Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study.

Carr, Ewan, Bendayan, Rebecca, Bean, Daniel, Stammers, Matt, Wang, Wenjuan, Zhang, Huayu, Searle, Thomas, Kraljevic, Zeljko, Shek, Anthony, Phan, Hang T T, Muruet, Walter, Gupta, Rishi K, Shinton, Anthony J, Wyatt, Mike, Shi, Ting, Zhang, Xin, Pickles, Andrew, Stahl, Daniel, Zakeri, Rosita, Noursadeghi, Mahdad, O'Gallagher, Kevin, Rogers, Matt, Folarin, Amos, Karwath, Andreas, Wickstrøm, Kristin E, Köhn-Luque, Alvaro, Slater, Luke, Cardoso, Victor Roth, Bourdeaux, Christopher, Holten, Aleksander Rygh, Ball, Simon, McWilliams, Chris, Roguski, Lukasz, Borca, Florina, Batchelor, James, Amundsen, Erik Koldberg, Wu, Xiaodong, Gkoutos, Georgios V, Sun, Jiaxing, Pinto, Ashwin, Guthrie, Bruce, Breen, Cormac, Douiri, Abdel, Wu, Honghan, Curcin, Vasa, Teo, James T, Shah, Ajay M and Dobson, Richard J B (2021) Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study. BMC medicine, 19 (1). p. 23. ISSN 1741-7015. This article is available to all UHB staff and students via ASK Discovery tool http://tinyurl.com/z795c8c by using their UHB Athens login IDs

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Official URL: 10.1186/s12916-020-01893-3

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.

Item Type: Article
Additional Information: This article is available to all UHB staff and students via ASK Discovery tool http://tinyurl.com/z795c8c by using their UHB Athens login IDs
Subjects: QA Mathematics. Computing
WC Communicabable diseases
Divisions: Clinical Support
Related URLs:
Depositing User: Mrs Yolande Brookes
Date Deposited: 22 Jan 2021 16:54
Last Modified: 22 Jan 2021 16:54
URI: http://www.repository.uhblibrary.co.uk/id/eprint/3901

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