS2 alone for medium-term risk stratification. METHODS: Training cohorts comprised 1276 patients admitted to King's College Hospital National Health Service (NHS) Foundation Trust with COVID-19 disease from 1 March to 30 April 2020. External validation cohorts included 6237 patients from five UK NHS Trusts (Guy's and St Thomas' Hospitals, University Hospitals Southampton, University Hospitals Bristol and Weston NHS Foundation Trust, University College London Hospitals, University Hospitals Birmingham), one hospital in Norway (Oslo University Hospital), and two hospitals in Wuhan, China (Wuhan Sixth Hospital and Taikang Tongji Hospital). The outcome was severe COVID-19 disease (transfer to intensive care unit (ICU) or death) at 14 days after hospital admission. Age, physiological measures, blood biomarkers, sex, ethnicity, and comorbidities (hypertension, diabetes, cardiovascular, respiratory and kidney diseases) measured at hospital admission were considered in the models. RESULTS: A baseline model of 'NEWS2 + age' had poor-to-moderate discrimination for severe COVID-19 infection at 14 days (area under receiver operating characteristic curve (AUC) in training cohort = 0.700, 95% confidence interval (CI) 0.680, 0.722; Brier score = 0.192, 95% CI 0.186, 0.197). A supplemented model adding eight routinely collected blood and physiological parameters (supplemental oxygen flow rate, urea, age, oxygen saturation, C-reactive protein, estimated glomerular filtration rate, neutrophil count, neutrophil/lymphocyte ratio) improved discrimination (AUC = 0.735; 95% CI 0.715, 0.757), and these improvements were replicated across seven UK and non-UK sites. However, there was evidence of miscalibration with the model tending to underestimate risks in most sites. CONCLUSIONS: NEWS2 score had poor-to-moderate discrimination for medium-term COVID-19 outcome which raises questions about its use as a screening tool at hospital admission. Risk stratification was improved by including readily available blood and physiological parameters measured at hospital admission, but there was evidence of miscalibration in external sites. This highlights the need for a better understanding of the use of early warning scores for COVID.
BACKGROUND: The National Early Warning Score (NEWS2) is currently recommended in the UK for the risk stratification of COVID-19 patients, but little is known about its ability to detect severe cases. We aimed to evaluate NEWS2 for the prediction of severe COVID-19 outcome and identify and validate a set of blood and physiological parameters routinely collected at hospital admission to improve upon the use of NEWS2 alone for medium-term risk stratification. METHODS: Training cohorts comprised 1276 patients admitted to King's College Hospital National Health Service (NHS) Foundation Trust with COVID-19 disease from 1 March to 30 April 2020. External validation cohorts included 6237 patients from five UK NHS Trusts (Guy's and St Thomas' Hospitals, University Hospitals Southampton, University Hospitals Bristol and Weston NHS Foundation Trust, University College London Hospitals, University Hospitals Birmingham), one hospital in Norway (Oslo University Hospital), and two hospitals in Wuhan, China (Wuhan Sixth Hospital and Taikang Tongji Hospital). The outcome was severe COVID-19 disease (transfer to intensive care unit (ICU) or death) at 14 days after hospital admission. Age, physiological measures, blood biomarkers, sex, ethnicity, and comorbidities (hypertension, diabetes, cardiovascular, respiratory and kidney diseases) measured at hospital admission were considered in the models. RESULTS: A baseline model of 'NEWS2 + age' had poor-to-moderate discrimination for severe COVID-19 infection at 14 days (area under receiver operating characteristic curve (AUC) in training cohort = 0.700, 95% confidence interval (CI) 0.680, 0.722; Brier score = 0.192, 95% CI 0.186, 0.197). A supplemented model adding eight routinely collected blood and physiological parameters (supplemental oxygen flow rate, urea, age, oxygen saturation, C-reactive protein, estimated glomerular filtration rate, neutrophil count, neutrophil/lymphocyte ratio) improved discrimination (AUC = 0.735; 95% CI 0.715, 0.757), and these improvements were replicated across seven UK and non-UK sites. However, there was evidence of miscalibration with the model tending to underestimate risks in most sites. CONCLUSIONS: NEWS2 score had poor-to-moderate discrimination for medium-term COVID-19 outcome which raises questions about its use as a screening tool at hospital admission. Risk stratification was improved by including readily available blood and physiological parameters measured at hospital admission, but there was evidence of miscalibration in external sites. This highlights the need for a better understanding of the use of early warning scores for COVID.
Entities:
Keywords:
Blood parameters; COVID-19; NEWS2 score; Prediction model
Authors: Gary B Smith; David R Prytherch; Paul Meredith; Paul E Schmidt; Peter I Featherstone Journal: Resuscitation Date: 2013-01-04 Impact factor: 5.262
Authors: Laure Wynants; Ben Van Calster; Gary S Collins; Richard D Riley; Georg Heinze; Ewoud Schuit; Marc M J Bonten; Darren L Dahly; Johanna A A Damen; Thomas P A Debray; Valentijn M T de Jong; Maarten De Vos; Paul Dhiman; Maria C Haller; Michael O Harhay; Liesbet Henckaerts; Pauline Heus; Michael Kammer; Nina Kreuzberger; Anna Lohmann; Kim Luijken; Jie Ma; Glen P Martin; David J McLernon; Constanza L Andaur Navarro; Johannes B Reitsma; Jamie C Sergeant; Chunhu Shi; Nicole Skoetz; Luc J M Smits; Kym I E Snell; Matthew Sperrin; René Spijker; Ewout W Steyerberg; Toshihiko Takada; Ioanna Tzoulaki; Sander M J van Kuijk; Bas van Bussel; Iwan C C van der Horst; Florien S van Royen; Jan Y Verbakel; Christine Wallisch; Jack Wilkinson; Robert Wolff; Lotty Hooft; Karel G M Moons; Maarten van Smeden Journal: BMJ Date: 2020-04-07
Authors: Tingyan Wang; David A Smith; Cori Campbell; Eleanor Barnes; Philippa C Matthews; Steve Harris; Hizni Salih; Kinga A Várnai; Kerrie Woods; Theresa Noble; Oliver Freeman; Zuzana Moysova; Thomas Marjot; Gwilym J Webb; Jim Davies Journal: Hepatol Commun Date: 2021-07-10
Authors: Ryan C Maves; Stephanie A Richard; David A Lindholm; Nusrat Epsi; Derek T Larson; Christian Conlon; Kyle Everson; Steffen Lis; Paul W Blair; Sharon Chi; Anuradha Ganesan; Simon Pollett; Timothy H Burgess; Brian K Agan; Rhonda E Colombo; Christopher J Colombo Journal: Open Forum Infect Dis Date: 2021-08-10 Impact factor: 3.835
Authors: Juan Caro-Codón; Juan R Rey; Antonio Buño; Angel M Iniesta; Sandra O Rosillo; Sergio Castrejon-Castrejon; Laura Rodriguez-Sotelo; Luis A Martinez; Irene Marco; Carlos Merino; Lorena Martin-Polo; Jose M Garcia-Veas; Marcel Martinez-Cossiani; Luis Gonzalez-Valle; Alicia Herrero; Esteban López-de-Sa; Jose L Merino Journal: Eur J Heart Fail Date: 2021-02-01 Impact factor: 17.349
Authors: Kristin E Wickstrøm; Valeria Vitelli; Ewan Carr; Aleksander R Holten; Rebecca Bendayan; Andrew H Reiner; Daniel Bean; Tom Searle; Anthony Shek; Zeljko Kraljevic; James Teo; Richard Dobson; Kristian Tonby; Alvaro Köhn-Luque; Erik K Amundsen Journal: PLoS One Date: 2021-08-25 Impact factor: 3.240
Authors: Helen Snooks; Alan John Watkins; Fiona Bell; Mike Brady; Andy Carson-Stevens; Edward Duncan; Bridie Angela Evans; Louise England; Theresa Foster; John Gallanders; Imogen Gunson; Robert Harris-Mayes; Mark Kingston; Ronan Lyons; Elisha Miller; Andy Newton; Alison Porter; Tom Quinn; Andy Rosser; Aloysius Niroshan Siriwardena; Robert Spaight; Victoria Williams Journal: J Am Coll Emerg Physicians Open Date: 2021-08-02
Authors: Emma Prower; David Grant; Alessandra Bisquera; Cormac P Breen; Luigi Camporota; Maja Gavrilovski; Megan Pontin; Abdel Douiri; Guy W Glover Journal: EClinicalMedicine Date: 2021-04-25