Your browser doesn't support javascript.
loading
Supplementing the National Early Warning Score (NEWS2) for anticipating early deterioration among patients with COVID-19 infection
Ewan Carr; Rebecca Bendayan; Daniel Bean; Matthew Stammers; Wenjuan Wang; Huayu Zhang; Thomas Searle; Zeljko Kraljevic; Anthony Shek; Hang T T Phan; Walter Muruet; Rishi K Gupta; Anthony J Shinton; Mike Wyatt; Ting Shi; Xin Zhang; Andrew Pickles; Daniel Stahl; Rosita Zakeri; Mahdad Noursadeghi; Kevin O'Gallagher; Matt Rogers; Amos Folarin; Christopher Bourdeaux; Chris McWilliams; Lukasz Roguski; Florina Borca; James Batchelor; Xiaodong Wu; Jiaxing Sun; Ashwin Pinto; Bruce Guthrie; Cormac Breen; Abdel Douiri; Honghan Wu; Vasa Curcin; James T Teo; Ajay Shah; Richard Dobson.
Affiliation
  • Ewan Carr; King's College London
  • Rebecca Bendayan; King's College London
  • Daniel Bean; King's College London
  • Matthew Stammers; Clinical Informatics Research Unit, University of Southampton
  • Wenjuan Wang; King's College London
  • Huayu Zhang; University of Edinburgh
  • Thomas Searle; King's College London
  • Zeljko Kraljevic; King's College London
  • Anthony Shek; King's College London
  • Hang T T Phan; Clinical Informatics Research Unit, University of Southampton
  • Walter Muruet; King's College London
  • Rishi K Gupta; University College London
  • Anthony J Shinton; UHS Digital, University Hospital Southampton
  • Mike Wyatt; University Hospitals Bristol NHS Foundation Trust, Bristol, UK
  • Ting Shi; Usher Institute, University of Edinburgh
  • Xin Zhang; Department of Pulmonary and Critical Care Medicine, People's Liberation Army Joint Logistic Support Force 920th Hospital, Yunnan, China
  • Andrew Pickles; King's College London
  • Daniel Stahl; King's College London
  • Rosita Zakeri; King's College London
  • Mahdad Noursadeghi; UCL Division of Infection and Immunity, University College London Hospitals NHS Trust
  • Kevin O'Gallagher; King's College London
  • Matt Rogers; University Hospitals Bristol NHS Foundation Trust, Bristol, U.K.
  • Amos Folarin; King's College London
  • Christopher Bourdeaux; University Hospitals Bristol NHS Foundation Trust, Bristol, U.K.
  • Chris McWilliams; Department of Engineering Mathematics, University of Bristol, Bristol, UK
  • Lukasz Roguski; University College London
  • Florina Borca; University of Southampton
  • James Batchelor; Clinical Informatics Research Unit, University of Southampton, Coxford Rd, Southampton SO16 5AF
  • Xiaodong Wu; Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai, China
  • Jiaxing Sun; Department of Pulmonary and Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai, China
  • Ashwin Pinto; UHS Digital, University Hospital Southampton
  • Bruce Guthrie; Usher Institute, University of Edinburgh
  • Cormac Breen; King's College London
  • Abdel Douiri; King's College London
  • Honghan Wu; University College London
  • Vasa Curcin; King's College London
  • James T Teo; Kings College Hospital NHS Foundation Trust
  • Ajay Shah; King's College London
  • Richard Dobson; Kings College London
Preprint in English | medRxiv | ID: ppmedrxiv-20078006
ABSTRACT
BackgroundThe National Early Warning Score (NEWS2) is currently recommended in the United Kingdom for risk stratification of COVID outcomes, but little is known about its ability to detect severe cases. We aimed to evaluate NEWS2 for severe COVID outcome and identify and validate a set of routinely-collected blood and physiological parameters taken at hospital admission to improve the score. MethodsTraining cohorts comprised 1276 patients admitted to Kings College Hospital NHS Foundation Trust with COVID-19 disease from 1st March to 30th April 2020. External validation cohorts included 5037 patients from four UK NHS Trusts (Guys and St Thomas Hospitals, University Hospitals Southampton, University Hospitals Bristol and Weston NHS Foundation Trust, University College London Hospitals), and two hospitals in Wuhan, China (Wuhan Sixth Hospital and Taikang Tongji Hospital). The outcome was severe COVID disease (transfer to intensive care unit 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. ResultsA baseline model of NEWS2 + age had poor-to-moderate discrimination for severe COVID infection at 14 days (AUC in training sample = 0.700; 95% 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, CRP, estimated GFR, neutrophil count, neutrophil/lymphocyte ratio) improved discrimination (AUC = 0.735; 95% CI 0.715, 0.757) and these improvements were replicated across five UK and non-UK sites. However, there was evidence of miscalibration with the model tending to underestimate risks in most sites. ConclusionsNEWS2 score had poor-to-moderate discrimination for medium-term COVID 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. KO_SCPLOWEYC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWMESSAGESC_SCPLOWO_LIThe National Early Warning Score (NEWS2), currently recommended for stratification of severe COVID-19 disease in the UK, showed poor-to-moderate discrimination for medium-term outcomes (14-day transfer to ICU or death) among COVID-19 patients. C_LIO_LIRisk stratification was improved by the addition of routinely-measured blood and physiological parameters routinely at hospital admission (supplemental oxygen, urea, oxygen saturation, CRP, estimated GFR, neutrophil count, neutrophil/lymphocyte ratio) which provided moderate improvements in a risk stratification model for 14-day ICU/death. C_LIO_LIThis improvement over NEWS2 alone was maintained across multiple hospital trusts but the model tended to be miscalibrated with risks of severe outcomes underestimated in most sites. C_LIO_LIWe benefited from existing pipelines for informatics at KCH such as CogStack that allowed rapid extraction and processing of electronic health records. This methodological approach provided rapid insights and allowed us to overcome the complications associated with slow data centralisation approaches. C_LI
License
cc_by_nc_nd
Full text: Available Collection: Preprints Database: medRxiv Type of study: Cohort_studies / Diagnostic study / Experimental_studies / Observational study / Prognostic study Language: English Year: 2020 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Type of study: Cohort_studies / Diagnostic study / Experimental_studies / Observational study / Prognostic study Language: English Year: 2020 Document type: Preprint
...