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

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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; Dobson, Richard J B.

In: BMC medicine, Vol. 19, No. 1, 23, 12.2021.

Research output: Contribution to journalArticlepeer-review

Harvard

Carr, E, Bendayan, R, Bean, D, Stammers, M, Wang, W, Zhang, H, Searle, T, Kraljevic, Z, Shek, A, Phan, HTT, Muruet, W, Gupta, RK, Shinton, AJ, Wyatt, M, Shi, T, Zhang, X, Pickles, A, Stahl, D, Zakeri, R, Noursadeghi, M, O'Gallagher, K, Rogers, M, Folarin, A, Karwath, A, Wickstrøm, KE, Köhn-Luque, A, Slater, L, Cardoso, VR, Bourdeaux, C, Holten, AR, Ball, S, McWilliams, C, Roguski, L, Borca, F, Batchelor, J, Amundsen, EK, Wu, X, Gkoutos, GV, Sun, J, Pinto, A, Guthrie, B, Breen, C, Douiri, A, Wu, H, Curcin, V, Teo, JT, Shah, AM & Dobson, RJB 2021, 'Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study', BMC medicine, vol. 19, no. 1, 23. https://doi.org/10.1186/s12916-020-01893-3

APA

Carr, E., Bendayan, R., Bean, D., Stammers, M., Wang, W., Zhang, H., Searle, T., Kraljevic, Z., Shek, A., Phan, H. T. T., Muruet, W., Gupta, R. K., Shinton, A. J., Wyatt, M., Shi, T., Zhang, X., Pickles, A., Stahl, D., Zakeri, R., ... Dobson, R. J. B. (2021). Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study. BMC medicine, 19(1), [23]. https://doi.org/10.1186/s12916-020-01893-3

Vancouver

Author

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 ; Dobson, Richard J B. / Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19 : a multi-hospital study. In: BMC medicine. 2021 ; Vol. 19, No. 1.

Bibtex

@article{c877e4e072de46bd95a4917c5e0d2339,
title = "Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study",
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.",
keywords = "Aged, COVID-19/diagnosis, Cohort Studies, Early Warning Score, Electronic Health Records, Female, Humans, Male, Middle Aged, Pandemics, Prognosis, SARS-CoV-2/isolation & purification, State Medicine, United Kingdom/epidemiology, NEWS2 score, Prediction model, Blood parameters, COVID-19",
author = "Ewan Carr and Rebecca Bendayan and Daniel Bean and Matt Stammers and Wenjuan Wang and Huayu Zhang and Thomas Searle and Zeljko Kraljevic and Anthony Shek and Phan, {Hang T T} and Walter Muruet and Gupta, {Rishi K} and Shinton, {Anthony J} and Mike Wyatt and Ting Shi and Xin Zhang and Andrew Pickles and Daniel Stahl and Rosita Zakeri and Mahdad Noursadeghi and Kevin O'Gallagher and Matt Rogers and Amos Folarin and Andreas Karwath and Wickstr{\o}m, {Kristin E} and Alvaro K{\"o}hn-Luque and Luke Slater and Cardoso, {Victor Roth} and Christopher Bourdeaux and Holten, {Aleksander Rygh} and Simon Ball and Chris McWilliams and Lukasz Roguski and Florina Borca and James Batchelor and Amundsen, {Erik Koldberg} and Xiaodong Wu and Gkoutos, {Georgios V} and Jiaxing Sun and Ashwin Pinto and Bruce Guthrie and Cormac Breen and Abdel Douiri and Honghan Wu and Vasa Curcin and Teo, {James T} and Shah, {Ajay M} and Dobson, {Richard J B}",
note = "Publisher Copyright: {\textcopyright} 2021, The Author(s).",
year = "2021",
month = jan,
day = "21",
doi = "10.1186/s12916-020-01893-3",
language = "English",
volume = "19",
journal = "BMC medicine",
issn = "1741-7015",
publisher = "Springer",
number = "1",

}

RIS

TY - JOUR

T1 - Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19

T2 - a multi-hospital study

AU - Carr, Ewan

AU - Bendayan, Rebecca

AU - Bean, Daniel

AU - Stammers, Matt

AU - Wang, Wenjuan

AU - Zhang, Huayu

AU - Searle, Thomas

AU - Kraljevic, Zeljko

AU - Shek, Anthony

AU - Phan, Hang T T

AU - Muruet, Walter

AU - Gupta, Rishi K

AU - Shinton, Anthony J

AU - Wyatt, Mike

AU - Shi, Ting

AU - Zhang, Xin

AU - Pickles, Andrew

AU - Stahl, Daniel

AU - Zakeri, Rosita

AU - Noursadeghi, Mahdad

AU - O'Gallagher, Kevin

AU - Rogers, Matt

AU - Folarin, Amos

AU - Karwath, Andreas

AU - Wickstrøm, Kristin E

AU - Köhn-Luque, Alvaro

AU - Slater, Luke

AU - Cardoso, Victor Roth

AU - Bourdeaux, Christopher

AU - Holten, Aleksander Rygh

AU - Ball, Simon

AU - McWilliams, Chris

AU - Roguski, Lukasz

AU - Borca, Florina

AU - Batchelor, James

AU - Amundsen, Erik Koldberg

AU - Wu, Xiaodong

AU - Gkoutos, Georgios V

AU - Sun, Jiaxing

AU - Pinto, Ashwin

AU - Guthrie, Bruce

AU - Breen, Cormac

AU - Douiri, Abdel

AU - Wu, Honghan

AU - Curcin, Vasa

AU - Teo, James T

AU - Shah, Ajay M

AU - Dobson, Richard J B

N1 - Publisher Copyright: © 2021, The Author(s).

PY - 2021/1/21

Y1 - 2021/1/21

N2 - 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.

AB - 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.

KW - Aged

KW - COVID-19/diagnosis

KW - Cohort Studies

KW - Early Warning Score

KW - Electronic Health Records

KW - Female

KW - Humans

KW - Male

KW - Middle Aged

KW - Pandemics

KW - Prognosis

KW - SARS-CoV-2/isolation & purification

KW - State Medicine

KW - United Kingdom/epidemiology

KW - NEWS2 score

KW - Prediction model

KW - Blood parameters

KW - COVID-19

UR - http://www.scopus.com/inward/record.url?scp=85099676867&partnerID=8YFLogxK

U2 - 10.1186/s12916-020-01893-3

DO - 10.1186/s12916-020-01893-3

M3 - Article

C2 - 33472631

VL - 19

JO - BMC medicine

JF - BMC medicine

SN - 1741-7015

IS - 1

M1 - 23

ER -